Terminal-Bench — cost vs performance

Best current row per canonical model in the group “accuracy · variant=v2.1 · evaluator=Artificial Analysis” (183 models) against context window (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 (8 models)bubble = context window

Frontier models 8

Pareto frontier
Model	accuracy on Terminal-Bench	Rank	context window (tokens)	Provider	Trust
Claude Fable 5.1Anthropic · Closed	91.4%	1	1M	—	Independent
Grok 4.6xAI · Closed	88.4%	5	500K	—	Independent
motif-3Motif Technologies · Open weights	74.9%	33	262.1K	—	Independent
apodex-1-1Apodex · Closed	69.7%	41	256K	—	Independent
Ling 3.0 Flash VLinclusionAI · Open weights	64.4%	52	131.1K	—	Independent
Mercury 2Inception · Closed	27.3%	113	128K	—	Independent
qwen3-32b-instructAlibaba Group · Open weights	5.24%	152	32.8K	—	Independent
gemma-3n-e4bGoogle · Open weights	0.75%	176	32K	—	Independent

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.