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fb552e00201dae79647e709843781ea34d01630c
APAW/agent-evolution/data/model-benchmarks.json
¨NW¨ fb552e0020 feat: v3 optimal model assignments + fitness gate 
- Update 30 agents to v3 heatmap maximum-score models:
  * go-dev: qwen3-coder -> deepseek-v4-pro-max (85->88 +3)
  * planner: nemotron -> deepseek-v4-pro-max (80->88 +8)
  * perf-engineer: nemotron -> deepseek-v4-pro-max (78->84 +6)
  * reflector: nemotron -> deepseek-v4-pro-max (78->84 +6)
  * security: nemotron -> deepseek-v4-pro-max (76->80 +4)
  * memory-manager: nemotron -> qwen3.6-plus (86->87 +1)
  * frontend: kimi-k2.5 -> minimax-m2.5 (92)
  * the-fixer: minimax-m2.5 -> kimi-k2.6 (88->90 +2)
  * browser-auto: kimi-k2.6 -> qwen3-coder (86->87 +1)
  * prompt-opt: glm-5.1 -> qwen3.6-plus (82->83 +1)
  * backend: deepseek-v3.2 -> qwen3-coder (91)
  * capability-analyst: nemotron -> glm-5.1 (85)
  * release-man: devstral-2 -> glm-5.1 (82)
  * evaluator: nemotron -> glm-5.1 (86)
  * workflow-arch: gpt-oss -> glm-5.1 (84)

- Add Model Evolution Guard:
  * fitness-gate.cjs: rejects downgrades >3 points or <75 score
  * Normalized model ID lookup (: vs -)
  * Diff report before any file modifications
- Update sync-benchmarks-from-yaml.cjs with fitness gate
- Sync kilo-meta.json, kilo.jsonc, .md agent files
- Rebuild research-dashboard.html (104KB, 30 agents, 11 models)

Total improvement: +105 points across 11 agents
Source: v3.html heatmap IF-adjusted composite scores
2026-04-30 08:42:10 +01:00

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{
"version": "1.0.0",
"generated": "2026-04-30T07:00:00Z",
"source": "capability-index.yaml v3 optimal",
"total_agents": 30,
"total_models_tracked": 11,
"providers": [
"ollama",
"ollama-cloud",
"openrouter",
"groq"
],
"models": [
{
"id": "qwen3-coder-480b",
"name": "Qwen3-Coder 480B",
"organization": "Qwen",
"parameters": "480B/35B active",
"context_window": "256K\u21921M",
"swe_bench": 66.5,
"if_score": 88,
"categories": [
"coding",
"agent"
],
"description": "SOTA open-source \u043a\u043e\u0434\u0438\u043d\u0433. \u0421\u0440\u0430\u0432\u043d\u0438\u043c \u0441 Claude Sonnet 4.",
"tags": [
"coding",
"agent",
"tools"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "minimax-m2.5",
"name": "MiniMax M2.5",
"organization": "MiniMax",
"parameters": "MoE undisclosed",
"context_window": "128K",
"swe_bench": 80.2,
"if_score": 82,
"categories": [
"coding",
"agent"
],
"description": "\u041b\u0438\u0434\u0435\u0440 SWE-bench 80.2%. \u041f\u043e\u043b\u043d\u044b\u0439 lifecycle \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438.",
"tags": [
"coding",
"agent"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "minimax-m2.7",
"name": "MiniMax M2.7",
"organization": "MiniMax",
"parameters": "~10B active",
"context_window": "128K",
"swe_bench": 78,
"if_score": 80,
"categories": [
"coding",
"agent",
"efficient"
],
"description": "\u0421\u0430\u043c\u043e\u043e\u0431\u0443\u0447\u0430\u0435\u043c\u0430\u044f. 56.2% SWE-Pro. 100 TPS. $0.30/M.",
"tags": [
"coding",
"agent",
"self-evolving"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "deepseek-v4-pro-max",
"name": "DeepSeek V4-Pro",
"organization": "DeepSeek",
"parameters": "1.6T/49B active MoE",
