deepseek
DeepSeek: DeepSeek V3.2
deepseek/deepseek-v3.2
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
Specifications
- Model ID
- deepseek/deepseek-v3.2
- Canonical ID
- deepseek/deepseek-v3.2-20251201
- Creator
- deepseek
- Added to OpenRouter
- 01.12.2025
- Context length
- 163,840
- Modality
- text->text
- Input modalities
- text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.260 / out $0.380
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Coding | BB — next 30% of the cohort | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 44.2 | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 49.4% · rank 85 | 1,115Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · asciiartwin rate 40.5% · rank 68 | 1,078Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 49.3% · rank 87 | 1,154Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 48.2% · rank 81 | 1,156Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 46.5% · rank 91 | 1,122Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · svgwin rate 40.8% · rank 86 | 1,024Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 46.8% · rank 85 | 1,140Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 50.2% · rank 83 | 1,168Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| GMICloudfp8 | 163,840 | $0.209 | $0.310 | — | — | 100% |
| SiliconFlowfp8 | 163,840 | $0.259 | $0.800 | — | — | 100% |
| DeepInfrafp4 | 163,840 | $0.260 | $0.380 | — | — | 100% |
| AtlasCloudfp8 | 163,840 | $0.260 | $0.380 | — | — | 100% |
| Baidufp8 | 131,072 | $0.280 | $0.420 | — | — | 100% |
| DigitalOcean | 163,840 | $0.300 | $0.960 | — | — | 96.67% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.