Claude Sonnet 4.6 vs Qwen3.8 27B
Qwen3.8 27B: 69.5% average across four Vision Evals tasks (#28 of 69 models). We have not run Claude Sonnet 4.6 through Roboflow's Vision Evals, so there is no head-to-head score. Run both on your own image below.
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Claude Sonnet 4.6 vs Qwen3.8 27B Comparison Table
Evals updated November 12, 2026Pricing updated November 13, 2026
| Property | Claude Sonnet 4.6 | Qwen3.8 27B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Aug 2026 |
| Context Window | 1.0M | 262K |
| Parameters | Unknown | 27.78B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $3.00 | $0.150 |
| Output $/1M | $15.00 | $1.88 |
| Vision Tasks | ||
| Model Features | ||
Both support 3 more features | ||
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | Not evaluated | 69.5%* |
| Quantizationsself-hosted | ||
| Avg cost / sample | – | $0.0009 |
| Avg speed / sample | – | 17.99s |
| By task | ||
| Object Detection (low) | – | 65.7% ±1.0, Mean of 3 runs, range 64.6 to 66.5 |
| Object Detection (high) | – | 66.1% ±1.4, Mean of 3 runs, range 64.9 to 67.8 |
| Counting (low) | – | 64.9% ±4.1, Mean of 3 runs, range 60.8 to 68.9 |
| Counting (high) | – | 68.0% ±2.0, Mean of 3 runs, range 66.2 to 70.3 |
| Identification (low) | – | 85.4% ±4.7, Mean of 3 runs, range 81.3 to 90.6 |
| Identification (high) | – | 87.5% ±3.1, Mean of 3 runs, range 84.4 to 90.6 |
| OCR | – | – |
| by category | ||
| Reasoning (low) | – | 62.0% ±2.0, Mean of 3 runs, range 60.3 to 64.2 |
| Reasoning (high) | – | 66.0% ±0.7, Mean of 3 runs, range 65.6 to 66.9 |
Claude Sonnet 4.6 vs Qwen3.8 27B: 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.
Qwen3.8-27B is a dense vision-language model of roughly 27.78 billion parameters from Alibaba's Qwen team, built on the architectural foundation established by the Qwen3.5 generation. It takes interleaved text, image, and video input through an integrated vision encoder and produces text, covering document and chart understanding, visual question answering, front-end code generation from visual references, and agentic computer-use workflows. The decoder is a hybrid stack of 64 layers that repeats a pattern of three Gated DeltaNet linear-attention blocks, each followed by a feed-forward block, then one grouped-query full-attention block, so only a quarter of the layers maintain a conventional key-value cache. Native context length is 262,144 tokens.
Post-training targets long-horizon agentic work, and the model exposes per-request thinking control that lets callers switch reasoning traces on or off and choose a reasoning effort level. Multi-token prediction weights are trained alongside the main network for speculative decoding.
Frequently Asked Questions
Claude Sonnet 4.6 is released under Proprietary, while Qwen3.8 27B uses Apache 2.0. In practice: Claude Sonnet 4.6: commercial use per vendor terms; Qwen3.8 27B: free for commercial use. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
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.