Claude Fable 5 vs Gemini 3.5 Flash
Gemini 3.5 Flash and Claude Fable 5 score 81.8% vs 71.7% averaged across five Vision Evals tasks (#5 and #20 of 65 models), so Gemini 3.5 Flash leads overall.
- Gemini 3.5 Flash wins 4 of the 5 tasks, with its widest lead on counting (80.6% vs 63.5%).
- Gemini 3.5 Flash is about a third of the cost: $0.012 vs $0.039 overall average cost per sample.
- Claude Fable 5 is faster: 9.5s vs 11.5s per sample.
Roboflow Vision Evals. Full breakdown below.
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Claude Fable 5 vs Gemini 3.5 Flash on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Fable 5 vs Gemini 3.5 Flash Comparison Table
Evals updated October 26, 2026Pricing updated November 5, 2026
| Property | Claude Fable 5 | Gemini 3.5 Flash |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Jun 2026 | May 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $10.00 | $1.50 |
| Output $/1M | $50.00 | $9.00 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 71.7% | 81.8% |
| Avg cost / sample | $0.039 | $0.012 |
| Avg speed / sample | 9.54s | 11.52s |
| By task | ||
| Object Detection (low) | 56.4% | 70.6% ±2.0, Mean of 3 runs, range 68.7 to 72.6 |
| Object Detection (high) | – | 69.8% ±1.8, Mean of 3 runs, range 67.5 to 71.1 |
| Counting (low) | 63.5% | 80.6% ±0.7, Mean of 3 runs, range 79.7 to 81.1 |
| Counting (high) | – | 82.4% ±0.0, Mean of 3 runs, range 82.4 to 82.4 |
| Identification (low) | 100.0% | 99.0% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| Identification (high) | – | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| OCR (low) | 72.3% | 76.7% |
| by category |
|
|
| OCR (high) | 74.2% | 75.5% |
| by category |
|
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| Reasoning (low) | 66.2% | 82.1% ±2.0, Mean of 3 runs, range 80.1 to 84.1 |
| Reasoning (high) | 66.2% | 81.0% ±1.7, Mean of 3 runs, range 79.5 to 82.8 |
Claude Fable 5 vs Gemini 3.5 Flash: Overview
Claude Fable 5 is Anthropic's first generally available Mythos-class large language model, released on June 9, 2026. It is built for long-horizon, asynchronous, and agentic tasks that prior Claude generations could not sustain, including multi-day autonomous coding sessions, complex knowledge work, and document-heavy analysis. The model supports a 1 million token context window with up to 128,000 output tokens per request and uses adaptive thinking as its sole reasoning mode, where the effort level is adjustable but raw chain-of-thought is never returned. Vision capabilities allow the model to parse diagrams, charts, and tables embedded in files and PDFs, and to use visual feedback to evaluate its own coding outputs against design goals.
Claude Fable 5 shares the same underlying model weights as Claude Mythos 5, but is deployed with safety classifiers that automatically reroute queries in high-risk domains — including cybersecurity, biology, and chemistry — to Claude Opus 4.8. These classifiers trigger in fewer than 5% of sessions on average. As a designated Covered Model, all traffic is subject to mandatory 30-day data retention to support safety monitoring. The model is available via the Claude API, Amazon Bedrock, Vertex AI, and Microsoft Foundry. Anthropic has not publicly disclosed parameter count, architecture details, or training data composition for this model.
Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.
Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.
Frequently Asked Questions
On Roboflow's Vision Evals, Gemini 3.5 Flash performed better. It scores higher on 4 of the five vision tasks and averages 81.8% (#5 of 65) against 71.7% (#20 of 65) for Claude Fable 5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals Counting benchmark at low effort, Gemini 3.5 Flash leads with 80.6% against 63.5%. This is the widest gap between the two models across the benchmark's tasks.
Gemini 3.5 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.012 per sample against $0.039. Claude Fable 5 is priced at $10.00 per 1M input tokens and $50.00 per 1M output; Gemini 3.5 Flash is priced at $1.50 per 1M input tokens and $9.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.
Claude Fable 5 is faster. Across Roboflow's Vision Evals it averaged 9.5s per inference against 11.5s. 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 image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.