"context_window": "1M",
"swe_bench": 80.6,
"if_score": 89,
"categories": [
"coding",
"agent",
"reasoning"
],
"description": "SWE-V 80.6, LiveCodeBench 93.5(#1!), Terminal-Bench 67.9, Codeforces 3206, 1M ctx, 27% FLOPs vs V3.2. MIT.",
"tags": [
"coding",
"agent",
"thinking",
"tools"
],
"openrouter": false,
"provider": "ollama-cloud"
},
{
"id": "deepseek-v4-flash",
"name": "DeepSeek V4-Pro",
"organization": "DeepSeek",
"parameters": "284B/13B active MoE",
"context_window": "1M",
"swe_bench": 79,
"if_score": 86,
"categories": [
"coding",
"efficient",
"agent"
],
"description": "SWE-V ~79%, Flash Max = Pro \u0443\u0440\u043e\u0432\u0435\u043d\u044c reasoning. 13B active = \u0443\u043b\u044c\u0442\u0440\u0430\u0431\u044b\u0441\u0442\u0440\u044b\u0439. 1M ctx. FP4+FP8. MIT.",
"tags": [
"coding",
"efficient",
"agent",
"thinking"
],
"openrouter": false,
"provider": "ollama-cloud"
},
{
"id": "kimi-k2-6",
"name": "Kimi K2.6",
"organization": "Moonshot AI",
"parameters": "1T/32B active MoE",
"context_window": "256K",
"swe_bench": 80.2,
"if_score": 91,
"categories": [
"coding",
"agent",
"multimodal"
],
"description": "SWE-Pro 58.6(#1!), SWE-V 80.2, Terminal-Bench 66.7, HLE 54.0(#1!), BrowseComp 83.2. 13h autonomous. 300 sub-agent swarm. Modified MIT.",
"tags": [
"coding",
"agent",
"swarm",
"vision",
"thinking",
"tools"
],
"openrouter": false,
"provider": "ollama-cloud"
},
{
"id": "nemotron-3-super",
"name": "Nemotron 3 Super",
"organization": "NVIDIA",
"parameters": "120B/12B active",
"context_window": "1M",
"swe_bench": 60.5,
"if_score": 78,
"categories": [
"agent",
"reasoning",
"efficient"
],
"description": "SWE-bench 60.5%. RULER@1M 91.75%! \u041d\u043e IF \u043d\u0438\u0436\u0435 \u2014 Mamba-layers \u0438\u043d\u043e\u0433\u0434\u0430 \u00ab\u0442\u0435\u0440\u044f\u044e\u0442\u00bb \u0438\u043d\u0441\u0442\u0440\u0443\u043a\u0446\u0438\u0438 \u0432 \u0434\u043b\u0438\u043d\u043d\u044b\u0445 \u043f\u0440\u043e\u043c\u043f\u0442\u0430\u0445.",
"tags": [
"agent",
"1M-ctx",
"thinking"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "glm-5.1",
"name": "GLM-5",
"organization": "Z.ai",
"parameters": "744B/40B active",
"context_window": "128K",
"swe_bench": null,
"if_score": 90,
"categories": [
"reasoning",
"agent"
],
"description": "\u041c\u043e\u0449\u043d\u044b\u0439 reasoning. Arena ELO 1451. \u041e\u0442\u043b\u0438\u0447\u043d\u044b\u0439 instruction following (IFEval ~90+).",
"tags": [
"reasoning",
"agent"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "deepseek-v4",
"name": "DeepSeek V4-Pro",
"organization": "DeepSeek",
"parameters": "Large MoE",
"context_window": "128K",
"swe_bench": null,
"if_score": 75,
"categories": [
"reasoning"
],
"description": "\u0425\u043e\u0440\u043e\u0448\u0438\u0439 reasoning, \u043d\u043e IF \u043d\u0435\u0441\u0442\u0430\u0431\u0438\u043b\u0435\u043d \u2014 \u0438\u043d\u043e\u0433\u0434\u0430 \u0438\u0433\u043d\u043e\u0440\u0438\u0440\u0443\u0435\u0442 \u0444\u043e\u0440\u043c\u0430\u0442 \u0432\u044b\u0432\u043e\u0434\u0430.",
"tags": [
"reasoning"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "qwen3-5-122b",
"name": "Qwen 3.5 122B",
"organization": "Qwen",
"parameters": "122B/10B active",
"context_window": "128K",
"swe_bench": null,
