Xiaomi MiMo-V2.5-Pro vs Mistral Large
Xiaomi MiMo-V2.5-Pro (2026) and Mistral Large (2024) compare a coding-specialized model against a standalone API model. Xiaomi MiMo-V2.5-Pro ships a 1.05m-token context window, while Mistral Large ships a 32k-token context window. On MMLU PRO, Xiaomi MiMo-V2.5-Pro leads by 17 pts. On pricing, Mistral Large costs $0.32/1M 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: Xiaomi MiMo-V2.5-Pro is coding-specialized model, while Mistral Large is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Xiaomi MiMo-V2.5-Pro | Mistral Large |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Agents, Vision, and Classification |
| Context window | 1.05m | 32k |
| Cheapest output | $0.87/1M tokens | $0.96/1M tokens |
| Provider routes | 3 tracked | 8 tracked |
| Shared benchmarks | MMLU PRO leader | 1 shared |
Decision tradeoffs
- Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on MMLU PRO, ahead by 17 points.
- Xiaomi MiMo-V2.5-Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Xiaomi MiMo-V2.5-Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- Local decision data tags Xiaomi MiMo-V2.5-Pro for Coding, RAG, and Agents.
- Mistral Large has broader tracked provider coverage for fallback and procurement flexibility.
- Mistral Large uniquely exposes Vision in local model data.
- Local decision data tags Mistral Large for Agents, Vision, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Xiaomi MiMo-V2.5-Pro
$566
Cheapest tracked route/tier: OpenRouter
Mistral Large
$496
Cheapest tracked route/tier: GCP Vertex AI
Estimated monthly gap: $69.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Mistral Large is $0.09/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large adds Vision in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Xiaomi MiMo-V2.5-Pro is $0.09/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-22 | 2024-02-08 |
| Context window | 1.05m | 32k |
| Parameters | 1T | 123B |
| Architecture | Mixture of Experts | - |
| License | Proprietary | Mistral License |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use: conditional | Commercial use: non-commercial |
| Knowledge cutoff | - | 2024-03 |
Pricing and availability
| Pricing attribute | Xiaomi MiMo-V2.5-Pro | Mistral Large |
|---|---|---|
| Input price | $0.43/1M tokens | $0.32/1M tokens |
| Output price | $0.87/1M tokens | $0.96/1M tokens |
| Providers |
Capabilities
| Capability | Xiaomi MiMo-V2.5-Pro | Mistral Large |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Xiaomi MiMo-V2.5-Pro | Mistral Large |
|---|---|---|
| MMLU PRO | 68.5 | 51.5 |
Deep dive
On shared benchmark coverage, MMLU PRO has Xiaomi MiMo-V2.5-Pro at 68.5 and Mistral Large at 51.5, with Xiaomi MiMo-V2.5-Pro ahead by 17 points. The largest visible gap is 17 points on MMLU PRO, 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 vision: Mistral Large. Both models share function calling, tool use, and 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, Xiaomi MiMo-V2.5-Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider, while Mistral Large lists $0.32/1M input and $0.96/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Large lower by about $0.05 per million blended tokens. Availability is 3 providers versus 8, so concentration risk also matters.
Choose Xiaomi MiMo-V2.5-Pro when coding workflow support and larger context windows are central to the workload. Choose Mistral Large when vision-heavy evaluation, lower input-token cost, 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, Xiaomi MiMo-V2.5-Pro or Mistral Large?
Xiaomi MiMo-V2.5-Pro supports 1.05m tokens, while Mistral Large supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Xiaomi MiMo-V2.5-Pro or Mistral Large?
Mistral Large is cheaper on tracked token pricing. Xiaomi MiMo-V2.5-Pro costs $0.43/1M input and $0.87/1M output tokens. Mistral Large costs $0.32/1M input and $0.96/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Xiaomi MiMo-V2.5-Pro or Mistral Large open source?
Xiaomi MiMo-V2.5-Pro is listed under Proprietary. Mistral Large is listed under Mistral License. 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 vision, Xiaomi MiMo-V2.5-Pro or Mistral Large?
Mistral Large has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, Xiaomi MiMo-V2.5-Pro or Mistral Large?
Both Xiaomi MiMo-V2.5-Pro and Mistral Large expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Xiaomi MiMo-V2.5-Pro and Mistral Large?
Xiaomi MiMo-V2.5-Pro is available on OpenRouter, Xiaomi, and Novita AI. Mistral Large is available on NVIDIA NIM, Microsoft Foundry, AWS Bedrock, Mistral AI Studio, and IBM watsonx. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-16. Data sourced from public model cards and provider documentation.