Claude Haiku 4.5 vs GPT-5 Mini
Compare Claude Haiku 4.5 and GPT-5 Mini side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, OCR, Classification, and Object Detection.
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Claude Haiku 4.5 vs GPT-5 Mini Comparison Table
Evals updated August 20, 2026Pricing updated August 24, 2026
| Property | Claude Haiku 4.5 | GPT-5 Mini |
|---|---|---|
| Organization | Anthropic | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Aug 2025 |
| Context Window | 200K | 400K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.00 | $0.250 |
| Output $/1M | $5.00 | $2.00 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Chart Question Answering | ||
| Classification | Demo | Demo |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Claude Haiku 4.5 vs GPT-5 Mini: 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.
GPT-5 Mini, released by OpenAI on August 7, 2025, is a mid-tier variant of the GPT-5 family that balances cost, speed, and capability. It is multimodal, supporting both text and image inputs, and offers a substantial input context window of ~400,000 tokens with output lengths up to ~128,000 tokens. While less powerful than the full GPT-5, it inherits its safety tuning, instruction-following improvements, and multimodal reasoning, making it a practical choice for developers who need large context handling without the expense of premium models.
GPT-5 Mini is optimized for affordability while retaining strong reasoning performance. Benchmarks show it outperforming earlier models such as GPT-4o on many multimodal and medical VQA tasks, though it lags behind GPT-5 on the most complex problems. Ideal use cases include prototyping, scalable content generation, document analysis, and mid-range reasoning tasks where efficiency and context capacity matter more than top-tier accuracy.