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AI model benchmarks

Compare independent benchmark scores and API prices to find the right models for your work.

Artificial Analysis via OpenRouter100 modelsSnapshot

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Model comparison

Top 10 by agentic index

Highest index score

57.2
Claude Fable 5.1 (Xhigh, Default Fallback)

Lowest input price

$0.15
GLM-5.3-Flash

Lowest output price

$0.50
GLM-5.3-Flash

Agentic index

Measured capability for the top models.

Higher is stronger on this index.

Input price

The same models, priced per 1M input tokens.

USD per million tokens. Lower costs less.

Output price

The same models, priced per 1M output tokens.

USD per million tokens. Lower costs less.

Summary cards and bars compare this top 10 only. Index scores are not percentages.

Cost efficiency

65 model configurations

Index score vs. input price

Each point is a model configuration. Toward the upper left means a higher score for a lower input price.

  • Anthropic
  • Qwen
  • Meta
  • z-ai
  • xAI
  • OpenAI
  • DeepSeek
  • Google
  • minimax
  • moonshotai
  • inclusionai
  • tencent
  • thinkingmachines
  • xiaomi
  • nvidia
  • Mistral
  • ibm-granite
  • cohere
  • Input-price frontier

1 free model is outside this logarithmic scale. Switch to Linear to include it.

The dashed frontier connects models with a higher score than every cheaper model, including free models in that comparison. It considers input pricing only; output prices and your workload also affect total cost. Equal spacing on this logarithmic price scale represents equal price ratios.

35 models are omitted from the scatter because this index score or input price is not reported.

View chart data
All filtered model configurations with a reported agentic index. Prices in USD per million tokens.
Model configurationAgentic indexInput priceOutput price
Claude Fable 5.1 (Xhigh, Default Fallback)57.2$5.00$25.00
Claude Opus 5 (Max)56.5$5.50$27.50
Qwen3.8 Max (0902)56$1.15$3.45
Muse Spark 1.3 (Max)55.5$1.25$4.25
GLM-5.3 (Max)53.1$0.527$1.075
Grok 4.6 (Xhigh)52.5$1.60$4.80
GPT-6 Astra (Max)51$10.00$50.00
GLM-5.3-Flash50.9$0.15$0.50
Claude Fable 5 (Max, Opus 4.8 Fallback)50.7$10.00$50.00
Qwen3.8 2.4T A95B50.1$2.00$6.00
Qwen3.8 Max49.9Not reportedNot reported
DeepSeek V4 Flash Vision (Max)47.5$0.44$1.32
GPT-5.6 Sol (Xhigh)47.4$4.00$20.00
Qwen3.8 27B (Xhigh)45.8$0.16$2.00
Claude Sonnet 5 (Max)43.6$2.20$11.00
Muse Spark 1.2 (Xhigh)43.2$1.25$4.25
GPT-5.6 Terra (Max)43.2$4.00$24.00
GPT-5.6 Luna (Max)42.1$0.20$1.20
Claude Opus 4.8 (Max)41.9$10.00$50.00
DeepSeek V4 Pro 0813 (Max)41.3$1.98$5.94
Grok 4.5 (High)41.2$4.00$12.00
DeepSeek V4 Flash 0731 (Max)41$0.048$0.144
Gemini 3.8 Flash (High)40.2$0.825$4.125
Claude Opus 4.7 (Max)38.6$5.00$25.00
GLM-5.2 (Max)38.4$0.527$1.075
GPT-5.5 (Xhigh)36.4$2.50$15.00
Gemini 3.7 Flash (High)35.2$0.825$4.125
Claude Sonnet 4.6 (Max)31.8$3.00$15.00
MiniMax-M329.5$0.224$0.88
Kimi K3 (Low)29.3$2.30$14.00
Gemini 3.6 Flash (High)29$1.35$6.75
Ling-3.0-flash-VL28.7$0.06$0.18
Ling-3.0-flash-Fin27.9Not reportedNot reported
Gemini 3.5 Flash (High)26$2.70$16.20
Muse Spark 1.1 (Xhigh)25.8$1.25$4.25
Hy324.1$0.18$0.60
GLM-5.1 (Reasoning)23.9$1.33$4.18
Nex-N2-Pro (Based on Qwen3.5-397B-A17B)23.7Not reportedNot reported
Inkling Small23.5$0.36$0.96
Qwen3.7 Max22.5$2.00$6.00
Inkling (Xhigh)22.5$1.00$4.05
DeepSeek V4 Flash 0420 (Max)22.2$0.105$0.21
MiMo-V2.5-Pro (Reasoning)21.3$0.435$0.87
Kimi K2.7 Code21$0.7125$3.00
Kimi K2.6 (Reasoning)20.5$0.65$3.41
Nemotron 3 Ultra 550B A55B (Reasoning)20.1$0.40$1.76
Ling 3.0 Flash19.3$0.021$0.063
Qwen3.6 27B (Reasoning)18.5$0.20$3.00
GPT-5.4 mini (Xhigh)17.9$1.50$9.00
Qwen3.7 Plus17.5$0.23$0.92
GPT-5.4 nano (Xhigh)16$0.10$0.625
Claude 4.5 Sonnet (Reasoning)15.8$3.00$15.00
MiMo-V2.515.8$0.40$2.00
MiniMax-M2.715.3$0.21$0.84
Gemini 3.5 Flash-Lite14.3$0.54$4.50
Muse Glimmer (High)8.5$0.24$0.96
Qwen3.5 397B A17B (Reasoning)8.3$0.60$3.60
Gemini 3.1 Pro Preview8.2$3.60$21.60
Claude 4.5 Haiku (Reasoning)8$1.10$5.50
Mistral Medium 3.57$0.75$3.75
Gemma 4 31B (Reasoning)4.2$0.34$0.10
gpt-oss-120b (High)3.7$0.15$0.75
Nemotron 3.5 Lightning3.5$0.05$0.20
Gemini 3.1 Flash-Lite1.6$0.45$2.70
Granite 4.2 8B1.3$0.06$0.25
North Mini Code1.1$0.00$0.00
Command A+1$0.30$1.50
Mistral Small 4 (Reasoning)0.8$0.165$0.66

