LLM Reference

Xiaomi MiMo-V2.5-Pro vs Mistral Large 3 675B Instruct

Xiaomi MiMo-V2.5-Pro (2026) and Mistral Large 3 675B Instruct (2025) 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 3 675B Instruct ships a 128k-token context window. On MMLU PRO, Mistral Large 3 675B Instruct leads by 17 pts. On pricing, Xiaomi MiMo-V2.5-Pro costs $0.43/1M input tokens versus $0.50/1M 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 3 675B Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalXiaomi MiMo-V2.5-ProMistral Large 3 675B Instruct
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopsmultimodal apps and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1.05m128k
Cheapest output$0.87/1M tokens$1.50/1M tokens
Provider routes3 tracked6 tracked
Shared benchmarks2 sharedMMLU PRO leader

Decision tradeoffs

Choose Xiaomi MiMo-V2.5-Pro when...
  • Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on Google-Proof Q&A, ahead by 22.8 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.
  • 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.
Choose Mistral Large 3 675B Instruct when...
  • Mistral Large 3 675B Instruct holds a shared-benchmark lead on MMLU PRO, ahead by 17 points.
  • Mistral Large 3 675B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Large 3 675B Instruct uniquely exposes Vision and Multimodal in local model data.
  • Local decision data tags Mistral Large 3 675B Instruct 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.

Lower estimate Xiaomi MiMo-V2.5-Pro

Xiaomi MiMo-V2.5-Pro

$566

Cheapest tracked route/tier: OpenRouter

Mistral Large 3 675B Instruct

$775

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $210. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Xiaomi MiMo-V2.5-Pro -> Mistral Large 3 675B Instruct
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Mistral Large 3 675B Instruct is $0.63/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Function calling and Tool use before moving production traffic.
  • Mistral Large 3 675B Instruct adds Vision and Multimodal in local capability data.
Mistral Large 3 675B Instruct -> Xiaomi MiMo-V2.5-Pro
  • Provider overlap exists on OpenRouter; start route-level A/B tests there.
  • Xiaomi MiMo-V2.5-Pro is $0.63/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision and Multimodal before moving production traffic.
  • Xiaomi MiMo-V2.5-Pro adds Function calling and Tool use in local capability data.

Specs

Specification
Released2026-04-222025-12-01
Context window1.05m128k
Parameters1T675B
ArchitectureMixture of ExpertsDecoder Only
LicenseProprietaryApache 2.0OSI-approved
OpennessProprietaryOpen source
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff-2024-11

Pricing and availability

Pricing attributeXiaomi MiMo-V2.5-ProMistral Large 3 675B Instruct
Input price$0.43/1M tokens$0.50/1M tokens
Output price$0.87/1M tokens$1.50/1M tokens
Providers

Capabilities

CapabilityXiaomi MiMo-V2.5-ProMistral Large 3 675B Instruct
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkXiaomi MiMo-V2.5-ProMistral Large 3 675B Instruct
MMLU PRO68.585.5
Google-Proof Q&A66.743.9

Deep dive

On shared benchmark coverage, MMLU PRO has Xiaomi MiMo-V2.5-Pro at 68.5 and Mistral Large 3 675B Instruct at 85.5, with Mistral Large 3 675B Instruct ahead by 17 points; Google-Proof Q&A has Xiaomi MiMo-V2.5-Pro at 66.7 and Mistral Large 3 675B Instruct at 43.9, with Xiaomi MiMo-V2.5-Pro ahead by 22.8 points. The largest visible gap is 22.8 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 vision: Mistral Large 3 675B Instruct, multimodal input: Mistral Large 3 675B Instruct, function calling: Xiaomi MiMo-V2.5-Pro, and tool use: Xiaomi MiMo-V2.5-Pro. 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, Xiaomi MiMo-V2.5-Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider, while Mistral Large 3 675B Instruct lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Xiaomi MiMo-V2.5-Pro lower by about $0.23 per million blended tokens. Availability is 3 providers versus 6, so concentration risk also matters.

Choose Xiaomi MiMo-V2.5-Pro when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Mistral Large 3 675B Instruct when vision-heavy evaluation 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 3 675B Instruct?

Xiaomi MiMo-V2.5-Pro supports 1.05m tokens, while Mistral Large 3 675B Instruct supports 128k 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 3 675B Instruct?

Xiaomi MiMo-V2.5-Pro is cheaper on tracked token pricing. Xiaomi MiMo-V2.5-Pro costs $0.43/1M input and $0.87/1M output tokens. Mistral Large 3 675B Instruct costs $0.50/1M input and $1.50/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Xiaomi MiMo-V2.5-Pro or Mistral Large 3 675B Instruct open source?

Xiaomi MiMo-V2.5-Pro is listed under Proprietary. Mistral Large 3 675B Instruct 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 vision, Xiaomi MiMo-V2.5-Pro or Mistral Large 3 675B Instruct?

Mistral Large 3 675B Instruct 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.

Which is better for multimodal input, Xiaomi MiMo-V2.5-Pro or Mistral Large 3 675B Instruct?

Mistral Large 3 675B Instruct has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Xiaomi MiMo-V2.5-Pro and Mistral Large 3 675B Instruct?

Xiaomi MiMo-V2.5-Pro is available on OpenRouter, Xiaomi, and Novita AI. Mistral Large 3 675B Instruct is available on OpenRouter, AWS Bedrock, NVIDIA NIM, Mistral AI Studio, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-19. Data sourced from public model cards and provider documentation.