Claude Sonnet 4.5 vs MiMo V2.6 Pro
MiMo V2.6 Pro: 50.3% average across five Vision Evals tasks (#56 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 Pro Comparison Table
Evals updated October 26, 2026Pricing updated November 6, 2026
| Property | Claude Sonnet 4.5 | MiMo V2.6 Pro |
|---|---|---|
| Organization | Anthropic | Xiaomi |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Sep 2025 | Sep 2026 |
| Context Window | 200K | 1.0M |
| Parameters | Unknown | 1.02T total, 42B active |
| License | Proprietary | MIT |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | $0.435 |
| Output $/1M | $15.00 | $0.870 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 50.3% |
| Avg cost / sample | – | $0.0011 |
| Avg speed / sample | – | 9.45s |
| By task | ||
| Object Detection (low) | – | 42.0% ±1.1, Mean of 3 runs, range 40.9 to 43.1 |
| Object Detection (high) | – | 46.7% ±0.8, Mean of 3 runs, range 45.7 to 47.3 |
| Counting (low) | – | 50.0% ±2.0, Mean of 3 runs, range 48.6 to 52.7 |
| Counting (high) | – | 59.0% ±5.4, Mean of 3 runs, range 52.7 to 63.5 |
| Identification (low) | – | 76.0% ±1.6, Mean of 3 runs, range 75.0 to 78.1 |
| Identification (high) | – | 78.1% ±4.7, Mean of 3 runs, range 71.9 to 81.3 |
| OCR (low) | – | 48.6% |
| by category |
| |
| OCR (high) | – | 49.9% |
| by category |
| |
| Reasoning (low) | – | 35.1% ±2.6, Mean of 3 runs, range 32.5 to 37.8 |
| Reasoning (high) | – | 55.9% ±2.3, Mean of 3 runs, range 54.3 to 58.9 |
Claude Sonnet 4.5 vs MiMo V2.6 Pro: 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 Pro is the flagship omni-modal foundation model in Xiaomi's MiMo V2.6 series, released as open weights alongside a Flash variant and a 9B distillation of Qwen3.5. It uses a sparse mixture-of-experts transformer with 1.02 trillion total parameters and roughly 42 billion activated per token, paired with a hybrid attention design that interleaves sliding-window and global attention layers to support a context window of about one million tokens. Dedicated encoders handle non-text inputs, including a vision encoder of roughly 681 million parameters and an audio tokenizer stack, so the model accepts text, images, video, and audio and returns text.
Post-training centers on large-scale reinforcement learning across thousands of interactive environments, combined with agentic grading, self-correction cold start, and a multi-prefix multi-teacher on-policy distillation stage that extends behavior to tasks that are hard to verify automatically.
Frequently Asked Questions
Claude Sonnet 4.5 is released under Proprietary, while MiMo V2.6 Pro uses MIT. In practice: Claude Sonnet 4.5: commercial use per vendor terms; MiMo V2.6 Pro: 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.