LLM Comparison
Claude Sonnet 4.6 vs MiMo-V2.6-Flash
Side-by-side specs, pricing & capabilities · Updated October 2026
Price vs Intelligence
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 48 5.3 | 57 273 |
| Family | Claude | MiMo |
| Status | Current | Current |
| Release Date | Feb 2026 | Sep 2026 |
| Context Window | 1.0M tokens | 1.0M tokens |
| Input Price | $3.00/M tokens | $0.14/M tokens |
| Output Price | $15.00/M tokens | $0.28/M tokens |
| Pricing Notes | Cache read: $0.3000/M tokens | USD per 1M tokens for Xiaomi MiMo pay-as-you-go API access. Cache-hit input is $0.0028 per 1M tokens. |
| Capabilities | textvisioncodetool-use | reasoningmultimodalcodingtool-useweb-searchstructured-outputcomputer-usecontext-cachingopen-weightslong-context |
| Max Output | 128K tokens | 128K tokens |
| API Identifier | anthropic/claude-sonnet-4.6 | mimo-v2.6-flash |
| Benchmarks | ||
| MMLU | 86.7anthropic | — |
| GPQA Diamond | 89.9anthropic | — |
| SWE-bench Verified | 72.5anthropic | — |
| Terminal-Bench 2.0 | 51anthropic | — |
| MATH 500 | 54.2anthropic | — |
| LiveCodeBench | 41.5anthropic | — |
| Berkeley Function Calling | 88.3anthropic | — |
| HLE | 30openrouter | — |
| GPQA-AA Elo | 1674artificial-analysis | — |
| DeepSWE v1.1 | — | 67.9xiaomi-mimo |
| AutomationBench v1.0.6 | — | 52.3xiaomi-mimo |
| Toolathlon-Verified | — | 73.6xiaomi-mimo |
| Terminal-Bench 4.0 | — | 28.8xiaomi-mimo |
| Terminal-Bench 2.1 | — | 87.6xiaomi-mimo |
| Artificial Analysis Intelligence Index v4.3.2 | — | 37.8843590141754artificial-analysis |
| View Claude Sonnet 4.6 | View MiMo-V2.6-Flash | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| MiMo-V2.6-FlashCheapest | $0.14 | $0.14 | $0.28 | — |
| Claude Sonnet 4.6 | $3.00 | $7.50 | $10.50 | +3650% |
Anthropic
Claude Sonnet 4.6
Claude Sonnet 4.6 is a multimodal llm from Anthropic. Supports up to 1,000,000 token context window. Achieves 88.0% on MMLU. Available from $3.00/M input tokens.
Xiaomi
MiMo-V2.6-Flash
MiMo-V2.6-Flash is Xiaomi's MIT-licensed, open-weight multimodal reasoning model optimized for high-frequency and large-scale professional workloads. It supports text, image, video, and audio input, a one-million-token context window, 128K-token output, tool use, web search, structured output, and agent workflows.
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