DeepSeek-V3.2 is a model that harmonizes high computational efficiency with superior reasoning and agent performance. DeepSeek's approach is built upon three key technical breakthroughs: DeepSeek Sparse Attention (DSA), scalable reinforcement learning framework, and large scale agentic task synthesis pipeline.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Deepseek V3.2 is listed in Requesty’s public model catalogue under the exact routing identifier vertex/deepseek-v3.2. DeepSeek-V3.2 is a model that harmonizes high computational efficiency with superior reasoning and agent performance. DeepSeek's approach is built upon three key technical breakthroughs: DeepSeek Sparse Attention (DSA), scalable reinforcement learning framework, and large scale agentic task synthesis pipeline.
At the time this draft was collected, the catalogue records a context window of 163,840 tokens and a maximum output of 65,535 tokens. It records reasoning support, vision input support, tool-calling support, and image-generation support. These fields describe the routing catalogue entry and should be rechecked against the current provider documentation before production use.
The source catalogue reports input and output prices when available. Pricing can depend on the route, region, token tier, cache use, account, and date, so this record does not infer a commercial commitment from a single snapshot. Confirm current pricing, data handling, regional controls, rate limits, and availability with the current upstream documentation.
This is a source-backed draft imported from Requesty’s public catalogue. It is not published automatically. An editor must verify the exact model identifier, the material claims, and the chosen deployment path before approving it for public discovery or sitemap inclusion.
Use the recorded facts as a shortlist, then validate the model against representative inputs and production constraints.
Deepseek V3.2 is categorized for Image-text-to-text, Text-to-image, Text-to-text AI models. Its current record accepts text, image and produces text, image. Confirm file formats, preprocessing, and provider-specific request schemas before implementation.
The directory records 163.8K context and 65.5K maximum output. Listed token prices are $0.56 input and $1.68 output per 1M tokens. Treat missing values as unknown and recheck current commercial terms.
Recorded output speed is — and time to first token is —. Hosting route, region, prompt length, concurrency, and provider load can materially change both measurements.
This page separates sourced model facts from incomplete fields. Benchmark evidence is displayed only when its source is linked and verified. Before choosing Deepseek V3.2, test task quality, tool reliability, safety behavior, data controls, rate limits, and total cost on the exact route you intend to use.
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