DeepSeek V3.2 vs Mixtral 8x22B v0.1
DeepSeek V3.2 (2025) and Mixtral 8x22B v0.1 (2024) are compact production models from DeepSeek and MistralAI. DeepSeek V3.2 ships a 160K-token context window, while Mixtral 8x22B v0.1 ships a 64K-token context window. On Google-Proof Q&A, DeepSeek V3.2 leads by 23.9 pts. On pricing, DeepSeek V3.2 costs $0.26/1M input tokens versus $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Pick DeepSeek V3.2 for reasoning; Mixtral 8x22B v0.1 is better when provider fit matters more.
Specs
| Released | 2025-01-01 | 2024-04-17 |
| Context window | 160K | 64K |
| Parameters | 671B | 8x22B |
| Architecture | decoder only | mixture of experts |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek V3.2 | Mixtral 8x22B v0.1 | |
|---|---|---|
| Input price | $0.26/1M tokens | $0.3/1M tokens |
| Output price | $0.42/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| DeepSeek V3.2 | Mixtral 8x22B v0.1 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek V3.2 | Mixtral 8x22B v0.1 |
|---|---|---|
| Google-Proof Q&A | 84.0 | 60.1 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has DeepSeek V3.2 at 84 and Mixtral 8x22B v0.1 at 60.1, with DeepSeek V3.2 ahead by 23.9 points. The largest visible gap is 23.9 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
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.
For cost, DeepSeek V3.2 lists $0.26/1M input and $0.42/1M output tokens, while Mixtral 8x22B v0.1 lists $0.3/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.2 lower by about $0.17 per million blended tokens. Availability is 4 providers versus 8, so concentration risk also matters.
Choose DeepSeek V3.2 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Mixtral 8x22B v0.1 when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V3.2 or Mixtral 8x22B v0.1?
DeepSeek V3.2 supports 160K tokens, while Mixtral 8x22B v0.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V3.2 or Mixtral 8x22B v0.1?
DeepSeek V3.2 is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.26/1M input and $0.42/1M output tokens. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.2 or Mixtral 8x22B v0.1 open source?
DeepSeek V3.2 is listed under Open Source. Mixtral 8x22B v0.1 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 Mixtral 8x22B v0.1?
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 Mixtral 8x22B v0.1?
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 Mixtral 8x22B v0.1?
DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.