All DeepSeek models ranked by benchmark performance.
Unless noted otherwise, ranking surfaces on this page use BenchLM's provisional leaderboard lane rather than the stricter sourced-only verified leaderboard.
Bottom line: DeepSeek models are open-weight and free or nearly free. DeepSeek V3.2 (Thinking) leads the lineup. Strong on math and reasoning, competitive with mid-tier proprietary models.
According to BenchLM.ai, DeepSeek V4 Pro (Max) leads this ranking with a score of 87, followed by DeepSeek V4 Pro (High) (83) and DeepSeek V4 Flash (Max) (75). There is a significant gap between the leading models and the rest of the field.
All models in this ranking are open-weight, meaning they can be self-hosted for maximum control and cost efficiency.
This ranking is based on provisional overall weighted scores across BenchLM.ai's scoring formula 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.
DeepSeek V4 Pro (Max)
DeepSeek · 1M
DeepSeek V4 Pro (High)
DeepSeek · 1M
DeepSeek V4 Flash (Max)
DeepSeek · 1M
DeepSeek V3.2 (Thinking) leads DeepSeek's lineup — best on knowledge (70) and agentic (69).
DeepSeek V3.2 non-reasoning variant with strong math (71) and multilingual (69).
DeepSeek Coder 2.0 coding-focused with strong math (71) and agentic (65).
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The top model is DeepSeek V4 Pro (Max) by DeepSeek with a provisional score of 87.
The best open-weight model is DeepSeek V4 Pro (Max) at position #1.
15 models are included in this ranking.
Models are ranked by the same overall BenchLM score used across all leaderboards. Comparing within DeepSeek's lineup helps identify which model fits your use case and budget.
This page only shows DeepSeek models. Cross-provider comparison requires the overall or category-specific leaderboards. Newer models may have limited benchmark coverage initially.
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