Claude Sonnet 4.5 vs Xiaomi MiMo-V2.5-Pro
Claude Sonnet 4.5 (2025) and Xiaomi MiMo-V2.5-Pro (2026) compare a standalone API model against a coding-specialized model. Claude Sonnet 4.5 ships a 200k-token context window, while Xiaomi MiMo-V2.5-Pro ships a 1.05m-token context window. On MMLU PRO, Claude Sonnet 4.5 leads by 17.5 pts. On pricing, Claude Sonnet 4.5 ranges from $3 to $6/1M input tokens by tier; Xiaomi MiMo-V2.5-Pro costs $0.43/1M input tokens. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Claude Sonnet 4.5 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 | Claude Sonnet 4.5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 1.05m |
| Cheapest output | $15/1M tokens | $0.87/1M tokens |
| Provider routes | 8 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 3 rows |
Decision tradeoffs
- Claude Sonnet 4.5 holds a shared-benchmark lead on MMLU PRO, ahead by 17.5 points.
- Claude Sonnet 4.5 has broader tracked provider coverage for fallback and procurement flexibility.
- Claude Sonnet 4.5 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Claude Sonnet 4.5 for Coding, RAG, and Agents.
- Xiaomi MiMo-V2.5-Pro holds a shared-benchmark lead on SWE-bench Verified, ahead by 1.7 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.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Claude Sonnet 4.5
$6,150
Cheapest tracked route/tier: Microsoft Foundry
Xiaomi MiMo-V2.5-Pro
$566
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $5,585. 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.
- Xiaomi MiMo-V2.5-Pro is $14.13/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Claude Sonnet 4.5 is $14.13/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Sonnet 4.5 adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-29 | 2026-04-22 |
| Context window | 200k | 1.05m |
| Parameters | — | 1T |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Proprietary |
| Openness | Proprietary | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-12 | - |
Pricing and availability
| Pricing attribute | Claude Sonnet 4.5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Input price |
| $0.43/1M tokens |
| Output price |
| $0.87/1M tokens |
| Providers |
Capabilities
| Capability | Claude Sonnet 4.5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | 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 | Claude Sonnet 4.5 | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| MMLU PRO | 86.0 | 68.5 |
| SWE-bench Verified | 77.2 | 78.9 |
| Google-Proof Q&A | 83.4 | 66.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has Claude Sonnet 4.5 at 86 and Xiaomi MiMo-V2.5-Pro at 68.5, with Claude Sonnet 4.5 ahead by 17.5 points; SWE-bench Verified has Claude Sonnet 4.5 at 77.2 and Xiaomi MiMo-V2.5-Pro at 78.9, with Xiaomi MiMo-V2.5-Pro ahead by 1.7 points; Google-Proof Q&A has Claude Sonnet 4.5 at 83.4 and Xiaomi MiMo-V2.5-Pro at 66.7, with Claude Sonnet 4.5 ahead by 16.7 points. The largest visible gap is 17.5 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: Claude Sonnet 4.5, multimodal input: Claude Sonnet 4.5, and reasoning mode: Claude Sonnet 4.5. 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, Claude Sonnet 4.5 lists tiered pricing: 0-200,001t is $3/1M input and $15/1M output; 200,001t+ is $6/1M input and $22.50/1M output, 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 Xiaomi MiMo-V2.5-Pro lower by about $6.03 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 8 providers versus 3, so concentration risk also matters.
Choose Claude Sonnet 4.5 when reasoning depth and broader provider choice are central to the workload. Choose Xiaomi MiMo-V2.5-Pro when coding workflow support, larger context windows, and lower input-token cost 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, Claude Sonnet 4.5 or Xiaomi MiMo-V2.5-Pro?
Xiaomi MiMo-V2.5-Pro supports 1.05m tokens, while Claude Sonnet 4.5 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Claude Sonnet 4.5 or Xiaomi MiMo-V2.5-Pro?
Claude Sonnet 4.5 lists tiered pricing: 0-200,001t is $3/1M input and $15/1M output; 200,001t+ is $6/1M input and $22.50/1M output. Xiaomi MiMo-V2.5-Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Claude Sonnet 4.5 or Xiaomi MiMo-V2.5-Pro open source?
Claude Sonnet 4.5 is listed under Proprietary. 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 vision, Claude Sonnet 4.5 or Xiaomi MiMo-V2.5-Pro?
Claude Sonnet 4.5 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, Claude Sonnet 4.5 or Xiaomi MiMo-V2.5-Pro?
Claude Sonnet 4.5 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 Claude Sonnet 4.5 and Xiaomi MiMo-V2.5-Pro?
Claude Sonnet 4.5 is available on Microsoft Foundry, Anthropic, Snowflake Cortex, GCP Vertex AI, and AWS Bedrock. 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.
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Last reviewed: 2026-05-26. Data sourced from public model cards and provider documentation.