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AI Atlas

SciCode — cost vs performance

Best current row per canonical model in the group “accuracy · evaluator=Artificial Analysis” (129 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.

open / restricted weights closed Pareto frontier (6 models)

Frontier models 6

Pareto frontier
Modelaccuracy on SciCodeRankcheapest current output price (USD / 1M tokens)ProviderTrust
Claude Fable 5.1Anthropic · Closed63.1%1$25Anthropic APIIndependent
Gemini 3.7 FlashGoogle · Closed59.8%3$1.88OpenRouterIndependent
gpt-5.6-lunaOpenAI · Closed53.6%22$0.60OpenAI APIIndependent
GLM 5.3 FlashZ.ai (Zhipu AI) · Open weights51.6%28$0.25OpenRouterIndependent
Ling 3.0 Flash VLinclusionAI · Open weights44.2%63$0.18OpenRouterIndependent
Ling 3.0 FlashinclusionAI · Open weights42.0%74$0.063OpenRouterIndependent

Methodology. Points are the best current row per canonical model in comparability group 'accuracy · 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.