Reasoning models tend to be the most expensive tier — they use chain-of-thought, produce more output tokens, and are priced accordingly. This ranking divides each model's weighted reasoning score by output token price, revealing which models deliver the best abstract reasoning, long-context comprehension, and multi-step logic per dollar. For applications that need strong reasoning without frontier-model budgets, the value leaders here are worth serious consideration.
Unless noted otherwise, ranking surfaces on this page use BenchLM's provisional leaderboard lane rather than the stricter sourced-only verified leaderboard.
Bottom line: Reasoning models are expensive — chain-of-thought generates more output tokens. GPT-4.1 nano and Gemini 3.1 Flash-Lite offer the best reasoning per dollar.
According to BenchLM.ai, Grok 4.1 Fast leads this ranking with a score of 177.42, followed by GPT-4.1 nano (169.45) and DeepSeek V3.2 (114.56). There is a significant gap between the leading models and the rest of the field.
The best open-weight option is DeepSeek V3.2 (ranked #3 with a score of 114.56). Open-weight models are highly competitive in this category — self-hosting is a viable alternative to proprietary APIs.
This ranking is based on provisional weighted averages across the scoring benchmarks in reasoning tracked by BenchLM.ai. For detailed model profiles, click any model name below. To compare two specific models head-to-head, use the "vs #" links.
Grok 4.1 Fast
xAI · 1M
Score: 88.7 · $0.5/1M
GPT-4.1 nano
OpenAI · 1M
Score: 67.8 · $0.4/1M
Best reasoning value. Strong reasoning scores at $0.40/1M output.
DeepSeek V3.2
DeepSeek · 128K
Score: 48.1 · $0.42/1M
GPT-4.1 nano leads reasoning value — best reasoning capability per dollar.
Gemini 3.1 Flash-Lite close second on reasoning value at the lowest price point.
Gemini 2.5 Flash good reasoning value with broader capabilities.
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The best value model is Grok 4.1 Fast by xAI with a provisional Score/$ ratio of 177.42 (score: 88.7, output: $0.5/1M tokens).
The best open-weight model is DeepSeek V3.2 at position #3.
52 models are included in this ranking.
Value scores divide the weighted reasoning score by output token price (per 1M tokens). Higher means more capability per dollar. Models with no listed price are excluded.
Value rankings favor cheap models even if absolute performance is modest. A model scoring half as well at one-tenth the price wins on value — but may not meet your quality bar. Always check raw scores alongside value rankings.
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