{
  "success": true,
  "version": "v2.2 Forward-Looking Anti-Softness Release",
  "snapshot_date": "2026-10-12",
  "count": 50,
  "governance": "Zero-Incentive-Protocol (ZIP-1.0) & Anti-Softness Firewall",
  "methodology": {
    "name": "AKI Grounded Intelligence Engine™ v2.2 Forward-Looking Anti-Softness Formula",
    "version": "2.2.0-AntiSoftness",
    "snapshot_date": "2026-10-12",
    "weights": {
      "hard_capability": 0.29,
      "coding_swe": 0.18,
      "reasoning_math": 0.14,
      "agentic_computer_use": 0.13,
      "science_knowledge": 0.1,
      "efficiency_value": 0.07,
      "openness_reproducibility": 0.05,
      "freshness_stability": 0.03,
      "preference_diversity": 0.01
    },
    "velocity_bonus_formula": "min(3.0, max(0.0, 90d_improvement_pts * 0.6))",
    "social_velocity_penalty": "max(0, (Weighted_Social_Share - 20%) * 0.5)",
    "media_hype_penalty": "max(0, (Media_Mentions - Independent_Replications) / Media_Mentions * 0.3) * 5",
    "single_source_cap_pct": 22,
    "lab_concentration_top5_cap": 3,
    "governance": "Zero-Incentive-Protocol (ZIP-1.0) Non-Sponsored Actuarial Standard"
  },
  "summary": {
    "total_models": 50,
    "open_weights_models": 22,
    "proprietary_models": 28,
    "mean_aki_score": 75,
    "mean_confidence_pct": 86,
    "leader": "Gemini 4 Argon High",
    "leader_score": 93.2,
    "runner_up": "GPT-6 Astra Max",
    "runner_up_score": 92,
    "top_open_weight": "Llama Spark 1.3 Max",
    "top_open_weight_score": 88.4,
    "fastest_velocity": "Grok 4.7 xhigh (+3.00 velocity bonus)",
    "best_value": "Qwen 3.8 Max ($0.40 / $0.80) & DeepSeek V4.1 Flash Max ($0.20 / $0.80)"
  },
  "models": [
    {
      "rank": 1,
      "model_id": "gemini-4-argon-high",
      "name": "Gemini 4 Argon High",
      "developer": "Google",
      "license_type": "proprietary",
      "aki_score_v2_2": 93.2,
      "confidence_pct": 88,
      "uncertainty_range": 1.8,
      "evidence_signal": "Strong early independent signals + Arena + high velocity",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 10,
      "change_from_v2_1": "+2.1",
      "why_ranked_here": "Why #1: Strong early independent signals + Arena + high velocity — Top drivers: Hard Capability 93rd percentile + Agentic 94th percentile — Rate of improvement +4.8 last 90 days → velocity bonus +2.88 — Social velocity penalty 0 — Pricing $2/$10 excellent value — Forward-looking #1.",
      "reasoning_score": 98.6,
      "agent_code_score": 94.2,
      "hard_capability_score": 93,
      "efficiency_score": 91,
      "openness_score": 60,
      "freshness_score": 95,
      "velocity_bonus": 2.88,
      "context_window": "2M",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 2,
      "model_id": "gpt-6-astra-max",
      "name": "GPT-6 Astra Max",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 92,
      "confidence_pct": 93,
      "uncertainty_range": 1.1,
      "evidence_signal": "Extremely broad independent evidence",
      "pricing_input_per_m": 10,
      "pricing_output_per_m": 50,
      "change_from_v2_1": "-0.4",
      "why_ranked_here": "Why #2: Extremely broad independent evidence — Top drivers: Hard Capability 96th percentile + Reasoning 95th percentile — Social velocity penalty -5 applied — Pricing $10/$50 — Highest multi-source consensus — Slightly reduced historical advantage Hard 32%→29%.",
      "reasoning_score": 99.4,
      "agent_code_score": 81.4,
      "hard_capability_score": 96,
      "efficiency_score": 75,
      "openness_score": 55,
      "freshness_score": 88,
      "velocity_bonus": 0.72,
      "context_window": "1M",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 3,
      "model_id": "claude-opus-5.5-max",
      "name": "Claude Opus 5.5 Max/Thinking",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 90.1,
      "confidence_pct": 93,
      "uncertainty_range": 1.1,
      "evidence_signal": "Deep independent evidence base",
      "pricing_input_per_m": 4,
      "pricing_output_per_m": 20,
      "change_from_v2_1": "-0.5",
      "why_ranked_here": "Why #3: Deep independent evidence base — Top drivers: Coding & SWE 94th percentile + Hard 92nd percentile — Social velocity penalty -7.5 applied — Still elite hype filtered — Pricing $4/$20 — Confidence 95%→93% reduced historical advantage.",
      "reasoning_score": 99.1,
      "agent_code_score": 94,
      "hard_capability_score": 92,
      "efficiency_score": 82,
      "openness_score": 55,
      "freshness_score": 89,
      "velocity_bonus": 0.5,
      "context_window": "500k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 4,
      "model_id": "llama-spark-1.3-max",
      "name": "Llama Spark 1.3 Max",
      "developer": "Meta",
      "license_type": "open_weights",
      "aki_score_v2_2": 88.4,
      "confidence_pct": 90,
      "uncertainty_range": 1.5,
      "evidence_signal": "Solid agentic + multimodal + velocity",
      "pricing_input_per_m": 1.25,
      "pricing_output_per_m": 4.25,
      "change_from_v2_1": "+2.1",
      "why_ranked_here": "Why #4: Solid agentic + multimodal + velocity — Top drivers: Agentic 91st percentile + Openness 95th percentile open-weight — Velocity +1.86 — Agentic 11%→13% +1.0 + openness 3%→5% +1.0 — Pricing ~$1.25/$4.25 good price — Rising.",
      "reasoning_score": 94.5,
      "agent_code_score": 91,
      "hard_capability_score": 87,
      "efficiency_score": 88,
      "openness_score": 95,
      "freshness_score": 92,
      "velocity_bonus": 1.86,
      "context_window": "256k",
      "official_url": "https://ai.meta.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 5,
      "model_id": "claude-sonnet-5.5-max",
      "name": "Claude Sonnet 5.5 Max",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 88.2,
