MiMo V2.6 Pro vs Qwen3.6 Plus
Compare MiMo V2.6 Pro and Qwen3.6 Plus side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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MiMo V2.6 Pro vs Qwen3.6 Plus Comparison Table
Evals updated September 22, 2026Pricing updated September 23, 2026
| Property | MiMo V2.6 Pro | Qwen3.6 Plus |
|---|---|---|
| Organization | Xiaomi | Qwen |
| Category | open | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Apr 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | 1.02T total, 42B active | |
| License | MIT | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.435 | $0.325 |
| Output $/1M | $0.870 | $1.95 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 62.5% | Not evaluated |
| Avg cost / sample | $0.0008 | – |
| Avg speed / sample | 8.47s | – |
| 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) | 90.7% ±1.7, Mean of 3 runs, range 88.5 to 91.9 | – |
| OCR (high) | 87.5% ±2.7, Mean of 3 runs, range 85.3 to 90.6 | – |
| Data Extraction (low) | 81.1% ±0.5, Mean of 3 runs, range 80.4 to 81.4 | – |
| Data Extraction (high) | 80.4% ±1.5, Mean of 3 runs, range 79.4 to 82.5 | – |
| 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 | – |
MiMo V2.6 Pro vs Qwen3.6 Plus: Overview
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. The resulting model targets long-horizon agentic work such as software engineering, terminal and computer-use operation, tool calling, cybersecurity analysis, and visual coding, and it reports gains over the prior MiMo generation on SWE-bench Verified, Terminal Bench, and internal visual coding and cyber benchmarks.
Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.
Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.
Frequently Asked Questions
Qwen3.6 Plus has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
MiMo V2.6 Pro is released under MIT, while Qwen3.6 Plus uses Proprietary. 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 image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.