Claude Haiku 4.5 vs Qwen3.8 27B
Compare Claude Haiku 4.5 and Qwen3.8 27B side-by-side.
Compare Claude Haiku 4.5 vs Qwen3.8 27B live
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Models in this comparison
Claude Haiku 4.5 vs Qwen3.8 27B Comparison Table
Evals updated August 14, 2026Pricing updated August 15, 2026
| Property | Claude Haiku 4.5 | Qwen3.8 27B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Aug 2026 |
| Context Window | 200K | 262K |
| Parameters | 27.78B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $1.00 | $0.450 |
| Output $/1M | $5.00 | $3.20 |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Object Detection | 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 | 61.2% |
| Avg cost / sample | – | $0.0018 |
| Avg speed / sample | – | 7.33s |
| By task | ||
| Object Detection | – | 54.5% $0.0036 |
| Counting | – | 41.9% $0.0005 |
| Identification | – | 78.1% $0.0005 |
| OCR | – | 81.4% $0.0019 |
| Data Extraction | – | 79.4% $0.0005 |
| Reasoning (low) | – | 31.8% $0.0005 |
| Reasoning (high) | – | 62.3% $0.0087 |
Claude Haiku 4.5 vs Qwen3.8 27B: Overview
Claude Haiku 4.5 is Anthropic’s lightweight model in the Claude 4.5 series, released in October 2025 under a proprietary license. Designed for speed and cost efficiency, it delivers near-frontier performance while maintaining Anthropic’s AI Safety Level 2 standard. Haiku 4.5 supports both text and multimodal (text and image) inputs, integrates tool use and extended reasoning, and features a 200,000 token context window, making it adept at handling long or complex workflows. Though the parameter count remains undisclosed, it achieves about 73.3% on SWE-bench Verified, reflecting strong coding and reasoning ability. Haiku 4.5 is ideal for developers and researchers seeking rapid, cost-effective model calls for analysis, coding, or multimodal understanding.
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. Qwen reports improvements over Qwen3.6-27B on agentic and multimodal evaluations including Terminal-Bench 2.1, OSWorld-Verified, and SWE-bench Multimodal, with additional results on MathVision, CharXiv, and an internal Vision2Web suite.
Frequently Asked Questions
Claude Haiku 4.5 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.
Claude Haiku 4.5 is released under Proprietary, while Qwen3.8 27B uses Apache 2.0. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.