      "confidence_pct": 91,
      "uncertainty_range": 1.4,
      "evidence_signal": "Excellent breadth + value",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 10,
      "change_from_v2_1": "-1.5",
      "why_ranked_here": "Why #5: Excellent breadth + value — Top drivers: Coding 90th percentile + Efficiency 89th percentile — Velocity +0.4 — Best pure value top tier — Outstanding coding/agent + value less hype than Opus/Fable.",
      "reasoning_score": 96,
      "agent_code_score": 90,
      "hard_capability_score": 88,
      "efficiency_score": 89,
      "openness_score": 55,
      "freshness_score": 87,
      "velocity_bonus": 0.4,
      "context_window": "500k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 6,
      "model_id": "grok-4.7-xhigh",
      "name": "Grok 4.7 xhigh",
      "developer": "xAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 88,
      "confidence_pct": 88,
      "uncertainty_range": 1.8,
      "evidence_signal": "Clear agentic & coding progress + velocity",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 6,
      "change_from_v2_1": "+2.9",
      "why_ranked_here": "Why #6: Clear agentic & coding progress + velocity — Top drivers: Agentic 93rd percentile + Coding 87th percentile — Velocity +3 cap fastest improvement +5.2 last 90 days — Pricing $2/$6 — X-native tools.",
      "reasoning_score": 95,
      "agent_code_score": 93,
      "hard_capability_score": 86,
      "efficiency_score": 87,
      "openness_score": 60,
      "freshness_score": 94,
      "velocity_bonus": 3,
      "context_window": "2M",
      "official_url": "https://x.ai",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 7,
      "model_id": "qwen-3.8-max",
      "name": "Qwen 3.8 Max",
      "developer": "Alibaba",
      "license_type": "open_weights",
      "aki_score_v2_2": 86.1,
      "confidence_pct": 90,
      "uncertainty_range": 1.5,
      "evidence_signal": "Strong coding + multilingual + open",
      "pricing_input_per_m": 0.4,
      "pricing_output_per_m": 0.8,
      "change_from_v2_1": "+2.5",
      "why_ranked_here": "Why #7: Strong coding + multilingual + open — Top drivers: Coding 89th percentile + Openness 94th percentile open-weight — Velocity +1.68 — Openness +1.0 — Leading open-weight.",
      "reasoning_score": 94,
      "agent_code_score": 89,
      "hard_capability_score": 84,
      "efficiency_score": 91,
      "openness_score": 94,
      "freshness_score": 91,
      "velocity_bonus": 1.68,
      "context_window": "256k",
      "official_url": "https://qwenlm.github.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 8,
      "model_id": "deepseek-v4-pro-max",
      "name": "DeepSeek V4 Pro Max",
      "developer": "DeepSeek",
      "license_type": "open_weights",
      "aki_score_v2_2": 85.2,
      "confidence_pct": 90,
      "uncertainty_range": 1.5,
      "evidence_signal": "Strong open-weight reasoning + value + velocity",
      "pricing_input_per_m": 0.66,
      "pricing_output_per_m": 1.98,
      "change_from_v2_1": "+3.1",
      "why_ranked_here": "Why #8: Strong open-weight reasoning + value + velocity — Top drivers: Efficiency 92nd percentile best pure value + Openness 95th percentile — Velocity +1.44 — Extreme cost efficiency + open.",
      "reasoning_score": 97,
      "agent_code_score": 86,
      "hard_capability_score": 83,
      "efficiency_score": 92,
      "openness_score": 95,
      "freshness_score": 90,
      "velocity_bonus": 1.44,
      "context_window": "256k",
      "official_url": "https://deepseek.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 9,
      "model_id": "glm-5.3-max",
      "name": "GLM-5.3 Max",
      "developer": "Z.AI",
      "license_type": "open_weights",
      "aki_score_v2_2": 85,
      "confidence_pct": 89,
      "uncertainty_range": 1.6,
      "evidence_signal": "Competitive reasoning/coding + open",
      "pricing_input_per_m": 1.4,
      "pricing_output_per_m": 4.4,
      "change_from_v2_1": "+2.1",
      "why_ranked_here": "Why #9: Competitive reasoning/coding + open — Top drivers: Reasoning 87th percentile + Openness 93rd percentile — Openness +1.0 — Good value.",
      "reasoning_score": 93,
      "agent_code_score": 85,
      "hard_capability_score": 83,
      "efficiency_score": 88,
      "openness_score": 93,
      "freshness_score": 89,
      "velocity_bonus": 1.2,
      "context_window": "200k",
      "official_url": "https://zhipuai.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 10,
      "model_id": "kimi-k3-max",
      "name": "Kimi K3 Max",
      "developer": "Moonshot",
      "license_type": "proprietary",
      "aki_score_v2_2": 84.8,
      "confidence_pct": 90,
      "uncertainty_range": 1.5,
      "evidence_signal": "Exceptional long-context + velocity",
      "pricing_input_per_m": 2.7,
      "pricing_output_per_m": 13.5,
      "change_from_v2_1": "+0.6",
      "why_ranked_here": "Why #10: Exceptional long-context + velocity — Top drivers: Reasoning 88th percentile + Agentic 86th percentile long-context — Velocity +0.6 — Solid strong reasoning & long context.",
      "reasoning_score": 94,
      "agent_code_score": 86,
      "hard_capability_score": 82,
      "efficiency_score": 81,
      "openness_score": 60,
      "freshness_score": 90,
      "velocity_bonus": 0.6,
      "context_window": "500k",
      "official_url": "https://moonshot.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 11,
      "model_id": "gpt-6.1-sol-max",
      "name": "GPT-6.1 Sol Max",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 84.5,
      "confidence_pct": 87,
      "uncertainty_range": 1.9,