"if_score": 92,
"categories": [
"reasoning",
"efficient"
],
"description": "IFEval 92.6%! \u041b\u0443\u0447\u0448\u0438\u0439 IF \u0441\u0440\u0435\u0434\u0438 open-source. Multimodal. Thinking.",
"tags": [
"vision",
"thinking",
"tools"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "qwen3-coder-next",
"name": "Qwen3-Coder-Next",
"organization": "Qwen",
"parameters": "80B/3B active",
"context_window": "128K",
"swe_bench": 70,
"if_score": 84,
"categories": [
"coding",
"efficient"
],
"description": "70% SWE-bench \u0441 3B active! \u0425\u043e\u0440\u043e\u0448\u0438\u0439 IF \u0434\u043b\u044f \u043a\u043e\u0434\u0438\u043d\u0433\u0430.",
"tags": [
"coding",
"efficient",
"tools"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "cogito-2-1-671b",
"name": "Cogito 2.1 671B",
"organization": "Cognitive",
"parameters": "671B MoE",
"context_window": "128K",
"swe_bench": null,
"if_score": 76,
"categories": [
"reasoning"
],
"description": "MIT \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u044f. 671B total. IF \u043d\u0435\u043f\u043b\u043e\u0445\u043e\u0439, \u043d\u043e \u0443\u0441\u0442\u0443\u043f\u0430\u0435\u0442 GLM/Qwen.",
"tags": [
"reasoning"
],
"openrouter": false,
"provider": "ollama"
},
{
"id": "qwen3-6-plus",
"name": "Qwen 3.6 Plus",
"organization": "Qwen",
"parameters": "Hybrid MoE",
"context_window": "1M",
"swe_bench": 78.8,
"if_score": 91,
"categories": [
"coding",
"agent",
"reasoning"
],
"description": "FREE \u043d\u0430 OpenRouter! 1M \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442. Always-on CoT. \u041f\u0440\u0435\u0432\u043e\u0441\u0445\u043e\u0434\u043d\u044b\u0439 IF \u2014 \u043d\u0430\u0441\u043b\u0435\u0434\u043d\u0438\u043a Qwen 3.5 (92.6%).",
"tags": [
"coding",
"agent",
"1M-ctx",
"free"
],
"openrouter": true,
"provider": "openrouter"
},
{
"id": "step-3-5-flash",
"name": "Step 3.5 Flash",
"organization": "StepFun",
"parameters": "MoE",
"context_window": "128K",
"swe_bench": null,
"if_score": 79,
"categories": [
"efficient"
],
"description": "\u0411\u0435\u0441\u043f\u043b\u0430\u0442\u043d\u0430 \u043d\u0430 OpenRouter. IF \u0441\u0440\u0435\u0434\u043d\u0438\u0439.",
"tags": [
"efficient",
"free"
],
"openrouter": true,
"provider": "openrouter"
},
{
"id": "deepseek-r1",
"name": "DeepSeek R1",
"organization": "DeepSeek",
"parameters": "671B MoE",
"context_window": "128K",
"swe_bench": null,
"if_score": 73,
"categories": [
"reasoning"
],
"description": "\u041c\u043e\u0449\u043d\u044b\u0435 reasoning-\u0446\u0435\u043f\u043e\u0447\u043a\u0438. \u041d\u043e IF \u0441\u043b\u0430\u0431\u044b\u0439 \u2014 \u0447\u0430\u0441\u0442\u043e \u0433\u0435\u043d\u0435\u0440\u0438\u0440\u0443\u0435\u0442 \u043b\u0438\u0448\u043d\u0438\u0439 reasoning \u0432\u043c\u0435\u0441\u0442\u043e \u043e\u0442\u0432\u0435\u0442\u0430.",
"tags": [
"reasoning",
"thinking",
"free"
],
"openrouter": true,
"provider": "openrouter"
}
],
"groq_models": [
{
"id": "openai/gpt-oss-20b",
"rpm": 30,
"rpd": "1K",
"tpm": "8K",
"tpd": "200K",
"speed": "1200+",
"use_case": "\u0423\u043b\u044c\u0442\u0440\u0430-\u0431\u044b\u0441\u0442\u0440\u044b\u0439 fallback \u0434\u043b\u044f \u043b\u0451\u0433\u043a\u0438\u0445 \u0440\u043e\u043b\u0435\u0439 (markdown-validator)."
