Claude Sonnet 4.5 vs MiMo V2.6 Flash
MiMo V2.6 Flash: 49.2% average across five Vision Evals tasks (#57 of 65 models). We have not run Claude Sonnet 4.5 through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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Claude Sonnet 4.5 vs MiMo V2.6 Flash Comparison Table
Evals updated October 26, 2026Pricing updated November 7, 2026
| Property | Claude Sonnet 4.5 | MiMo V2.6 Flash |
|---|---|---|
| Organization | Anthropic | Xiaomi |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2025 | Sep 2026 |
| Context Window | 200K | 1.0M |
| Parameters | Unknown | 309B total, 15B active |
| License | Proprietary | MIT |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | $0.140 |
| Output $/1M | $15.00 | $0.280 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 49.2% |
| Avg cost / sample | – | $0.0003 |
| Avg speed / sample | – | 16.34s |
| By task | ||
| Object Detection (low) | – | 37.8% ±1.1, Mean of 3 runs, range 36.4 to 38.7 |
| Object Detection (high) | – | 45.0% ±2.5, Mean of 3 runs, range 42.2 to 47.1 |
| Counting (low) | – | 49.5% ±8.1, Mean of 3 runs, range 41.9 to 58.1 |
| Counting (high) | – | 64.9% ±1.4, Mean of 3 runs, range 63.5 to 66.2 |
| Identification (low) | – | 76.0% ±3.1, Mean of 3 runs, range 71.9 to 78.1 |
| Identification (high) | – | 82.3% ±4.7, Mean of 3 runs, range 78.1 to 87.5 |
| OCR (low) | – | 49.7% |
| by category |
| |
| OCR (high) | – | 50.4% |
| by category |
| |
| Reasoning (low) | – | 33.1% ±2.0, Mean of 3 runs, range 31.1 to 35.1 |
| Reasoning (high) | – | 58.5% ±1.3, Mean of 3 runs, range 57.0 to 59.6 |
Claude Sonnet 4.5 vs MiMo V2.6 Flash: Overview
Claude Sonnet 4.5, released by Anthropic in September 2025, is the company’s most advanced Sonnet-series model, built for high-performance reasoning, coding, and long-horizon agentic workflows. It is a multimodal system that accepts both text and images, with a 200,000-token context window designed for handling large documents and extended interactions. Anthropic highlights its improvements in reliability, reduced sycophancy, and alignment, making it suitable for sustained enterprise use.
It introduces infrastructure features such as a memory tool (beta), checkpointing for Claude Code, parallel tool use, and tighter integration with VS Code. Compared to Opus, which targets broader reasoning, Sonnet 4.5 is optimized for structured, long-duration tasks. Positioned against leading offerings from OpenAI and Google, it is aimed at enterprise automation, software engineering, and research-intensive applications.
MiMo-V2.6-Flash is the efficiency-oriented checkpoint of Xiaomi's MiMo-V2.6 series, a natively omnimodal foundation model that accepts text, image, video, and audio in a single model and supports a one million token context window. The language backbone is a sparse mixture-of-experts transformer with roughly 309 billion total parameters and 15 billion activated per token, organized as 48 layers with 256 routed experts and top-8 routing. It uses a hybrid attention scheme that interleaves sliding window attention with global attention layers to cut key-value cache cost on long sequences, and pairs the backbone with a vision encoder, an audio encoder, and an audio tokenizer, plus a multi-token prediction module and a draft model for faster decoding.
Training emphasizes large scale reinforcement learning on verifiable, long-horizon tasks, with RL compute, environment diversity, and grader compute scaled together in a single mixed run.
Frequently Asked Questions
Claude Sonnet 4.5 is released under Proprietary, while MiMo V2.6 Flash uses MIT. In practice: Claude Sonnet 4.5: commercial use per vendor terms; MiMo V2.6 Flash: free for commercial use. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.