Leaderboard

Explore benchmark scores and API prices. Shortlist up to three models to compare.

Top 10 of 100 models

Select 2–3 to compare

Artificial Analysis agents index and OpenRouter token prices, ordered by highest score. Scores are not percentages.
Position#ModelAgents indexAPI pricing / 1M tokensAdd to comparison
1Claude Fable 5.1 (Xhigh, Default Fallback)Agents 57.2
In $5.00 / Out $25.00 / 1M tokens
2Claude Opus 5 (Max)Agents 56.5
In $5.50 / Out $27.50 / 1M tokens
3Qwen3.8 Max (0902)Agents 56.0
In $1.15 / Out $3.45 / 1M tokens
4Muse Spark 1.3 (Max)Agents 55.5
In $1.25 / Out $4.25 / 1M tokens
5GLM-5.3 (Max)Agents 53.1
In $0.53 / Out $1.08 / 1M tokens
6Grok 4.6 (Xhigh)Agents 52.5
In $1.60 / Out $4.80 / 1M tokens
7GPT-6 Astra (Max)Agents 51.0
In $10.00 / Out $50.00 / 1M tokens
8GLM-5.3-FlashAgents 50.9
In $0.15 / Out $0.50 / 1M tokens
9Claude Fable 5 (Max, Opus 4.8 Fallback)Agents 50.7
In $10.00 / Out $50.00 / 1M tokens
10Qwen3.8 2.4T A95BAgents 50.1
In $2.00 / Out $6.00 / 1M tokens

Prices in USD. Missing values are “Not reported.” Configuration labels are preserved from the source.

Methodology & sources

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).

Licensed under CC BY 4.0. View the license. Artificial Analysis source.

How to read these results

Each view uses one Artificial Analysis index. Intelligence, coding and agentic scores measure different evaluations. They are not percentages and are not combined with popularity or individual test accuracies. Configuration labels are preserved from the source.

Prices are USD per million input or output tokens. The cost-efficiency chart compares input prices only; output prices and your workload also affect total cost. Shortlist models to estimate token charges for the same workload. Actual costs depend on tokens consumed and provider rates.

These general benchmarks do not measure CRE underwriting accuracy. Test a shortlist on the same rent roll, T-12 and lease examples, checking extraction, arithmetic and cited evidence against known answers before using it for live work.

The snapshot timestamp identifies the source data snapshot, not when every model was evaluated.