Claude Sonnet 5.5 vs Gemini 3.7 Flash
Gemini 3.7 Flash and Claude Sonnet 5.5 score 80.1% vs 77.6% averaged across five Vision Evals tasks (#9 and #13 of 68 models), so Gemini 3.7 Flash leads overall.
- Gemini 3.7 Flash wins 3 of the 5 tasks, with its widest lead on OCR (73.9% vs 66.3%).
- Gemini 3.7 Flash is about half the cost: $0.0033 vs $0.0073 overall average cost per sample.
- Claude Sonnet 5.5 is faster: 8.3s vs 11.0s per sample.
Roboflow Vision Evals. Full breakdown below.
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Claude Sonnet 5.5 vs Gemini 3.7 Flash on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Sonnet 5.5 vs Gemini 3.7 Flash Comparison Table
Evals updated November 10, 2026Pricing updated November 12, 2026
| Property | Claude Sonnet 5.5 | 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 | Unknown | Undisclosed |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $0.750 |
| Output $/1M | $10.00 | $3.75 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 77.6% | 80.1% |
| Avg cost / sample | $0.0073 | $0.0033 |
| Avg speed / sample | 8.33s | 11.04s |
| By task | ||
| Object Detection (low) | 74.3% ±0.9, Mean of 3 runs, range 73.5 to 75.3 | 70.5% ±1.1, Mean of 3 runs, range 69.4 to 71.5 |
| Object Detection (high) | 76.8% ±0.4, Mean of 3 runs, range 76.5 to 77.3 | 74.3% ±0.8, Mean of 3 runs, range 73.3 to 75.0 |
| Counting (low) | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 | 78.4% ±1.4, Mean of 3 runs, range 77.0 to 79.7 |
| Counting (high) | 82.9% ±1.4, Mean of 3 runs, range 81.1 to 83.8 | 79.3% ±2.0, Mean of 3 runs, range 77.0 to 81.1 |
| Identification (low) | 91.7% ±3.1, Mean of 3 runs, range 87.5 to 93.8 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| Identification (high) | 90.6% ±0.0, Mean of 3 runs, range 90.6 to 90.6 | 96.9% ±0.0, Mean of 3 runs, range 96.9 to 96.9 |
| OCR (low) | 66.3% | 73.9% |
| by category |
|
|
| OCR (high) | – | 78.8% |
| by category |
| |
| Reasoning (low) | 76.4% ±0.7, Mean of 3 runs, range 75.5 to 76.8 | 80.8% ±2.0, Mean of 3 runs, range 78.8 to 82.8 |
| Reasoning (high) | 83.9% ±1.7, Mean of 3 runs, range 82.1 to 85.4 | 81.9% ±1.3, Mean of 3 runs, range 80.1 to 82.8 |
Claude Sonnet 5.5 vs Gemini 3.7 Flash: Overview
Claude Sonnet 5.5 is a proprietary multimodal language model from Anthropic and the second release in the Claude 5.5 family, following Claude Opus 5.5. It accepts interleaved text and image input and returns text, operating with a 1M token context window and a maximum output of 128K tokens per request. The model uses adaptive thinking by default, allocating variable reasoning effort per request rather than exposing a manual extended thinking toggle, and its training data cutoff is June 2026. Anthropic positions it as a faster, lower cost complement to Opus 5.5 for well scoped everyday tasks, bug fixing, and producing documents, slides, and spreadsheets.
Anthropic describes it as the first Sonnet model able to complete Pokemon Red from screenshots alone, and it generates output more than 30% faster than Sonnet 5 while using fewer tokens for equivalent work.
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 3 of the five vision tasks and averages 80.1% (#9 of 68) against 77.6% (#13 of 68) for Claude Sonnet 5.5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
No. On the Vision Evals OCR benchmark at low effort, Gemini 3.7 Flash leads with 73.9% against 66.3%. 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 $0.0033 per sample against $0.0073. Claude Sonnet 5.5 is priced at $2.00 per 1M input tokens and $10.00 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 Sonnet 5.5 is faster. Across Roboflow's Vision Evals it averaged 8.3s per inference against 11.0s. 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 OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.