BenchmarksArtificial Analysis Intelligence Index

Artificial Analysis Intelligence Index — cost vs performance

Best current row per canonical model in the group “index” (477 models) against total parameters. 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 (10 models)bubble = total parameters

Frontier models 10

Pareto frontier
Model	index on Artificial Analysis Intelligence Index	Rank	total parameters	Provider	Trust
GLM 5.3Z.ai (Zhipu AI) · Open weights	44.9	7	753.3B	—	Independent
GLM 5.3 FlashZ.ai (Zhipu AI) · Open weights	41.9	12	321.3B	—	Independent
Qwen3.8 27BQwen · Open weights	33.9	34	27.8B	—	Independent
Gemma 4 26B A4BGoogle · Open weights	16.7	146	25.8B	—	Independent
Qwen3.5-9BQwen · Open weights	13.7	174	9.65B	—	Independent
Qwen3.5-4BQwen · Open weights	13.1	183	4.66B	—	Independent
LFM2.5-2.6B (free)Liquid AI · Open weights	8.39	279	2.7B	—	Independent
DeepSeek-R1-Distill-Qwen-1.5BDeepSeek · Open weights	5.51	414	1.78B	—	Independent
LFM2.5-1.2B-InstructLiquid AI · Open weights	5.21	440	1.17B	—	Independent
Qwen3-0.6BQwen · Open weights	4.83	463	751.6M	—	Independent

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