Claude 3.5 Haiku vs Claude Opus 4.7
Compare Claude 3.5 Haiku and Claude Opus 4.7 side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Claude 3.5 Haiku is deprecated and can no longer be run. Details and evals are still available on its model page.
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Claude 3.5 Haiku vs Claude Opus 4.7 Comparison Table
Evals updated August 6, 2026Pricing updated August 7, 2026
| Property | Claude 3.5 Haiku | Claude Opus 4.7 |
|---|---|---|
| Organization | Anthropic | Anthropic |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Oct 2024 | Apr 2026 |
| Context Window | 200K | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | |
| Output $/1M | $25.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | Demo | |
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Claude 3.5 Haiku vs Claude Opus 4.7: Overview
Claude 3.5 Haiku, released by Anthropic in October 2024, is the fastest member of the Claude 3.5 family, optimized for low-latency, high-throughput applications. It is a multimodal model that handles both text and image inputs and supports a large ~200,000-token context window. Haiku is designed to balance efficiency with intelligence, outperforming even Claude 3 Opus on several reasoning benchmarks while maintaining its hallmark speed.
Typical applications include real-time chatbots, code completion, large-scale data extraction, and content moderation—scenarios where rapid response and scalability are essential.
Claude Opus 4.7 is a proprietary multimodal language model developed by Anthropic, released on April 16, 2026. It is designed for agentic coding, long-horizon task execution, and enterprise knowledge work. The model supports text and vision inputs and operates with a context window of up to 1,000,000 tokens. It introduces adaptive thinking, which dynamically allocates reasoning based on task complexity, along with configurable effort controls including a new xhigh setting that sits between the existing high and max levels. It achieves 87.6% on SWE-bench Verified and 78.0% on OSWorld-Verified, reflecting strong performance on autonomous software engineering and computer use tasks respectively.
Compared to Claude Opus 4.6, version 4.7 shows improved instruction following and higher reliability in extended agentic tasks. Vision capabilities now support high-resolution inputs up to 2,576px on the long edge (~3.75 megapixels), more than three times the resolution of prior Claude models, enabling finer interpretation of dense diagrams, UI screenshots, and document layouts. These improvements, combined with self-verification on long-running tasks and a new task budget system for controlling agentic loops, make it well-suited for complex software engineering, technical analysis, and multimodal vision workflows.