      "evidence_signal": "Near-Astra intelligence at low cost",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 10,
      "change_from_v2_1": "-4.4",
      "why_ranked_here": "Why #11: Near-Astra intelligence at low cost — Top drivers: Efficiency 91st percentile + Hard 85th percentile — Near-Astra at ~1/5 cost — Efficiency king — Was 88.9 #5 now #11 because hard reduction hits efficiency-focused model.",
      "reasoning_score": 93,
      "agent_code_score": 84,
      "hard_capability_score": 85,
      "efficiency_score": 91,
      "openness_score": 55,
      "freshness_score": 86,
      "velocity_bonus": 0.4,
      "context_window": "500k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 12,
      "model_id": "claude-fable-5.1-max",
      "name": "Claude Fable 5.1 Max",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 84.3,
      "confidence_pct": 91,
      "uncertainty_range": 1.4,
      "evidence_signal": "Strong coding & long-horizon",
      "pricing_input_per_m": 10,
      "pricing_output_per_m": 50,
      "change_from_v2_1": "-3.5",
      "why_ranked_here": "Why #12: Strong coding & long-horizon — Top drivers: Coding 88th percentile + Agentic 87th percentile long-horizon — Strong coding & long-horizon — Still top-tier after penalty expensive + high social noise.",
      "reasoning_score": 99.6,
      "agent_code_score": 88,
      "hard_capability_score": 91,
      "efficiency_score": 65,
      "openness_score": 55,
      "freshness_score": 88,
      "velocity_bonus": 0.2,
      "context_window": "500k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 13,
      "model_id": "mimo-v2.6-pro",
      "name": "MiMo-V2.6-Pro",
      "developer": "Xiaomi",
      "license_type": "open_weights",
      "aki_score_v2_2": 83.2,
      "confidence_pct": 87,
      "uncertainty_range": 1.9,
      "evidence_signal": "Leading open-weight contender + velocity",
      "pricing_input_per_m": 0.4,
      "pricing_output_per_m": 0.8,
      "change_from_v2_1": "+3.3",
      "why_ranked_here": "Why #13: Leading open-weight contender + velocity — Top drivers: Openness 96th percentile open-weight + Efficiency 90th percentile $0.40/$0.80 best value — Velocity +1.2 — Best open-weight overall.",
      "reasoning_score": 89,
      "agent_code_score": 84,
      "hard_capability_score": 81,
      "efficiency_score": 90,
      "openness_score": 96,
      "freshness_score": 88,
      "velocity_bonus": 1.2,
      "context_window": "256k",
      "official_url": "https://github.com/xiaomi",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 14,
      "model_id": "claude-opus-5",
      "name": "Claude Opus 5",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 80.9,
      "confidence_pct": 89,
      "uncertainty_range": 1.6,
      "evidence_signal": "Deep historical evidence",
      "pricing_input_per_m": 5,
      "pricing_output_per_m": 25,
      "change_from_v2_1": "-0.5",
      "why_ranked_here": "Why #14: Deep historical evidence — Top drivers: Hard 84th percentile + Coding 83rd percentile — Previous-gen but still competitive — Deep historical evidence.",
      "reasoning_score": 92,
      "agent_code_score": 83,
      "hard_capability_score": 84,
      "efficiency_score": 75,
      "openness_score": 55,
      "freshness_score": 85,
      "velocity_bonus": 0.1,
      "context_window": "500k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 15,
      "model_id": "gpt-6-sol-max",
      "name": "GPT-6 Sol Max",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 80.2,
      "confidence_pct": 85,
      "uncertainty_range": 2.2,
      "evidence_signal": "Balanced everyday frontier",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 10,
      "change_from_v2_1": "-0.5",
      "why_ranked_here": "Why #15: Balanced everyday frontier — Top drivers: Efficiency 86th percentile + Reasoning 82nd percentile — Reliable — Balanced frontier everyday model.",
      "reasoning_score": 90,
      "agent_code_score": 82,
      "hard_capability_score": 81,
      "efficiency_score": 86,
      "openness_score": 55,
      "freshness_score": 84,
      "velocity_bonus": 0.1,
      "context_window": "256k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 16,
      "model_id": "deepseek-v4.1-flash-max",
      "name": "DeepSeek V4.1 Flash Max",
      "developer": "DeepSeek",
      "license_type": "open_weights",
      "aki_score_v2_2": 80.5,
      "confidence_pct": 89,
      "uncertainty_range": 1.6,
      "evidence_signal": "Extreme efficiency + open",
      "pricing_input_per_m": 0.2,
      "pricing_output_per_m": 0.8,
      "change_from_v2_1": "+1.3",
      "why_ranked_here": "Why #16: Extreme efficiency + open — Top drivers: Efficiency 94th percentile budget king + Openness 94th percentile — Openness + velocity — Budget king cheapest high-performer.",
      "reasoning_score": 88,
      "agent_code_score": 81,
      "hard_capability_score": 79,
      "efficiency_score": 94,
      "openness_score": 94,
      "freshness_score": 89,
      "velocity_bonus": 1.1,
      "context_window": "256k",
      "official_url": "https://deepseek.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 17,
      "model_id": "gemini-3.8-flash",
      "name": "Gemini 3.8 Flash",
      "developer": "Google",
      "license_type": "proprietary",
      "aki_score_v2_2": 78.9,
      "confidence_pct": 88,
      "uncertainty_range": 1.8,
      "evidence_signal": "Speed + price",
      "pricing_input_per_m": 0.75,
      "pricing_output_per_m": 3.75,
      "change_from_v2_1": "+0.5",
      "why_ranked_here": "Why #17: Speed + price — Top drivers: Efficiency 88th percentile + Agentic 82nd percentile — High-volume workhorse.",
      "reasoning_score": 87,
      "agent_code_score": 82,
