DeepSeek: DeepSeek V3.1 Rank
DeepSeek V3.1 has an overall score of 66 out of 100, tied for rank 140 of 291. The published scores are price 72, context 47, parameters 71, and freshness 73. The overall score is their average. recency is not published and is left out of the average.
Data sourced from OpenRouter API and manual data collection | Last updated: Nov 3, 2026, 8:01 AM UTC
Component scores are ranked in
tied for rank 140 of 291
Component scores
| Score | Result | Published value | Source |
|---|---|---|---|
| Freshness | 73 | AI Knowledge Cutoff | |
| Recency | — | — | AI Release Date |
| Context | 47 | 164K tokens, output 147K | AI Context Window |
| Parameters | 71 | 671B total, 37B active | AI Parameter Count |
| Price | 72 | $0.425 / 1M blended, $0.25 / 1M input, $0.95 / 1M output | AI Token Price |
139 listed models have a higher overall score. Among DeepSeek models, it ranks 6 of 11.
DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...
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Frequently asked questions
What is the DeepSeek V3.1 rank?
DeepSeek V3.1 has an overall score of 66 out of 100, tied for rank 140 of 291. The published scores are price 72, context 47, parameters 71, and freshness 73. The overall score is their average. recency is not published and is left out of the average.
Where does DeepSeek V3.1 rank?
DeepSeek V3.1 is tied for rank 140 of 291. 139 listed models have a higher overall score. Among DeepSeek models, it ranks 6 of 11.
What scores make up DeepSeek V3.1?
DeepSeek V3.1 scores price 72 (AI Token Price), context 47 (AI Context Window), parameters 71 (AI Parameter Count), and freshness 73 (AI Knowledge Cutoff). The overall score of 66 is the average of those 4.