Claude Fable 5.1 vs Gemini 3.7 Flash
Compare Claude Fable 5.1 and Gemini 3.7 Flash 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 3.7 Flash on Vision Evals
Gemini 3.7 Flash scores higher on 4 of the six Vision Evals tasks.
The widest gap is Object Detection, where Gemini 3.7 Flash leads 70.5% to 61.4%.
Overall, Claude Fable 5.1 averages 81.3% (#7 of 36) against 85.2% (#2 of 36) for Gemini 3.7 Flash.
Gemini 3.7 Flash is cheaper ($0.0031 vs $0.035 per sample), while Claude Fable 5.1 is faster (8.3s vs 16.5s per sample).
Claude Fable 5.1 vs Gemini 3.7 Flash Comparison Table
Evals updated September 2, 2026Pricing updated September 2, 2026
| Property | Claude Fable 5.1 | Gemini 3.7 Flash |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Aug 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Undisclosed | |
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $10.00 | $0.750 |
| Output $/1M | $50.00 | $3.75 |
| 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% | 85.2% |
| Avg cost / sample | $0.035 | $0.0031 |
| Avg speed / sample | 8.28s | 16.50s |
| By task | ||
| Object Detection (low) | 61.4% ±0.5, Mean of 3 runs, range 61.0 to 62.0 | 70.5% ±1.1, Mean of 3 runs, range 69.4 to 71.5 |
| Object Detection (high) | 65.0% ±0.4, Mean of 3 runs, range 64.6 to 65.3 | 74.3% ±0.8, Mean of 3 runs, range 73.3 to 75.0 |
| Counting (low) | 69.4% ±2.7, Mean of 3 runs, range 66.2 to 71.6 | 78.4% ±1.4, Mean of 3 runs, range 77.0 to 79.7 |
| Counting (high) | 73.0% ±4.7, Mean of 3 runs, range 67.6 to 77.0 | 79.3% ±2.0, Mean of 3 runs, range 77.0 to 81.1 |
| Identification (low) | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | 96.9% ±3.1, Mean of 3 runs, range 93.8 to 100.0 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 94.0% ±0.4, Mean of 3 runs, range 93.6 to 94.4 | 88.2% ±1.6, Mean of 3 runs, range 86.9 to 90.0 |
| OCR (high) | 93.6% ±0.2, Mean of 3 runs, range 93.5 to 93.9 | 89.0% ±0.8, Mean of 3 runs, range 88.3 to 89.9 |
| Data Extraction (low) | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | 96.2% ±0.5, Mean of 3 runs, range 95.9 to 96.9 |
| Data Extraction (high) | 93.5% ±0.5, Mean of 3 runs, range 92.8 to 93.8 | 95.9% ±0.0, Mean of 3 runs, range 95.9 to 95.9 |
| Reasoning (low) | 72.0% ±1.3, Mean of 3 runs, range 70.9 to 73.5 | 80.8% ±2.0, Mean of 3 runs, range 78.8 to 82.8 |
| Reasoning (high) | 73.1% ±2.0, Mean of 3 runs, range 71.5 to 75.5 | 81.9% ±1.3, Mean of 3 runs, range 80.1 to 82.8 |
Claude Fable 5.1 vs Gemini 3.7 Flash: 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 3.7 Flash is a proprietary multimodal model from Google, positioned in the Flash branch of the Gemini 3 series that trades some of the capacity of the larger Pro models for lower latency and lower cost per token. It accepts interleaved text and image input alongside other modalities handled by the Gemini family and returns text, and it continues the series pattern of exposing a configurable thinking budget so that reasoning effort can be scaled up for harder problems or reduced for high throughput extraction, routing and classification work. The model is announced roughly three weeks after Gemini 3.6 Flash, part of an unusually fast iteration cadence within the Flash line.
Google reports gains concentrated in agentic coding and front end generation, citing a WebDev Arena Elo of 1588 for this release compared with 1538 for the preceding Flash model, and describes it as producing more functional layouts and more feature complete applications in fewer prompts. Weights are not published and the architecture, parameter count and training corpus are undisclosed, consistent with prior Gemini releases. Visual capability follows the Flash lineage, covering image and document understanding, chart and diagram interpretation, text recognition in images, and general visual question answering.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.7 Flash performed better. It scores higher on 4 of the six vision tasks and averages 85.2% (#2 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 3.7 Flash leads with 70.5% against 61.4%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.7 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0031 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 3.7 Flash is priced at $0.75 per 1M input tokens and $3.75 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Fable 5.1 is faster. Across Roboflow's Vision Evals it averaged 8.3s per inference against 16.5s. 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.