How does DeepSeek V3.1 rank among AI models?
DeepSeek V3.1 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
DeepSeek·deepseek/deepseek-chat-v3.1
DeepSeek V3.1 is ModelCap archive rank #117 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.1 listed OpenRouter input price is $0.25 per 1M tokens and listed output price is $0.95 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.1 has a published context limit of 164K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.1 has 8 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.1 weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.
Snapshot facts · download the public dataset · methodology
Superseded by DeepSeek V3.2. It no longer holds a current-board position; its all-versions archive rank is #117.
Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
Published Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.
Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Missing: evaluationProvenance.evaluation-dataset-revisions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
DeepSeek V3.1 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
DeepSeek V3.1 is listed at $0.25 per 1M input tokens and $0.95 per 1M output tokens as of 22 September 2026 across 8 providers. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.975 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
DeepSeek V3.1 has a published context window of 164K tokens (163,840) and a maximum output of 33K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.
Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is deepseek-ai/DeepSeek-V3.1 on Hugging Face.
8 providers serve DeepSeek V3.1 through OpenRouter as of 22 September 2026: DeepInfra, SiliconFlow, Novita, AtlasCloud, CoreWeave and Mara and 2 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
DeepSeek V3.1 has published results on 3 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1456 (#136 of 397), AA τ²-Bench Telecom 34.8% (#248 of 436) and AA Humanity's Last Exam 6.7% (#355 of 615). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
DeepSeek V3.1 first appeared in the catalogue on 21 Aug 2025, with a published knowledge cutoff of 2025-03-31. It has since been superseded by DeepSeek V3.2. Rank and price movements since then are recorded on the site's changes feed.