      "hard_capability_score": 78,
      "efficiency_score": 88,
      "openness_score": 55,
      "freshness_score": 87,
      "velocity_bonus": 0.4,
      "context_window": "1M",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 18,
      "model_id": "step-5-preview",
      "name": "Step 5 Preview",
      "developer": "StepFun",
      "license_type": "proprietary",
      "aki_score_v2_2": 78.8,
      "confidence_pct": 84,
      "uncertainty_range": 2.4,
      "evidence_signal": "Emerging frontier",
      "pricing_input_per_m": 0.5,
      "pricing_output_per_m": 2,
      "change_from_v2_1": "+1.2",
      "why_ranked_here": "Why #18: Emerging frontier — Top drivers: Reasoning 82nd percentile + Hard 80th percentile — Velocity +1.2 — Emerging frontier.",
      "reasoning_score": 88,
      "agent_code_score": 78,
      "hard_capability_score": 80,
      "efficiency_score": 84,
      "openness_score": 55,
      "freshness_score": 88,
      "velocity_bonus": 1.2,
      "context_window": "256k",
      "official_url": "https://stepfun.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 19,
      "model_id": "grok-4.6",
      "name": "Grok 4.6",
      "developer": "xAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 77.3,
      "confidence_pct": 85,
      "uncertainty_range": 2.2,
      "evidence_signal": "Previous generation",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 6,
      "change_from_v2_1": "+0.5",
      "why_ranked_here": "Why #19: Previous generation — Top drivers: Coding 81st percentile + Agentic 80th percentile — Previous Grok generation.",
      "reasoning_score": 86,
      "agent_code_score": 81,
      "hard_capability_score": 77,
      "efficiency_score": 82,
      "openness_score": 60,
      "freshness_score": 83,
      "velocity_bonus": 0.3,
      "context_window": "1M",
      "official_url": "https://x.ai",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 20,
      "model_id": "claude-fable-5",
      "name": "Claude Fable 5",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 75.8,
      "confidence_pct": 89,
      "uncertainty_range": 1.6,
      "evidence_signal": "Deep evidence base",
      "pricing_input_per_m": 10,
      "pricing_output_per_m": 50,
      "change_from_v2_1": "-0.3",
      "why_ranked_here": "Why #20: Deep evidence base — Top drivers: Coding 82nd percentile + Reasoning 81st percentile — Deep evidence base.",
      "reasoning_score": 89,
      "agent_code_score": 82,
      "hard_capability_score": 79,
      "efficiency_score": 60,
      "openness_score": 55,
      "freshness_score": 85,
      "velocity_bonus": 0.1,
      "context_window": "500k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 21,
      "model_id": "qwen-3.8-27b",
      "name": "Qwen 3.8 27B",
      "developer": "Alibaba",
      "license_type": "open_weights",
      "aki_score_v2_2": 77,
      "confidence_pct": 87,
      "uncertainty_range": 1.9,
      "evidence_signal": "Strong open model + open",
      "pricing_input_per_m": 0.2,
      "pricing_output_per_m": 0.6,
      "change_from_v2_1": "+1.7",
      "why_ranked_here": "Why #21: Strong open model + open — Top drivers: Openness 93rd percentile + Coding 84th percentile — Strong open model.",
      "reasoning_score": 85,
      "agent_code_score": 84,
      "hard_capability_score": 76,
      "efficiency_score": 89,
      "openness_score": 93,
      "freshness_score": 88,
      "velocity_bonus": 1.2,
      "context_window": "128k",
      "official_url": "https://qwenlm.github.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 22,
      "model_id": "glm-5.3-flash",
      "name": "GLM-5.3 Flash",
      "developer": "Z.AI",
      "license_type": "open_weights",
      "aki_score_v2_2": 76.2,
      "confidence_pct": 86,
      "uncertainty_range": 2.1,
      "evidence_signal": "High efficiency open + open",
      "pricing_input_per_m": 0.15,
      "pricing_output_per_m": 0.5,
      "change_from_v2_1": "+1.5",
      "why_ranked_here": "Why #22: High efficiency open + open — Top drivers: Efficiency 92nd percentile extreme value + Openness 92nd percentile — Extreme value.",
      "reasoning_score": 84,
      "agent_code_score": 80,
      "hard_capability_score": 75,
      "efficiency_score": 92,
      "openness_score": 92,
      "freshness_score": 87,
      "velocity_bonus": 1.1,
      "context_window": "128k",
      "official_url": "https://zhipuai.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 23,
      "model_id": "deepseek-v4-flash",
      "name": "DeepSeek V4 Flash",
      "developer": "DeepSeek",
      "license_type": "open_weights",
      "aki_score_v2_2": 75.8,
      "confidence_pct": 85,
      "uncertainty_range": 2.2,
      "evidence_signal": "Budget high-performer + open",
      "pricing_input_per_m": 0.14,
      "pricing_output_per_m": 0.28,
      "change_from_v2_1": "+1.7",
      "why_ranked_here": "Why #23: Budget high-performer + open — Top drivers: Efficiency 93rd percentile + Openness 93rd percentile — Budget high-performer.",
      "reasoning_score": 83,
      "agent_code_score": 79,
      "hard_capability_score": 74,
      "efficiency_score": 93,
      "openness_score": 93,
      "freshness_score": 86,
      "velocity_bonus": 1,
      "context_window": "128k",
      "official_url": "https://deepseek.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 24,
      "model_id": "gpt-6-luna",
      "name": "GPT-6 Luna",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 72.8,
      "confidence_pct": 80,
      "uncertainty_range": 3,
      "evidence_signal": "Ultra-cheap tier",
      "pricing_input_per_m": 0.1,
      "pricing_output_per_m": 0.5,
      "change_from_v2_1": "-0.4",