},
{
"id": "llama-3.1-8b-instant",
"rpm": 30,
"rpd": "14.4K",
"tpm": "6K",
"tpd": "500K",
"speed": "~800",
"use_case": "14.4K RPD! \u0421\u0430\u043c\u044b\u0439 \u0432\u044b\u0441\u043e\u043a\u0438\u0439 \u043b\u0438\u043c\u0438\u0442. \u0414\u043b\u044f health-check / ping \u0440\u043e\u043b\u0435\u0439."
},
{
"id": "groq/compound",
"rpm": 30,
"rpd": "250",
"tpm": "70K",
"tpd": "\u2014",
"speed": "varies",
"use_case": "\u041c\u0443\u043b\u044c\u0442\u0438\u043c\u043e\u0434\u0435\u043b\u044c\u043d\u0430\u044f \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u044f. \u0414\u043b\u044f research-\u0437\u0430\u0434\u0430\u0447."
},
{
"id": "groq/compound-mini",
"rpm": 30,
"rpd": "250",
"tpm": "70K",
"tpd": "\u2014",
"speed": "varies",
"use_case": "\u041b\u0451\u0433\u043a\u0430\u044f \u0432\u0435\u0440\u0441\u0438\u044f compound."
},
{
"id": "llama-prompt-guard-2",
"rpm": 30,
"rpd": "14.4K",
"tpm": "15K",
"tpd": "500K",
"speed": "~1K",
"use_case": "Security: \u0432\u0445\u043e\u0434\u043d\u043e\u0439 \u0444\u0438\u043b\u044c\u0442\u0440 \u0434\u043b\u044f security-auditor (14.4K RPD!)."
}
],
"agent_model_scores": [
{
"agent": "lead-developer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "H",
"scores": {
"qwen3-coder-480b": 92,
"minimax-m2.5": 86,
"minimax-m2.7": 82,
"nemotron-3-super": 70,
"glm-5.1": 68,
"deepseek-v4-pro-max": 88,
"qwen3-5-122b": 66,
"qwen3-coder-next": 80,
"qwen3-6-plus": 88,
"kimi-k2-6": 90
}
},
{
"agent": "frontend-developer",
"current_model_index": 1,
"current_model_id": "minimax-m2.5",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 86,
"minimax-m2.5": 92,
"minimax-m2.7": 88,
"nemotron-3-super": 62,
"glm-5.1": 56,
"deepseek-v4-pro-max": 82,
"qwen3-5-122b": 60,
"qwen3-coder-next": 76,
"qwen3-6-plus": 88,
"kimi-k2-6": 86
}
},
{
"agent": "php-developer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "H",
"scores": {
"qwen3-coder-480b": 87,
"minimax-m2.5": 76,
"minimax-m2.7": 72,
"nemotron-3-super": 64,
"glm-5.1": 56,
"deepseek-v4-pro-max": 74,
"qwen3-5-122b": 60,
"qwen3-coder-next": 76,
"qwen3-6-plus": 84,
"kimi-k2-6": 86
}
},
{
"agent": "python-developer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "H",
"scores": {
"qwen3-coder-480b": 90,
"minimax-m2.5": 82,
"minimax-m2.7": 78,
"nemotron-3-super": 66,
"glm-5.1": 60,
"deepseek-v4-pro-max": 78,
"qwen3-5-122b": 64,
"qwen3-coder-next": 78,
"qwen3-6-plus": 88,
"kimi-k2-6": 88
}
},
{
"agent": "backend-developer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 91,
"minimax-m2.5": 84,
"minimax-m2.7": 80,
"nemotron-3-super": 68,
"glm-5.1": 63,
"deepseek-v4-pro-max": 86,
"qwen3-5-122b": 62,
"qwen3-coder-next": 78,
"qwen3-6-plus": 87,
"kimi-k2-6": 90
}
},
{
"agent": "go-developer",
"current_model_index": 3,
"current_model_id": "deepseek-v4-pro-max",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 85,
"minimax-m2.5": 78,
"minimax-m2.7": 74,
"nemotron-3-super": 66,
"glm-5.1": 58,
"deepseek-v4-pro-max": 88,
"qwen3-5-122b": 58,
"qwen3-coder-next": 74,
"qwen3-6-plus": 82,
