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AI Atlas

Terminal-Bench — cost vs performance

Best current row per canonical model in the group “accuracy · variant=v2.1 · evaluator=Artificial Analysis” (183 models) against cheapest current output price (USD / 1M tokens). The dashed line is the Pareto frontier: no model is both better and cheaper than a point on it.

XOutput priceInput priceParametersContextMemory (est.)ScaleloglinearBubblecontextparamsnone
Group

open / restricted weights closed Pareto frontier (7 models)

Frontier models 7

Pareto frontier
Modelaccuracy on Terminal-BenchRankcheapest current output price (USD / 1M tokens)ProviderTrust
Claude Fable 5.1Anthropic · Closed91.4%1$25OpenRouterIndependent
gpt-5.6-solOpenAI · Closed89.5%3$5OpenRouterIndependent
Gemini 3.8 FlashGoogle · Closed87.6%7$1.88OpenRouterIndependent
Qwen3.8 FlashQwen · Open weights86.1%8$0.47Together AIIndependent
GLM 5.3 FlashZ.ai (Zhipu AI) · Open weights84.3%14$0.25OpenRouterIndependent
Ling 3.0 Flash VLinclusionAI · Open weights64.4%52$0.18OpenRouterIndependent
Ling 3.0 FlashinclusionAI · Open weights55.4%68$0.063OpenRouterIndependent

Methodology. Points are the best current row per canonical model in comparability group 'accuracy · variant=v2.1 · evaluator=Artificial Analysis'. Price = cheapest current offer across providers (the provider shown). Pareto frontier maximises the score and minimises x; exact ties are all kept. memory_estimate is an estimate (see /methodology). Only the selected comparability group is plotted; points under other configurations are not mixed in. Price = cheapest current offer across providers at the time of the last crawl. Nothing is estimated except where marked.