Claude Sonnet 4.6 vs Claude Sonnet 5.5
Compare Claude Sonnet 4.6 and Claude Sonnet 5.5 side-by-side.
Compare Claude Sonnet 4.6 vs Claude Sonnet 5.5 live
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Models in this comparison
Claude Sonnet 4.6 vs Claude Sonnet 5.5 Comparison Table
Evals updated September 28, 2026Pricing updated September 28, 2026
| Property | Claude Sonnet 4.6 | Claude Sonnet 5.5 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Sep 2026 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | |
| Output $/1M | $15.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 83.8% |
| Avg cost / sample | – | $0.0065 |
| Avg speed / sample | – | 10.78s |
| By task | ||
| Object Detection (low) | – | 74.3% ±0.9, Mean of 3 runs, range 73.5 to 75.3 |
| Object Detection (high) | – | 76.8% ±0.4, Mean of 3 runs, range 76.5 to 77.3 |
| Counting (low) | – | 79.3% ±0.7, Mean of 3 runs, range 78.4 to 79.7 |
| Counting (high) | – | 82.9% ±1.4, Mean of 3 runs, range 81.1 to 83.8 |
| Identification (low) | – | 91.7% ±3.1, Mean of 3 runs, range 87.5 to 93.8 |
| Identification (high) | – | 90.6% ±0.0, Mean of 3 runs, range 90.6 to 90.6 |
| OCR (low) | – | 90.6% ±0.9, Mean of 3 runs, range 90.0 to 91.7 |
| OCR (high) | – | 90.9% ±1.5, Mean of 3 runs, range 89.2 to 92.3 |
| Data Extraction (low) | – | 90.7% ±1.5, Mean of 3 runs, range 89.7 to 92.8 |
| Data Extraction (high) | – | 93.1% ±0.5, Mean of 3 runs, range 92.8 to 93.8 |
| Reasoning (low) | – | 76.4% ±0.7, Mean of 3 runs, range 75.5 to 76.8 |
| Reasoning (high) | – | 83.9% ±1.7, Mean of 3 runs, range 82.1 to 85.4 |
Claude Sonnet 4.6 vs Claude Sonnet 5.5: Overview
Claude Sonnet 4.6 is Anthropic's mid-tier large language model, released February 17, 2026, designed to balance performance, cost, and versatility for professional and developer use. It supports text and vision-based tasks with advanced reasoning, agentic capabilities, and Adaptive Thinking — a mode where the model dynamically scales its internal reasoning depth. A beta context window of up to 1,000,000 tokens (200K standard) enables processing of entire codebases or document collections in a single request. Parameters are undisclosed.
Optimized for coding, computer use, long-context reasoning, agent planning, and knowledge work, Sonnet 4.6 delivers a full generational upgrade over Sonnet 4.5 and approaches Opus 4.5-level performance across many benchmarks at a fraction of the cost. It is the default model on Claude.ai, Claude Cowork, and is available via API and major cloud platforms — making it well suited for production workloads requiring strong reasoning without flagship pricing.
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.
On visual and agentic evaluations reported at launch, Sonnet 5.5 scores 61.6% on Chartography, a chart recognition test, compared with 15.6% for Claude Sonnet 5, and 80.1% on OSWorld 2.1, a computer use benchmark measuring screenshot driven control of a desktop environment, compared with 57.0% for Sonnet 5. It reports 70.6% on Terminal-Bench 4.0 for agentic coding. 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.