      "why_ranked_here": "Why #24: Ultra-cheap tier — Top drivers: Efficiency 90th percentile ultra-cheap + Freshness 80th percentile — High-volume only not intelligence-focused.",
      "reasoning_score": 80,
      "agent_code_score": 76,
      "hard_capability_score": 71,
      "efficiency_score": 90,
      "openness_score": 55,
      "freshness_score": 82,
      "velocity_bonus": 0.2,
      "context_window": "128k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 25,
      "model_id": "minimax-m3",
      "name": "MiniMax M3",
      "developer": "MiniMax",
      "license_type": "open_weights",
      "aki_score_v2_2": 74,
      "confidence_pct": 81,
      "uncertainty_range": 2.8,
      "evidence_signal": "Growing evidence + open",
      "pricing_input_per_m": 0.3,
      "pricing_output_per_m": 1.2,
      "change_from_v2_1": "+1.5",
      "why_ranked_here": "Why #25: Growing evidence + open — Top drivers: Openness 88th percentile + Reasoning 78th percentile — Growing evidence — Emerging.",
      "reasoning_score": 82,
      "agent_code_score": 75,
      "hard_capability_score": 72,
      "efficiency_score": 86,
      "openness_score": 88,
      "freshness_score": 83,
      "velocity_bonus": 1.1,
      "context_window": "256k",
      "official_url": "https://minimax.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 26,
      "model_id": "gpt-6-mini",
      "name": "GPT-6 Mini",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 73.5,
      "confidence_pct": 82,
      "uncertainty_range": 2.7,
      "evidence_signal": "Emerging cheap tier",
      "pricing_input_per_m": 0.2,
      "pricing_output_per_m": 1,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #26: New entry #26 — GPT-6 Mini — AKI 73.5 · Conf 82% — Near-GPT-6 Sol intelligence at mini cost — Top drivers: Efficiency 91st percentile + Reasoning 79th percentile — Freshness boost +8% new high-quality independent evidence <14 days.",
      "reasoning_score": 81,
      "agent_code_score": 75,
      "hard_capability_score": 71,
      "efficiency_score": 91,
      "openness_score": 55,
      "freshness_score": 89,
      "velocity_bonus": 0.8,
      "context_window": "256k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 27,
      "model_id": "claude-haiku-5.5",
      "name": "Claude Haiku 5.5",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 73,
      "confidence_pct": 84,
      "uncertainty_range": 2.4,
      "evidence_signal": "Fast + cheap Claude",
      "pricing_input_per_m": 0.5,
      "pricing_output_per_m": 2.5,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #27: New entry #27 — Claude Haiku 5.5 — AKI 73.0 · Conf 84% — Fast + cheap Claude — Top drivers: Efficiency 89th percentile + Coding 80th percentile — Social velocity penalty -3 — Pricing $0.50/$2.50 — Emerging.",
      "reasoning_score": 80,
      "agent_code_score": 80,
      "hard_capability_score": 72,
      "efficiency_score": 89,
      "openness_score": 55,
      "freshness_score": 86,
      "velocity_bonus": 0.6,
      "context_window": "256k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 28,
      "model_id": "gemini-4-flash-high",
      "name": "Gemini 4 Flash High",
      "developer": "Google",
      "license_type": "proprietary",
      "aki_score_v2_2": 72.8,
      "confidence_pct": 83,
      "uncertainty_range": 2.5,
      "evidence_signal": "Speed + Argon lineage",
      "pricing_input_per_m": 0.5,
      "pricing_output_per_m": 2,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #28: New entry #28 — Gemini 4 Flash High — AKI 72.8 · Conf 83% — Speed + Argon lineage — Top drivers: Efficiency 90th percentile + Agentic 83rd percentile — Freshness boost +10% — Pricing $0.50/$2.00 — Emerging.",
      "reasoning_score": 81,
      "agent_code_score": 83,
      "hard_capability_score": 71,
      "efficiency_score": 90,
      "openness_score": 55,
      "freshness_score": 89,
      "velocity_bonus": 0.9,
      "context_window": "1M",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 29,
      "model_id": "kimi-k4-max",
      "name": "Kimi K4 Max",
      "developer": "Moonshot",
      "license_type": "proprietary",
      "aki_score_v2_2": 71.8,
      "confidence_pct": 82,
      "uncertainty_range": 2.7,
      "evidence_signal": "Exceptional long-context 1M+",
      "pricing_input_per_m": 2.5,
      "pricing_output_per_m": 12,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #29: New entry #29 — Kimi K4 Max — AKI 71.8 · Conf 82% — Exceptional long-context 1M+ — Top drivers: Reasoning 84th percentile + Openness 90th percentile — Freshness boost +8% new high-quality independent evidence <14 days.",
      "reasoning_score": 84,
      "agent_code_score": 77,
      "hard_capability_score": 70,
      "efficiency_score": 79,
      "openness_score": 60,
      "freshness_score": 88,
      "velocity_bonus": 0.7,
      "context_window": "1M",
      "official_url": "https://moonshot.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 30,
      "model_id": "deepseek-v5-pro",
      "name": "DeepSeek V5 Pro",
      "developer": "DeepSeek",
      "license_type": "open_weights",
      "aki_score_v2_2": 71.5,
      "confidence_pct": 83,
      "uncertainty_range": 2.5,
      "evidence_signal": "Next-gen open-weight",
      "pricing_input_per_m": 0.7,
      "pricing_output_per_m": 2.1,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #30: New entry #30 — DeepSeek V5 Pro — AKI 71.5 · Conf 83% — Next-gen open-weight — Top drivers: Openness 95th percentile + Coding 82nd percentile — Velocity +1.5 — Pricing ~$0.70/$2.10 — Emerging.",
      "reasoning_score": 82,
      "agent_code_score": 82,
      "hard_capability_score": 71,
      "efficiency_score": 88,
      "openness_score": 95,
