Claude Opus 4.6 vs Mistral Small 3.1 24B
Compare Claude Opus 4.6 and Mistral Small 3.1 24B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.
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Claude Opus 4.6 vs Mistral Small 3.1 24B: Overview
Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.
As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.
Mistral Small 3.1 24B, released on March 17, 2025, is an open-weight multimodal model from Mistral AI, distributed under the Apache-2.0 license. With around 24B parameters and a 128K token context window, it is available in both base and instruction-tuned (“Instruct”) variants. The model introduces vision support alongside text, enabling tasks like multimodal reasoning, captioning, and image-based Q&A.
It is multilingual, supporting many languages, and is optimized for fast responses, function calling, structured dialogue, and long-context reasoning. Despite its size, the model can be run locally in quantized formats, fitting on machines with ~32GB RAM, making it accessible to developers outside large cloud setups. However, the output length is smaller than the 128K input window, meaning long generations may require chaining. In addition, using full vision features or the maximum context window significantly increases compute costs, and performance on highly complex reasoning or enterprise-scale tasks still trails larger proprietary frontier models.
Claude Opus 4.6 vs Mistral Small 3.1 24B Comparison Table
| Property | Claude Opus 4.6 | Mistral Small 3.1 24B |
|---|---|---|
| Organization | Anthropic | Mistral |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Mar 2025 |
| Context Window | 1.0M | 128K |
| Parameters | 24B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | $0.351 |
| Output $/1M | $25.00 | $0.555 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| OCR | Demo | Demo |
| Vision Language | ||
| Visual Question Answering | Demo | Demo |
| Classification | Demo | |
| Object Detection | Demo | |
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Overall Score | 64.18% | |
| Avg Response Time | 23.35s | |
| Median input tokensincl. image tokens | 2.2K | |
| Median output tokens | 130 | |
| Est. cost / taskon this benchmark | $0.014 | |
| Defect Detection | 73.3%(11/15) | |
| Document Understanding | 77.8%(7/9) | |
| Object Counting | 20%(2/10) | |
| Object Understanding | 71.4%(10/14) | |
| Spatial Understanding | 68.4%(13/19) | |
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