DeepSeek·#82 of 352 on the current board·cheaper than #81 Mistral Medium 3.5
DeepSeek V3.2 is a language model from DeepSeek. It ranks #82 of 352 on ModelCap's current board, with an Index score of 60.6, measured on 3 public benchmarks. Its score range of 55.8–65.4 spans positions #64–#100. It is listed at $0.26 per million input tokens and $0.38 per million output tokens across 7 providers. It reads up to 164K tokens of context, and its weights are openly downloadable.
Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology
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.
Showing 20 of 53 rows.
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.
Not yet published: pinned evaluation dataset versions.
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.
deepseek/deepseek-v3.2OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
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.
Models within 3 places of #82 on the ModelCap Index.
Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).
The same publisher's other current models with a public Index position.
DeepSeek V3.2 holds ModelCap Index position #82 of 352 ranked language models as of 6 November 2026, with an Index score of 60.6 (interval 55.8–65.4); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.
DeepSeek V3.2 is listed at $0.26 per 1M input tokens and $0.38 per 1M output tokens as of 6 November 2026; the lowest output price among 7 providers is $0.31 on GMICloud. 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 $0.71 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 V3.2 has a published context window of 164K tokens (163,840). The snapshot lists a 147,456 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context 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-V3.2 on Hugging Face.
7 providers serve DeepSeek V3.2 through OpenRouter as of 6 November 2026: GMICloud, SiliconFlow, DeepInfra, AtlasCloud, Baidu and DigitalOcean and 1 more. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
DeepSeek V3.2 has published results on 5 public boards tracked by ModelCap as of 6 November 2026: Arena text 1425 (#127 of 419), Arena coding 1475 (#119 of 414), ARC-AGI-2 4.0% (#193 of 280), SWE-bench 70.0% (#14 of 47) and WildClawBench OpenClaw 34.0 (#27 of 34). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
DeepSeek V3.2 ranks #82 (Index 60.6) and R1 0528 ranks #86 (Index 59.7) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.
DeepSeek V3.2 first appeared in the catalogue on 1 Dec 2025. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.