DeepSeek V3.2 vs Xiaomi MiMo-V2.5-Pro
DeepSeek V3.2 (2025) and Xiaomi MiMo-V2.5-Pro (2026) compare a standalone API model against a coding-specialized model. DeepSeek V3.2 ships a 160k-token context window, while Xiaomi MiMo-V2.5-Pro ships a 1.05m-token context window. On SWE-bench Verified, Xiaomi MiMo-V2.5-Pro leads by 8.9 pts. On pricing, DeepSeek V3.2 costs $0.25/1M input tokens versus $0.43/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: DeepSeek V3.2 is standalone API model, while Xiaomi MiMo-V2.5-Pro is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.2 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 160k | 1.05m |
| Cheapest output | $0.38/1M tokens | $0.87/1M tokens |
| Provider routes | 7 tracked | 3 tracked |
| Shared benchmarks | 2 rows | SWE-bench Verified leader |
Decision tradeoffs
- DeepSeek V3.2 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 17.3 points.
- DeepSeek V3.2 has the lower cheapest tracked output price at $0.38/1M tokens.
- DeepSeek V3.2 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V3.2 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.2 for Coding, RAG, and Agents.
- Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on SWE-bench Verified, ahead by 8.9 points.
- Xiaomi MiMo-V2.5-Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Xiaomi MiMo-V2.5-Pro uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Xiaomi MiMo-V2.5-Pro for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3.2
$296
Cheapest tracked route/tier: OpenRouter
Xiaomi MiMo-V2.5-Pro
$566
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $269. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- Xiaomi MiMo-V2.5-Pro is $0.49/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- Xiaomi MiMo-V2.5-Pro adds Function calling and Tool use in local capability data.
- Provider overlap exists on OpenRouter and Novita AI; start route-level A/B tests there.
- DeepSeek V3.2 is $0.49/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- DeepSeek V3.2 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-01 | 2026-04-22 |
| Context window | 160k | 1.05m |
| Parameters | 671B | 1T |
| Architecture | decoder only | mixture of experts |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V3.2 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Input price | $0.25/1M tokens | $0.43/1M tokens |
| Output price | $0.38/1M tokens | $0.87/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.2 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3.2 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| SWE-bench Verified | 70.0 | 78.9 |
| Google-Proof Q&A | 84.0 | 66.7 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek V3.2 at 70 and Xiaomi MiMo-V2.5-Pro at 78.9, with Xiaomi MiMo-V2.5-Pro ahead by 8.9 points; Google-Proof Q&A has DeepSeek V3.2 at 84 and Xiaomi MiMo-V2.5-Pro at 66.7, with DeepSeek V3.2 ahead by 17.3 points. The largest visible gap is 17.3 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 function calling: Xiaomi MiMo-V2.5-Pro, tool use: Xiaomi MiMo-V2.5-Pro, and code execution: DeepSeek V3.2. Both models share structured outputs, 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 $0.25/1M input and $0.38/1M output tokens on the cheapest tracked provider, while Xiaomi MiMo-V2.5-Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.2 lower by about $0.28 per million blended tokens. Availability is 7 providers versus 3, so concentration risk also matters.
Choose DeepSeek V3.2 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Xiaomi MiMo-V2.5-Pro when coding workflow support 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.
FAQ
Which has a larger context window, DeepSeek V3.2 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro supports 1.05m 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.
Which is cheaper, DeepSeek V3.2 or Xiaomi MiMo-V2.5-Pro?
DeepSeek V3.2 is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.25/1M input and $0.38/1M output tokens. Xiaomi MiMo-V2.5-Pro costs $0.43/1M input and $0.87/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.2 or Xiaomi MiMo-V2.5-Pro open source?
DeepSeek V3.2 is listed under MIT. Xiaomi MiMo-V2.5-Pro is listed under Proprietary. 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 function calling, DeepSeek V3.2 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, DeepSeek V3.2 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro has the clearer documented tool use signal in this comparison. If tool use 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 Xiaomi MiMo-V2.5-Pro?
DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, OpenRouter, and Microsoft Foundry. Xiaomi MiMo-V2.5-Pro is available on OpenRouter, Xiaomi, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-26. Data sourced from public model cards and provider documentation.