      "freshness_score": 88,
      "velocity_bonus": 1.5,
      "context_window": "256k",
      "official_url": "https://deepseek.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 31,
      "model_id": "qwen-3.9-max",
      "name": "Qwen 3.9 Max",
      "developer": "Alibaba",
      "license_type": "open_weights",
      "aki_score_v2_2": 70.8,
      "confidence_pct": 84,
      "uncertainty_range": 2.4,
      "evidence_signal": "Coding + multilingual + open",
      "pricing_input_per_m": 2.2,
      "pricing_output_per_m": 6.5,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #31: New entry #31 — Qwen 3.9 Max — AKI 70.8 · Conf 84% — Coding + multilingual + open — Top drivers: Coding 85th percentile + Openness 94th percentile — Velocity +1.2 — Pricing $2.20/$6.50 — Emerging.",
      "reasoning_score": 82,
      "agent_code_score": 85,
      "hard_capability_score": 70,
      "efficiency_score": 83,
      "openness_score": 94,
      "freshness_score": 87,
      "velocity_bonus": 1.2,
      "context_window": "256k",
      "official_url": "https://qwenlm.github.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 32,
      "model_id": "glm-6-preview",
      "name": "GLM-6 Preview",
      "developer": "Z.AI",
      "license_type": "open_weights",
      "aki_score_v2_2": 70.2,
      "confidence_pct": 81,
      "uncertainty_range": 2.8,
      "evidence_signal": "Next-gen reasoning + open",
      "pricing_input_per_m": 1.5,
      "pricing_output_per_m": 4.8,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #32: New entry #32 — GLM-6 Preview — AKI 70.2 · Conf 81% — Next-gen reasoning + open — Top drivers: Reasoning 83rd percentile + Openness 92nd percentile — Freshness boost +12% — Pricing ~$1.50/$4.80 — Emerging.",
      "reasoning_score": 83,
      "agent_code_score": 78,
      "hard_capability_score": 69,
      "efficiency_score": 84,
      "openness_score": 92,
      "freshness_score": 89,
      "velocity_bonus": 1,
      "context_window": "200k",
      "official_url": "https://zhipuai.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 33,
      "model_id": "mimo-v3-preview",
      "name": "MiMo-V3 Preview",
      "developer": "Xiaomi",
      "license_type": "open_weights",
      "aki_score_v2_2": 69.8,
      "confidence_pct": 80,
      "uncertainty_range": 3,
      "evidence_signal": "Next open-weight contender",
      "pricing_input_per_m": 0.5,
      "pricing_output_per_m": 1,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #33: New entry #33 — MiMo-V3 Preview — AKI 69.8 · Conf 80% — Next open-weight contender — Top drivers: Openness 95th percentile + Efficiency 88th percentile — Velocity +1.0 — Pricing ~$0.50/$1.00 — Emerging.",
      "reasoning_score": 79,
      "agent_code_score": 77,
      "hard_capability_score": 68,
      "efficiency_score": 88,
      "openness_score": 95,
      "freshness_score": 87,
      "velocity_bonus": 1,
      "context_window": "256k",
      "official_url": "https://github.com/xiaomi",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 34,
      "model_id": "llama-spark-1.2",
      "name": "Llama Spark 1.2",
      "developer": "Meta",
      "license_type": "open_weights",
      "aki_score_v2_2": 69.5,
      "confidence_pct": 86,
      "uncertainty_range": 2.1,
      "evidence_signal": "Previous Llama",
      "pricing_input_per_m": 1,
      "pricing_output_per_m": 3.5,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #34: Previous Llama — Top drivers: Agentic 82nd percentile + Openness 90th percentile — Previous-gen but still solid agentic + multimodal — Deep historical evidence.",
      "reasoning_score": 80,
      "agent_code_score": 82,
      "hard_capability_score": 68,
      "efficiency_score": 84,
      "openness_score": 90,
      "freshness_score": 82,
      "velocity_bonus": 0.1,
      "context_window": "128k",
      "official_url": "https://ai.meta.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 35,
      "model_id": "grok-4.5",
      "name": "Grok 4.5",
      "developer": "xAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 69,
      "confidence_pct": 83,
      "uncertainty_range": 2.5,
      "evidence_signal": "Previous Grok",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 6,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #35: Previous Grok — Top drivers: Coding 79th percentile + Agentic 78th percentile — Previous generation.",
      "reasoning_score": 79,
      "agent_code_score": 79,
      "hard_capability_score": 68,
      "efficiency_score": 80,
      "openness_score": 60,
      "freshness_score": 80,
      "velocity_bonus": 0.1,
      "context_window": "1M",
      "official_url": "https://x.ai",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 36,
      "model_id": "claude-opus-4.8",
      "name": "Claude Opus 4.8",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 68.5,
      "confidence_pct": 88,
      "uncertainty_range": 1.8,
      "evidence_signal": "Legacy but still used",
      "pricing_input_per_m": 5,
      "pricing_output_per_m": 25,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #36: Legacy but still used — Top drivers: Hard 78th percentile + Coding 77th percentile — Deep historical evidence — Legacy.",
      "reasoning_score": 84,
      "agent_code_score": 77,
      "hard_capability_score": 78,
      "efficiency_score": 62,
      "openness_score": 55,
      "freshness_score": 80,
      "velocity_bonus": 0.05,
      "context_window": "200k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 37,
      "model_id": "gpt-4o-legacy",
      "name": "GPT-4o / GPT-5 Legacy",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 68,
      "confidence_pct": 90,
      "uncertainty_range": 1.5,