"kimi-k2-6": 86
}
},
{
"agent": "flutter-developer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 86,
"minimax-m2.5": 70,
"minimax-m2.7": 66,
"nemotron-3-super": 60,
"glm-5.1": 53,
"deepseek-v4-pro-max": 78,
"qwen3-5-122b": 58,
"qwen3-coder-next": 74,
"qwen3-6-plus": 82,
"kimi-k2-6": 84
}
},
{
"agent": "devops-engineer",
"current_model_index": -1,
"current_model_id": "kimi-k2.6",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 66,
"minimax-m2.5": 53,
"minimax-m2.7": 48,
"nemotron-3-super": 78,
"glm-5.1": 75,
"deepseek-v4-pro-max": 86,
"qwen3-5-122b": 70,
"qwen3-coder-next": 54,
"qwen3-6-plus": 76,
"kimi-k2-6": 88
}
},
{
"agent": "sdet-engineer",
"current_model_index": 0,
"current_model_id": "qwen3-coder-480b",
"reasoning_effort": "H",
"scores": {
"qwen3-coder-480b": 88,
"minimax-m2.5": 84,
"minimax-m2.7": 80,
"nemotron-3-super": 70,
"glm-5.1": 63,
"deepseek-v4-pro-max": 84,
"qwen3-5-122b": 64,
"qwen3-coder-next": 78,
"qwen3-6-plus": 84,
"kimi-k2-6": 87
}
},
{
"agent": "code-skeptic",
"current_model_index": 1,
"current_model_id": "minimax-m2.5",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 82,
"minimax-m2.5": 85,
"minimax-m2.7": 80,
"nemotron-3-super": 73,
"glm-5.1": 72,
"deepseek-v4-pro-max": 82,
"qwen3-5-122b": 70,
"qwen3-coder-next": 72,
"qwen3-6-plus": 80,
"kimi-k2-6": 82
}
},
{
"agent": "security-auditor",
"current_model_index": 3,
"current_model_id": "deepseek-v4-pro-max",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 76,
"minimax-m2.5": 74,
"minimax-m2.7": 68,
"nemotron-3-super": 76,
"glm-5.1": 68,
"deepseek-v4-pro-max": 80,
"qwen3-5-122b": 72,
"qwen3-coder-next": 64,
"qwen3-6-plus": 75,
"kimi-k2-6": 80
}
},
{
"agent": "performance-engineer",
"current_model_index": 3,
"current_model_id": "deepseek-v4-pro-max",
"reasoning_effort": "M",
"scores": {
"qwen3-coder-480b": 78,
"minimax-m2.5": 75,
"minimax-m2.7": 70,
"nemotron-3-super": 78,
"glm-5.1": 74,
"deepseek-v4-pro-max": 84,
"qwen3-5-122b": 70,
"qwen3-coder-next": 67,
"qwen3-6-plus": 76,
"kimi-k2-6": 82
}
},
{
"agent": "the-fixer",
"current_model_index": -1,
"current_model_id": "kimi-k2.6",
"reasoning_effort": "M",
"scores": {
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"agent": "devops \u2192 K2.6",
"from_model": "deepseek-v3.2",
"from_provider": "",
"to_model": "kimi-k2.6:cloud \u2705",
"to_provider": "Ollama Cloud",
"impact": "low",
"quality_change": "+35%",
"speed_change": "=",
"context_change": "256K",
"provider_change": "",
"rationale": "APPLIED."
},
{
"agent": "orchestrator",
"from_model": "glm-5.1.1 (\u260590)",
"from_provider": "Ollama",
"to_model": "K2.6 (\u260592) RE:Medium",
"to_provider": "Ollama Cloud",
"impact": "medium",
"quality_change": "+2%",
"speed_change": "~1x",
"context_change": "200K\u2192256K",
"provider_change": "Ollama Cloud",
"rationale": "K2.6=92\u2605 \u0432\u0441\u0451 \u0435\u0449\u0451 \u043b\u0443\u0447\u0448\u0438\u0439 \u0434\u043b\u044f orchestration. V4-Pro=86 \u0441\u043b\u0430\u0431\u0435\u0435. 300 sub-agent swarm."
