Claude Fable 5.1 vs Gemini 3.1 Pro
Compare Claude Fable 5.1 and Gemini 3.1 Pro side-by-side. See how these vision models stack up in Object Detection, OCR, Image Captioning, Open Prompt, and Classification.
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Models in this comparison
Claude Fable 5.1 vs Gemini 3.1 Pro on Vision Evals
Gemini 3.1 Pro scores higher on 5 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.1 Pro leads 67.4% to 61.4%.
Overall, Claude Fable 5.1 averages 81.3% (#7 of 36) against 83.3% (#5 of 36) for Gemini 3.1 Pro.
Gemini 3.1 Pro is both cheaper ($0.0093 vs $0.035 per sample) and faster (7.8s vs 8.3s per sample).
Claude Fable 5.1 vs Gemini 3.1 Pro Comparison Table
Evals updated September 2, 2026Pricing updated September 2, 2026
| Property | Claude Fable 5.1 | Gemini 3.1 Pro |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Feb 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $10.00 | $2.00 |
| Output $/1M | $50.00 | $12.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | 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 | 81.3% | 83.3% |
| Avg cost / sample | $0.035 | $0.0093 |
| Avg speed / sample | 8.28s | 7.81s |
| By task | ||
| Object Detection (low) | 61.4% ±0.5, Mean of 3 runs, range 61.0 to 62.0 | 67.4% |
| Object Detection (high) | 65.0% ±0.4, Mean of 3 runs, range 64.6 to 65.3 | – |
| Counting (low) | 69.4% ±2.7, Mean of 3 runs, range 66.2 to 71.6 | 71.6% |
| Counting (high) | 73.0% ±4.7, Mean of 3 runs, range 67.6 to 77.0 | – |
| Identification (low) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 100.0% |
| Identification (high) | 96.9% ±3.1, Mean of 3 runs, range 93.8 to 100.0 | – |
| OCR (low) | 94.0% ±0.4, Mean of 3 runs, range 93.6 to 94.4 | 92.6% |
| OCR (high) | 93.6% ±0.2, Mean of 3 runs, range 93.5 to 93.9 | – |
| Data Extraction (low) | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | 95.9% |
| Data Extraction (high) | 93.5% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | – |
| Reasoning (low) | 72.0% ±1.3, Mean of 3 runs, range 70.9 to 73.5 | 72.2% |
| Reasoning (high) | 73.1% ±2.0, Mean of 3 runs, range 71.5 to 75.5 | 74.8% |
Claude Fable 5.1 vs Gemini 3.1 Pro: Overview
Claude Fable 5.1 is a proprietary multimodal model from Anthropic in the Mythos-class tier of the Claude 5 family, positioned above Claude Opus for demanding reasoning and long-horizon agentic work. It accepts text and images as input and returns text, with a one million token context window and a maximum output of 128 thousand tokens. Adaptive thinking is always on, and an effort parameter controls how much reasoning the model applies to a given request. Anthropic reports a reliable knowledge and training data cutoff of June 2026. Claude Fable 5.1 and Claude Mythos 5.1 share the same underlying model; the difference between them is the set of safety classifiers applied to dual-use cybersecurity and biology requests.
On the vision side, Anthropic documents improvements in reading dense charts, financial filings, and tables nested inside PDF documents, which extends the model toward document understanding, chart question answering, and spreadsheet and slide work. Reported evaluations cover agentic scientific research on Terminal-Bench-Science 0.1, agentic coding on Terminal-Bench 4.0, computer use on OSWorld 2.0, and multidisciplinary reasoning on Humanity's Last Exam. Model weights are not published.
Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.
The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on 5 of the six vision tasks and averages 83.3% (#5 of 36) against 81.3% (#7 of 36) for Claude Fable 5.1. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Object Detection benchmark at low effort, Gemini 3.1 Pro leads with 67.4% against 61.4%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.1 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0093 per sample against $0.035. Claude Fable 5.1 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Gemini 3.1 Pro is faster. Across Roboflow's Vision Evals it averaged 7.8s per inference against 8.3s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.