      "evidence_signal": "Legacy frontier standard",
      "pricing_input_per_m": 2.5,
      "pricing_output_per_m": 10,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #37: Legacy frontier — Top drivers: Hard 77th percentile + Reasoning 76th percentile — Deep historical evidence — Legacy but still used.",
      "reasoning_score": 82,
      "agent_code_score": 75,
      "hard_capability_score": 77,
      "efficiency_score": 75,
      "openness_score": 55,
      "freshness_score": 78,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 38,
      "model_id": "gemini-2.5-pro",
      "name": "Gemini 2.5 Pro",
      "developer": "Google",
      "license_type": "proprietary",
      "aki_score_v2_2": 67.5,
      "confidence_pct": 89,
      "uncertainty_range": 1.6,
      "evidence_signal": "Legacy Gemini",
      "pricing_input_per_m": 1.25,
      "pricing_output_per_m": 5,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #38: Legacy Gemini — Top drivers: Reasoning 77th percentile + Efficiency 76th percentile — Deep historical evidence.",
      "reasoning_score": 81,
      "agent_code_score": 74,
      "hard_capability_score": 75,
      "efficiency_score": 76,
      "openness_score": 55,
      "freshness_score": 78,
      "velocity_bonus": 0,
      "context_window": "1M",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 39,
      "model_id": "kimi-k2.x",
      "name": "Kimi K2.x",
      "developer": "Moonshot",
      "license_type": "proprietary",
      "aki_score_v2_2": 67,
      "confidence_pct": 82,
      "uncertainty_range": 2.7,
      "evidence_signal": "Previous Kimi",
      "pricing_input_per_m": 1.2,
      "pricing_output_per_m": 4.8,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #39: Previous Kimi — Top drivers: Reasoning 76th percentile + Agentic 75th percentile — Previous generation.",
      "reasoning_score": 80,
      "agent_code_score": 75,
      "hard_capability_score": 73,
      "efficiency_score": 77,
      "openness_score": 55,
      "freshness_score": 76,
      "velocity_bonus": 0,
      "context_window": "200k",
      "official_url": "https://moonshot.cn",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 40,
      "model_id": "qwen-3.5-max",
      "name": "Qwen 3.5 Max",
      "developer": "Alibaba",
      "license_type": "open_weights",
      "aki_score_v2_2": 66.5,
      "confidence_pct": 85,
      "uncertainty_range": 2.2,
      "evidence_signal": "Previous Qwen",
      "pricing_input_per_m": 0.8,
      "pricing_output_per_m": 2.4,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #40: Previous Qwen — Top drivers: Coding 77th percentile + Openness 90th percentile — Previous-gen.",
      "reasoning_score": 78,
      "agent_code_score": 77,
      "hard_capability_score": 72,
      "efficiency_score": 82,
      "openness_score": 90,
      "freshness_score": 77,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://qwenlm.github.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 41,
      "model_id": "deepseek-v3",
      "name": "DeepSeek V3",
      "developer": "DeepSeek",
      "license_type": "open_weights",
      "aki_score_v2_2": 66,
      "confidence_pct": 87,
      "uncertainty_range": 1.9,
      "evidence_signal": "Previous DeepSeek",
      "pricing_input_per_m": 0.14,
      "pricing_output_per_m": 0.28,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #41: Previous DeepSeek — Top drivers: Efficiency 87th percentile + Openness 92nd percentile — Previous-gen — Extreme cost efficiency.",
      "reasoning_score": 79,
      "agent_code_score": 74,
      "hard_capability_score": 71,
      "efficiency_score": 87,
      "openness_score": 92,
      "freshness_score": 76,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://deepseek.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 42,
      "model_id": "mistral-large-3",
      "name": "Mistral Large 3",
      "developer": "Mistral",
      "license_type": "open_weights",
      "aki_score_v2_2": 65.5,
      "confidence_pct": 83,
      "uncertainty_range": 2.5,
      "evidence_signal": "European open-weight",
      "pricing_input_per_m": 2,
      "pricing_output_per_m": 6,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #42: European open-weight — Top drivers: Openness 91st percentile + Reasoning 74th percentile — Competitive open-weight.",
      "reasoning_score": 77,
      "agent_code_score": 73,
      "hard_capability_score": 70,
      "efficiency_score": 79,
      "openness_score": 91,
      "freshness_score": 75,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://mistral.ai",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 43,
      "model_id": "command-r-plus",
      "name": "Command R+ / Cohere",
      "developer": "Cohere",
      "license_type": "proprietary",
      "aki_score_v2_2": 65,
      "confidence_pct": 82,
      "uncertainty_range": 2.7,
      "evidence_signal": "RAG + enterprise",
      "pricing_input_per_m": 3,
      "pricing_output_per_m": 15,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #43: RAG + enterprise — Top drivers: Science & Knowledge 76th percentile + Agentic 74th percentile — Enterprise-focused.",
      "reasoning_score": 76,
      "agent_code_score": 74,
      "hard_capability_score": 69,
      "efficiency_score": 74,
      "openness_score": 55,
      "freshness_score": 74,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://cohere.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 44,
      "model_id": "claude-sonnet-4.5",
      "name": "Claude Sonnet 4.5",
      "developer": "Anthropic",
      "license_type": "proprietary",
      "aki_score_v2_2": 64.5,
      "confidence_pct": 87,
      "uncertainty_range": 1.9,
      "evidence_signal": "Previous Sonnet",
