Claude Haiku 4.5 vs GPT-4o mini
Compare Claude Haiku 4.5 and GPT-4o 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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GPT-4o mini is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
Claude Haiku 4.5 vs GPT-4o 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-4o mini, launched by OpenAI in July 2024, is a lightweight, cost-efficient variant of GPT-4o designed for developers who need strong multimodal reasoning at scale. It supports text and vision inputs (with audio/video support planned) and offers a 128,000-token input context window with outputs up to ~16,000 tokens. Like GPT-4o, it has a knowledge cutoff of October 2023 and integrates the same safety mitigations against misuse and prompt attacks.
GPT-4o mini is significantly cheaper than full GPT-4o while outperforming older models such as GPT-3.5 Turbo. It achieves around 82% on MMLU, reflecting solid reasoning, math, and coding capabilities despite its efficiency focus. The model replaced GPT-3.5 Turbo as the default in ChatGPT for many users, making it widely accessible for everyday conversational AI, educational tools, content generation, and scalable multimodal applications where affordability and speed are priorities.
Claude Haiku 4.5 vs GPT-4o mini Comparison Table
| Property | Claude Haiku 4.5 | GPT-4o mini |
|---|---|---|
| Organization | Anthropic | OpenAI |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Oct 2025 | Jul 2024 |
| Context Window | 200K | 128K |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $1.00 | $0.150 |
| Output $/1M | $5.00 | $0.600 |
| Vision Tasks | ||
| Captioning | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 58.21% | |
| Avg Response Time | 3.15s | |
| Median input tokensincl. image tokens | 2.2K | |
| Median output tokens | 174 | |
| Est. cost / taskon this benchmark | $0.0030 | |
| Defect Detection | 80%(12/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 0%(0/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 52.6%(10/19) | |
| OCR | ||
| Overall Score | 61.57% | |
| Avg Response Time | 2.13s | |
| Median input tokensincl. image tokens | 735 | |
| Median output tokens | 101 | |
| Est. cost / taskon this benchmark | $0.0012 | |
| Focused Scene OCR | 61.6%(61/99) | |
| Handwritten Math | 20%(2/10) | |
| License Plate Recognition | 66.7%(20/30) | |
| Text Recognition | 63.3%(19/30) | |
| VQA & Extraction | 65%(39/60) | |
Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology