Humanity's Last Exam — cost vs performance

Best current row per canonical model in the group “accuracy · evaluator=Artificial Analysis” (453 models) against cheapest current input price (USD / 1M tokens). The dashed line is the Pareto frontier: no model is both better and cheaper than a point on it.

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XOutput price Input price Parameters Context Memory (est.)Scalelog linearBubblecontext params none

open / restricted weights closed Pareto frontier (7 models)bubble = context window

Frontier models 7

Pareto frontier
Model	accuracy on Humanity's Last Exam	Rank	cheapest current input price (USD / 1M tokens)	Provider	Trust
Claude Fable 5.1Anthropic · Closed	59.1%	1	$5	OpenRouter	Independent
Claude Opus 5Anthropic · Closed	54.9%	3	$2.5	Anthropic API	Independent
gpt-5.6-solOpenAI · Closed	49.5%	5	$1	OpenRouter	Independent
Gemini 3.7 FlashGoogle · Closed	47.9%	8	$0.375	OpenRouter	Independent
GLM 5.3 FlashZ.ai (Zhipu AI) · Open weights	39.9%	33	$0.075	Z.ai API	Independent
Ling 3.0 FlashinclusionAI · Open weights	23.7%	104	$0.021	OpenRouter	Independent
Granite 4.0 MicroIBM · Open weights	5%	312	$0.017	OpenRouter	Independent

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.