Claude Sonnet 5.5 vs GPT-5.6 Sol
Claude Sonnet 5.5 and GPT-5.6 Sol score 77.6% vs 72.4% averaged across five Vision Evals tasks (#14 and #23 of 69 models), so Claude Sonnet 5.5 leads overall.
- Claude Sonnet 5.5 wins all 5 tasks, with its widest lead on reasoning (76.4% vs 66.0%).
- Claude Sonnet 5.5 is about a third of the cost: $0.0073 vs $0.021 overall average cost per sample.
- Claude Sonnet 5.5 is faster: 8.3s vs 12.2s per sample.
Roboflow Vision Evals. Full breakdown below.
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Claude Sonnet 5.5 vs GPT-5.6 Sol on Vision Evals
Roboflow Vision Evals. Full breakdown below.
Claude Sonnet 5.5 vs GPT-5.6 Sol Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | Claude Sonnet 5.5 | GPT-5.6 Sol |
|---|---|---|
| Organization | Anthropic | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Jul 2026 |
| Context Window | 1.0M | 1.5M |
| Parameters | Unknown | Unknown |
| License | Proprietary | Proprietary |
| Commercial use | commercial use per vendor terms | commercial use per vendor terms |
| Pricing per 1M tokens | ||
| Input $/1M | $2.00 | $4.40 |
| Output $/1M | $10.00 | $22.00 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 77.6% | 72.4% |
| Avg cost / sample | $0.0073 | $0.021 |
| Avg speed / sample | 8.33s | 12.16s |
| By task | ||
| Object Detection (low) | 74.3% ±0.9, Mean of 3 runs, range 73.5 to 75.3 | 68.4% ±0.7, Mean of 3 runs, range 67.9 to 69.3 |
| Object Detection (high) | 76.8% ±0.4, Mean of 3 runs, range 76.5 to 77.3 | 68.4% ±0.8, Mean of 3 runs, range 67.7 to 69.3 |
| Counting (low) | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 | 74.3% ±1.4, Mean of 3 runs, range 73.0 to 75.7 |
| Counting (high) | 82.9% ±1.4, Mean of 3 runs, range 81.1 to 83.8 | 76.1% ±2.0, Mean of 3 runs, range 74.3 to 78.4 |
| Identification (low) | 91.7% ±3.1, Mean of 3 runs, range 87.5 to 93.8 | 89.6% ±4.7, Mean of 3 runs, range 84.4 to 93.8 |
| Identification (high) | 90.6% ±0.0, Mean of 3 runs, range 90.6 to 90.6 | 92.7% ±1.6, Mean of 3 runs, range 90.6 to 93.8 |
| OCR (low) | 66.3% | 63.6% |
| by category |
|
|
| OCR (high) | – | 65.3% |
| by category |
| |
| Reasoning (low) | 76.4% ±0.7, Mean of 3 runs, range 75.5 to 76.8 | 66.0% ±2.6, Mean of 3 runs, range 63.6 to 68.9 |
| Reasoning (high) | 83.9% ±1.7, Mean of 3 runs, range 82.1 to 85.4 | 71.7% ±1.3, Mean of 3 runs, range 70.2 to 72.8 |
Claude Sonnet 5.5 vs GPT-5.6 Sol: 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.
GPT-5.6 Sol is the flagship model in OpenAI's GPT-5.6 family, which also includes Terra (a balanced everyday-work tier) and Luna (a fast, cost-efficient tier). Sol is designed for demanding reasoning, long-horizon agentic workflows, software engineering, computer use, scientific research, and cybersecurity tasks. It introduces two new capability modes: a "max" reasoning effort setting that allocates additional compute time for difficult problems, and an "ultra" mode that coordinates multiple subagents in parallel to accelerate complex, multi-step work. The model supports native multimodal input, allowing it to process screenshots, diagrams, charts, documents, and photographs alongside text. A reported context window of approximately 1.5 million tokens enables processing of large codebases, lengthy research documents, and extended agentic sessions.
GPT-5.6 Sol was announced on June 26, 2026, initially in a limited preview for trusted partners, and reached general availability on July 9, 2026. On the Agents' Last Exam benchmark, which evaluates long-running professional workflows across 55 fields, Sol scores 53.6. The model also demonstrates gains in life sciences evaluations, including long-horizon genomics and quantitative biology analyses. OpenAI paired the release with its most extensive safety evaluation to date, combining human red teaming with large-scale automated testing, and classified Sol as High capability in both cybersecurity and biological risk under its Preparedness Framework, though it does not cross the Critical threshold in either category.
Frequently Asked Questions
On Roboflow's Vision Evals, Claude Sonnet 5.5 performed better. It scores higher on all five vision tasks and averages 77.6% (#14 of 69) against 72.4% (#23 of 69) for GPT-5.6 Sol. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.
Yes. On the Vision Evals Reasoning benchmark at low effort, Claude Sonnet 5.5 leads with 76.4% against 66.0%. This is the widest gap between the two models across the benchmark's tasks.
Claude Sonnet 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0073 per sample against $0.021. Claude Sonnet 5.5 is priced at $2.00 per 1M input tokens and $10.00 per 1M output; GPT-5.6 Sol is priced at $4.40 per 1M input tokens and $22.00 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 12.2s. 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.