Claude Fable 5.2 vs MiMo V2.6 Pro
Claude Fable 5.2 and MiMo V2.6 Pro score 86.5% vs 50.3% averaged across five Vision Evals tasks (#2 and #58 of 67 models), so Claude Fable 5.2 leads overall.
- Claude Fable 5.2 wins all 5 tasks, with its widest lead on reasoning (88.1% vs 35.1%).
- MiMo V2.6 Pro is under a tenth of the cost: $0.0011 vs $0.031 overall average cost per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Claude Fable 5.2 vs MiMo V2.6 Pro live
Run the same image across every model that supports a task and compare their outputs side-by-side.
These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Claude Fable 5.2 vs MiMo V2.6 Pro on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Fable 5.2 vs MiMo V2.6 Pro Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Fable 5.2 | MiMo V2.6 Pro |
|---|---|---|
| Organization | Anthropic | Xiaomi |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Nov 2026 | Sep 2026 |
| Context Window | 1.0M | 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 | $8.00 | $0.435 |
| Output $/1M | $40.00 | $0.870 |
| Vision Tasks | ||
| Captioning | Supported | Demo |
| Classification | Supported | Demo |
| Object Detection | Supported | Demo |
| OCR | Supported | Demo |
| Visual Question Answering | Supported | Demo |
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 86.5% | 50.3% |
| Avg cost / sample | $0.031 | $0.0011 |
| Avg speed / sample | 9.33s | 9.45s |
| By task | ||
| Object Detection (low) | 81.6% ±0.3, Mean of 3 runs, range 81.2 to 81.9 | 42.0% ±1.1, Mean of 3 runs, range 40.9 to 43.1 |
| Object Detection (high) | 83.3% ±0.5, Mean of 3 runs, range 82.8 to 83.7 | 46.7% ±0.8, Mean of 3 runs, range 45.7 to 47.3 |
| Counting (low) | 86.5% ±0.0, Mean of 3 runs, range 86.5 to 86.5 | 50.0% ±2.0, Mean of 3 runs, range 48.6 to 52.7 |
| Counting (high) | 92.8% ±1.4, Mean of 3 runs, range 91.9 to 94.6 | 59.0% ±5.4, Mean of 3 runs, range 52.7 to 63.5 |
| Identification (low) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | 76.0% ±1.6, Mean of 3 runs, range 75.0 to 78.1 |
| Identification (high) | 94.8% ±1.6, Mean of 3 runs, range 93.8 to 96.9 | 78.1% ±4.7, Mean of 3 runs, range 71.9 to 81.3 |
| OCR (low) | 79.5% | 48.6% |
| by category |
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| OCR (high) | 84.8% | 49.9% |
| by category |
|
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| Reasoning (low) | 88.1% ±1.3, Mean of 3 runs, range 86.8 to 89.4 | 35.1% ±2.6, Mean of 3 runs, range 32.5 to 37.8 |
| Reasoning (high) | 92.0% ±1.0, Mean of 3 runs, range 91.4 to 93.4 | 55.9% ±2.3, Mean of 3 runs, range 54.3 to 58.9 |
Claude Fable 5.2 vs MiMo V2.6 Pro: Overview
Claude Fable 5.2 is a proprietary multimodal model from Anthropic, released on November 9, 2026. It accepts text and images and produces text, with a one million token context window and up to 128,000 output tokens. Adaptive thinking is always enabled, with an effort setting that controls reasoning. Anthropic positions Fable for demanding reasoning and long-running technical work, including coding and analysis of visual inputs.
Fable 5.2 succeeds Fable 5.1. Anthropic reports improvements in coding, reasoning, and vision, with output generation up to 30% faster than its predecessor. Fable and Mythos 5.2 share an underlying model, with additional cybersecurity and biology safeguards applied to Fable. Model weights are not publicly released.
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
On Roboflow's Vision Evals, Claude Fable 5.2 performed better. It scores higher on all five vision tasks and averages 86.5% (#2 of 67) against 50.3% (#58 of 67) for MiMo V2.6 Pro. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Reasoning benchmark at low effort, Claude Fable 5.2 leads with 88.1% against 35.1%. This is the widest gap between the two models across the benchmark's tasks.
MiMo V2.6 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0011 per sample against $0.031. Claude Fable 5.2 is priced at $8.00 per 1M input tokens and $40.00 per 1M output; MiMo V2.6 Pro is priced at $0.43 per 1M input tokens and $0.87 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Fable 5.2 is faster. Across Roboflow's Vision Evals it averaged 9.3s per inference against 9.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.