      "pricing_input_per_m": 3,
      "pricing_output_per_m": 15,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #44: Previous Sonnet — Top drivers: Coding 75th percentile + Efficiency 73rd percentile — Previous-gen.",
      "reasoning_score": 78,
      "agent_code_score": 75,
      "hard_capability_score": 71,
      "efficiency_score": 73,
      "openness_score": 55,
      "freshness_score": 73,
      "velocity_bonus": 0,
      "context_window": "200k",
      "official_url": "https://anthropic.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 45,
      "model_id": "gpt-6-nano",
      "name": "GPT-6 Nano",
      "developer": "OpenAI",
      "license_type": "proprietary",
      "aki_score_v2_2": 64,
      "confidence_pct": 80,
      "uncertainty_range": 3,
      "evidence_signal": "Ultra-cheap nano",
      "pricing_input_per_m": 0.05,
      "pricing_output_per_m": 0.2,
      "change_from_v2_1": "NEW",
      "why_ranked_here": "Why #45: New entry #45 — GPT-6 Nano — AKI 64.0 · Conf 80% — Ultra-cheap nano — Top drivers: Efficiency 92nd percentile $0.05/$0.20 — Freshness boost +10% — High-volume only not intelligence-focused.",
      "reasoning_score": 73,
      "agent_code_score": 71,
      "hard_capability_score": 66,
      "efficiency_score": 92,
      "openness_score": 55,
      "freshness_score": 87,
      "velocity_bonus": 0.5,
      "context_window": "128k",
      "official_url": "https://openai.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 46,
      "model_id": "gemini-3.5-flash",
      "name": "Gemini 3.5 Flash",
      "developer": "Google",
      "license_type": "proprietary",
      "aki_score_v2_2": 63.5,
      "confidence_pct": 86,
      "uncertainty_range": 2.1,
      "evidence_signal": "Previous Flash",
      "pricing_input_per_m": 0.5,
      "pricing_output_per_m": 2,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #46: Previous Flash — Top drivers: Efficiency 85th percentile + Speed — High-volume workhorse — Previous-gen.",
      "reasoning_score": 75,
      "agent_code_score": 72,
      "hard_capability_score": 68,
      "efficiency_score": 85,
      "openness_score": 55,
      "freshness_score": 72,
      "velocity_bonus": 0,
      "context_window": "500k",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 47,
      "model_id": "phi-4-microsoft",
      "name": "Phi-4 / Microsoft",
      "developer": "Microsoft",
      "license_type": "open_weights",
      "aki_score_v2_2": 63,
      "confidence_pct": 84,
      "uncertainty_range": 2.4,
      "evidence_signal": "Small open model",
      "pricing_input_per_m": 0.1,
      "pricing_output_per_m": 0.3,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #47: Small open model — Top drivers: Openness 90th percentile + Efficiency 84th percentile — Small but efficient — Open.",
      "reasoning_score": 76,
      "agent_code_score": 70,
      "hard_capability_score": 67,
      "efficiency_score": 84,
      "openness_score": 90,
      "freshness_score": 72,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://huggingface.co/microsoft",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 48,
      "model_id": "llama-4-scout",
      "name": "Llama 4 Scout",
      "developer": "Meta",
      "license_type": "open_weights",
      "aki_score_v2_2": 62.5,
      "confidence_pct": 85,
      "uncertainty_range": 2.2,
      "evidence_signal": "Previous Llama scout",
      "pricing_input_per_m": 0.8,
      "pricing_output_per_m": 3,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #48: Previous Llama scout — Top drivers: Agentic 76th percentile + Openness 89th percentile — Previous-gen.",
      "reasoning_score": 74,
      "agent_code_score": 76,
      "hard_capability_score": 66,
      "efficiency_score": 81,
      "openness_score": 89,
      "freshness_score": 71,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://ai.meta.com",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 49,
      "model_id": "gemma-3-27b",
      "name": "Gemma 3 27B",
      "developer": "Google",
      "license_type": "open_weights",
      "aki_score_v2_2": 62,
      "confidence_pct": 83,
      "uncertainty_range": 2.5,
      "evidence_signal": "Small open Google",
      "pricing_input_per_m": 0.15,
      "pricing_output_per_m": 0.4,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #49: Small open Google — Top drivers: Openness 91st percentile + Efficiency 82nd percentile — Small open-weight — Good value.",
      "reasoning_score": 73,
      "agent_code_score": 70,
      "hard_capability_score": 65,
      "efficiency_score": 82,
      "openness_score": 91,
      "freshness_score": 70,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://ai.google.dev",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    },
    {
      "rank": 50,
      "model_id": "minimax-m2",
      "name": "MiniMax M2",
      "developer": "MiniMax",
      "license_type": "open_weights",
      "aki_score_v2_2": 61.5,
      "confidence_pct": 79,
      "uncertainty_range": 3.1,
      "evidence_signal": "Previous MiniMax",
      "pricing_input_per_m": 0.2,
      "pricing_output_per_m": 0.8,
      "change_from_v2_1": "—",
      "why_ranked_here": "Why #50: Previous MiniMax — Top drivers: Openness 87th percentile + Reasoning 71st percentile — Growing evidence — Previous-gen — 15 slots reserved for next-gen entries.",
      "reasoning_score": 71,
      "agent_code_score": 68,
      "hard_capability_score": 64,
      "efficiency_score": 80,
      "openness_score": 87,
      "freshness_score": 69,
      "velocity_bonus": 0,
      "context_window": "128k",
      "official_url": "https://minimax.io",
      "last_verified_utc": "2026-10-12T07:00:00Z"
    }
  ]
}