Claude Fable 5.2 vs Gemini 3.5 Flash
Claude Fable 5.2 and Gemini 3.5 Flash score 86.5% vs 81.8% averaged across five Vision Evals tasks (#2 and #6 of 67 models), so Claude Fable 5.2 leads overall.
- Claude Fable 5.2 wins 4 of the 5 tasks, with its widest lead on object detection (81.6% vs 70.6%).
- Gemini 3.5 Flash is about half the cost: $0.012 vs $0.031 overall average cost per sample.
- Claude Fable 5.2 is faster: 9.3s vs 11.5s per sample.
Roboflow Vision Evals. Full breakdown below.
Compare Claude Fable 5.2 vs Gemini 3.5 Flash 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 Gemini 3.5 Flash on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Fable 5.2 vs Gemini 3.5 Flash Comparison Table
Evals updated November 10, 2026Pricing updated November 10, 2026
| Property | Claude Fable 5.2 | Gemini 3.5 Flash |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Nov 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 | $8.00 | $1.50 |
| Output $/1M | $40.00 | $9.00 |
| 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% | 81.8% |
| Avg cost / sample | $0.031 | $0.012 |
| Avg speed / sample | 9.33s | 11.52s |
| By task | ||
| Object Detection (low) | 81.6% ±0.3, Mean of 3 runs, range 81.2 to 81.9 | 70.6% ±2.0, Mean of 3 runs, range 68.7 to 72.6 |
| Object Detection (high) | 83.3% ±0.5, Mean of 3 runs, range 82.8 to 83.7 | 69.8% ±1.8, Mean of 3 runs, range 67.5 to 71.1 |
| Counting (low) | 86.5% ±0.0, Mean of 3 runs, range 86.5 to 86.5 | 80.6% ±0.7, Mean of 3 runs, range 79.7 to 81.1 |
| Counting (high) | 92.8% ±1.4, Mean of 3 runs, range 91.9 to 94.6 | 82.4% ±0.0, Mean of 3 runs, range 82.4 to 82.4 |
| Identification (low) | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 | 99.0% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| Identification (high) | 94.8% ±1.6, Mean of 3 runs, range 93.8 to 96.9 | 97.9% ±1.6, Mean of 3 runs, range 96.9 to 100.0 |
| OCR (low) | 79.5% | 76.7% |
| by category |
|
|
| OCR (high) | 84.8% | 75.5% |
| by category |
|
|
| Reasoning (low) | 88.1% ±1.3, Mean of 3 runs, range 86.8 to 89.4 | 82.1% ±2.0, Mean of 3 runs, range 80.1 to 84.1 |
| Reasoning (high) | 92.0% ±1.0, Mean of 3 runs, range 91.4 to 93.4 | 81.0% ±1.7, Mean of 3 runs, range 79.5 to 82.8 |
Claude Fable 5.2 vs Gemini 3.5 Flash: 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.
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, Claude Fable 5.2 performed better. It scores higher on 4 of the five vision tasks and averages 86.5% (#2 of 67) against 81.8% (#6 of 67) for Gemini 3.5 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Object Detection benchmark at low effort, Claude Fable 5.2 leads with 81.6% against 70.6%. 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 $0.031. Claude Fable 5.2 is priced at $8.00 per 1M input tokens and $40.00 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 5.2 is faster. Across Roboflow's Vision Evals it averaged 9.3s per inference against 11.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.