},
{
"agent": "the-fixer",
"from_model": "minimax-m2.5 (\u260588)",
"from_provider": "Ollama",
"to_model": "V4-Pro (\u260588) / K2.6 (\u260590)",
"to_provider": "Ollama Cloud",
"impact": "medium",
"quality_change": "+2%",
"speed_change": "~1x",
"context_change": "128K\u21921M/256K",
"provider_change": "Ollama Cloud",
"rationale": "K2.6=90(\u043b\u0443\u0447\u0448\u0438\u0439), V4-Pro=88=M2.5. M2.5 SWE-bench 80.2% \u0441\u0442\u0430\u0431\u0438\u043b\u044c\u043d\u0435\u0435. \u041d\u0435 \u0441\u0440\u043e\u0447\u043d\u043e."
},
{
"agent": "Qwen3-Coder (7 coding)",
"from_model": "qwen3-coder",
"from_provider": "Ollama",
"to_model": "\u2705",
"to_provider": "",
"impact": "low",
"quality_change": "=0%",
"speed_change": "=",
"context_change": "256K",
"provider_change": "Ollama",
"rationale": "lead=92\u2605, backend=91\u2605, python=90\u2605."
},
{
"agent": "GLM-5.1 (12 agents)",
"from_model": "glm-5.1.1",
"from_provider": "Ollama",
"to_model": "\u2705",
"to_provider": "",
"impact": "low",
"quality_change": "=0%",
"speed_change": "=",
"context_change": "200K",
"provider_change": "",
"rationale": "orchestrator=90, system-analyst=90. SWE-Pro #1."
},
{
"agent": "Kimi K2.6 (3 agents)",
"from_model": "kimi-k2.6",
"from_provider": "Ollama Cloud",
"to_model": "\u2705",
"to_provider": "",
"impact": "low",
"quality_change": "=0%",
"speed_change": "=",
"context_change": "256K",
"provider_change": "",
"rationale": "devops=88\u2605, browser=86, agent-arch=86."
}
],
"impact_data": [
{
"category": "debug GLM5.1\u2192V4-Pro/K2.6",
"before": 88,
"after": 90,
"delta": 2,
"notes": "LiveCodeBench 93.5, Terminal 67.9"
},
{
"category": "planner Nem\u2192V4-Pro Max",
"before": 80,
"after": 88,
"delta": 8,
"notes": "\u260588! GPQA 90.1, 1M ctx"
},
{
"category": "go-dev Coder\u2192V4-Pro Max",
"before": 85,
"after": 88,
"delta": 3,
"notes": "\u260588! Go/Rust specialist, 1M ctx"
},
{
"category": "history-miner \u2192V4-Pro",
"before": 85,
"after": 86,
"delta": 1,
"notes": "MRCR 83.5, long-context"
},
{
"category": "orchestrator \u2192K2.6 (next)",
"before": 90,
"after": 92,
"delta": 2,
"notes": "300 sub-agent swarm"
},
{
"category": "frontend \u2192 M2.5 \u2705",
"before": 90,
"after": 92,
"delta": 2,
"notes": "Spec-writing, UI architect"
},
{
"category": "devops \u2192 K2.6 \u2705",
"before": 65,
"after": 88,
"delta": 23,
"notes": "IF:65\u219291! Terminal 66.7"
},
{
"category": "Qwen3-Coder (7) \u2705",
"before": 90,
"after": 90,
"delta": 0,
"notes": "SOTA coding"
},
{
"category": "GLM-5.1 (12) \u2705",
"before": 87,
"after": 87,
"delta": 0,
"notes": "SWE-Pro #1"
},
{
"category": "Nemotron Super (6) \u2705",
"before": 82,
"after": 82,
"delta": 0,
"notes": "1M ctx, RULER 91.75%"
}
],
"benchmark_comparison": {
"benchmarks": [
{
"name": "SWE-V",
"full_name": "SWE-Bench Verified",
"description": "GitHub issue resolution (500 tasks)",
"roles": "lead-dev, backend, fixer"
},
{
"name": "SWE-P",
"full_name": "SWE-Bench Pro",
"description": "Multi-lang, decontaminated (1865 tasks)",
"roles": "all coding agents"
},
{
"name": "T-Bench",
"full_name": "Terminal-Bench 2.0",
"description": "CLI/shell multi-step tasks",
"roles": "devops, planner, orchestrator"
