Claude Haiku 4.5 vs Qwen3.5 397B A17B
We don't benchmark Claude Haiku 4.5 or Qwen3.5 397B A17B on Vision Evals. Claude Haiku 4.5 is proprietary under Proprietary: commercial use per vendor terms. Qwen3.5 397B A17B is open-weight under Apache 2.0: free for commercial use. Qwen3.5 397B A17B is cheaper per token ($0.60/M vs $1/M input). Test them side by side on your own images below.
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Claude Haiku 4.5 vs Qwen3.5 397B A17B Comparison Table
Pricing updated November 11, 2026
| Property | Claude Haiku 4.5 | Qwen3.5 397B A17B |
|---|---|---|
| Organization | Anthropic | Qwen |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Feb 2026 |
| Context Window | 200K | 262K |
| Parameters | Unknown | 397B |
| License | Proprietary | Apache 2.0 |
| Commercial use | commercial use per vendor terms | free for commercial use |
| Pricing per 1M tokens | ||
| Input $/1M | $1.00 | $0.600 |
| Output $/1M | $5.00 | $3.60 |
| Vision Tasks | ||
| Classification | Demo | Supported |
| Object Detection | Demo | Supported |
| Model Features | ||
Both support 3 more features | ||
Claude Haiku 4.5 vs Qwen3.5 397B A17B: 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. Haiku 4.5 is ideal for developers and researchers seeking rapid, cost-effective model calls for analysis, coding, or multimodal understanding.
Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.
As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.