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DeepSeek V3.2 vs Qwen3.5-235B-A22B

DeepSeek V3.2 (2025) and Qwen3.5-235B-A22B (2026) are general-purpose language models from DeepSeek and Alibaba. DeepSeek V3.2 ships a 160K-token context window, while Qwen3.5-235B-A22B ships a 512k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Qwen3.5-235B-A22B is safer overall; choose DeepSeek V3.2 when coding workflow support matters.

Specs

Released2025-01-012026-02-24
Context window160K512k
Parameters671B235B
Architecturedecoder onlyMoE
LicenseOpen SourceApache 2.0
Knowledge cutoff--

Pricing and availability

DeepSeek V3.2Qwen3.5-235B-A22B
Input price$0.26/1M tokens-
Output price$0.42/1M tokens-
Providers-

Capabilities

DeepSeek V3.2Qwen3.5-235B-A22B
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: DeepSeek V3.2 and code execution: DeepSeek V3.2. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: DeepSeek V3.2 has $0.26/1M input tokens and Qwen3.5-235B-A22B has no token price sourced yet. Provider availability is 4 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose DeepSeek V3.2 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, DeepSeek V3.2 or Qwen3.5-235B-A22B?

Qwen3.5-235B-A22B supports 512k tokens, while DeepSeek V3.2 supports 160K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Is DeepSeek V3.2 or Qwen3.5-235B-A22B open source?

DeepSeek V3.2 is listed under Open Source. Qwen3.5-235B-A22B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for structured outputs, DeepSeek V3.2 or Qwen3.5-235B-A22B?

DeepSeek V3.2 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for code execution, DeepSeek V3.2 or Qwen3.5-235B-A22B?

DeepSeek V3.2 has the clearer documented code execution signal in this comparison. If code execution is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run DeepSeek V3.2 and Qwen3.5-235B-A22B?

DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Qwen3.5-235B-A22B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick DeepSeek V3.2 over Qwen3.5-235B-A22B?

Qwen3.5-235B-A22B is safer overall; choose DeepSeek V3.2 when coding workflow support matters. If your workload also depends on coding workflow support, start with DeepSeek V3.2; if it depends on long-context analysis, run the same evaluation with Qwen3.5-235B-A22B.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.