},
{
"name": "LCB",
"full_name": "LiveCodeBench",
"description": "Code gen from specs (held-out)",
"roles": "sdet, go-dev, python-dev"
},
{
"name": "GPQA",
"full_name": "GPQA Diamond",
"description": "PhD-level reasoning",
"roles": "system-analyst, planner"
},
{
"name": "BComp",
"full_name": "BrowseComp",
"description": "Web research & synthesis",
"roles": "browser-auto, capability-analyst"
},
{
"name": "HLE",
"full_name": "Humanity Last Exam",
"description": "Frontier knowledge (with tools)",
"roles": "agent-architect, evaluator"
},
{
"name": "Ctx",
"full_name": "Context Window",
"description": "Max tokens in one pass",
"roles": "history-miner, memory-mgr"
},
{
"name": "$/M",
"full_name": "Cost per 1M input",
"description": "API pricing",
"roles": "all agents (ROI)"
}
],
"closed_source_models": [
{
"name": "Claude Opus 4.7",
"organization": "Anthropic",
"scores": [
87.6,
64.3,
69.4,
null,
94.2,
79.3,
53,
"1M",
"$5"
],
"color": "#c084fc",
"note": "#1 \u0430\u043f\u0440\u0435\u043b\u044c 2026"
},
{
"name": "GPT-5.5",
"organization": "OpenAI",
"scores": [
null,
58.6,
82.7,
null,
null,
83.4,
57.2,
"1M",
"$5"
],
"color": "#ff6b81",
"note": "\u041d\u043e\u0432\u0435\u0439\u0448\u0438\u0439, Terminal #1"
},
{
"name": "GPT-5.4",
"organization": "OpenAI",
"scores": [
78.2,
59.1,
75.1,
null,
94.4,
82.7,
58.7,
"200K",
"$2.50"
],
"color": "#ff6b81",
"note": "Reasoning, math"
},
{
"name": "Gemini 3.1 Pro",
"organization": "Google",
"scores": [
80.6,
46.1,
68.5,
null,
94.3,
85.9,
51.4,
"2M",
"$2"
],
"color": "#facc15",
"note": "ARC-AGI 77.1%, \u0434\u0435\u0448\u0451\u0432\u044b\u0439"
},
{
"name": "Claude Sonnet 4.6",
"organization": "Anthropic",
"scores": [
79.6,
null,
null,
null,
null,
null,
null,
"200K",
"$3"
],
"color": "#c084fc",
"note": "5\u00d7 \u0434\u0435\u0448\u0435\u0432\u043b\u0435 Opus"
},
{
"name": "GPT-5.3-Codex",
"organization": "OpenAI",
"scores": [
85,
57,
77.3,
null,
null,
null,
null,
"200K",
"$6"
],
"color": "#ff6b81",
"note": "Coding specialist"
}
],
"apaw_models": [
{
"name": "Kimi K2.6",
"organization": "APAW",
"scores": [
80.2,
58.6,
66.7,
87.2,
null,
83.2,
54,
"256K",
"$0.95"
],
"color": "#00ff94",
"note": "devops, browser, architect (3)"
},
{
"name": "GLM-5.1",
"organization": "APAW",
"scores": [
null,
58.4,
63.5,
null,
86.2,
68.7,
null,
"200K",
"~$0.50"
],
"color": "#00ff94",
"note": "12 agents! orchestrator, eval..."
},
{
"name": "V4-Pro Max",
"organization": "APAW",
"scores": [
80.6,
55.4,
67.9,
93.5,
90.1,
83.4,
48.2,
"1M",
"$0.42"
],
"color": "#00d4ff",
"note": "planner, go-dev (\u0440\u0435\u043a.)"
},
{
"name": "Qwen3-Coder 480B",
"organization": "APAW",
"scores": [
66.5,
null,
null,
null,
null,
null,
null,
"256K",
"~$0.50"
],
"color": "#00ff94",
"note": "7 coding agents"
},
{
"name": "MiniMax M2.5",
"organization": "APAW",
"scores": [
80.2,
51.3,
null,
null,
null,
76.3,
null,
"204K",
"$0.15"
],
"color": "#00ff94",
"note": "frontend, skeptic, fixer (3)"
},
{
"name": "Nemotron Super",
"organization": "APAW",
"scores": [
60.5,
null,
null,
null,
null,
null,
null,
"1M",
"~$0.40"
],
"color": "#00ff94",
"note": "6 agents (memory, history)"
}
]
}
}
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