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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 that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments. Users can control the reasoning behaviour with the `reasoning` `enabled` boolean. [Learn more in our docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#enable-reasoning-with-default-config)
| Signal | Strength | Weight | Impact |
|---|---|---|---|
| Benchmarksjust now | 70 | 30% | +20.9 |
| Recencyjust now | 100 | 15% | +15.0 |
| Capabilitiesjust now | 67 | 20% | +13.3 |
| Context Windowjust now | 83 | 10% | +8.3 |
| Output Capacityjust now | 20 | 10% | +2.0 |
| Pricingjust now | 0 | 15% | +0.1 |
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You save $39.01/month vs category average
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