DeepSeek V3.2

DeepSeek V3.2 by DeepSeek excels in the Coding category, where it ranks #92 with a composite score of 53/100. 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) It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

DeepSeek V3.2 is priced at $0.25 per million input tokens and $0.40 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, DeepSeek V3.2 holds rank #92 out of 6 models tracked. Its quality rank is #92 and adoption rank is #92. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

DeepSeek V3.2 has been evaluated across 6 different signals. Its strongest areas include Capabilities (57/100), Context Window (83/100), Output Capacity (80/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 53/100 reflects a weighted combination of all tracked signals.

DeepSeek V3.2 is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check DeepSeek's website for current free tier availability and promotional offers.