Claude Opus 4 vs Mistral Small 3.1 24B
Compare Claude Opus 4 and Mistral Small 3.1 24B side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.
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Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.
Models in this comparison
Claude Opus 4 vs Mistral Small 3.1 24B: Overview
Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.
Positioned at the high end of Anthropic’s offerings, Opus 4 achieves state-of-the-art results on coding benchmarks like SWE-Bench (72.5%) and Terminal-Bench (43.2%). It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.
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 vs Mistral Small 3.1 24B Comparison Table
| Property | Claude Opus 4 | Mistral Small 3.1 24B |
|---|---|---|
| Organization | Anthropic | Mistral |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | May 2025 | Mar 2025 |
| Context Window | 200K | 128K |
| Parameters | 24B | |
| License | Proprietary | Apache 2.0 |
| Pricing per 1M tokens | ||
| Input $/1M | $15.00 | $0.351 |
| Output $/1M | $75.00 | $0.555 |
| Vision Tasks | ||
| Captioning | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Classification | ||
| Object Detection | ||
| Model Features | ||
| Multimodal Vision | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
Vision Evalspass/fail results · 67 prompts Score key:≥75%40–74%<40% | ||
| Visual Understanding | ||
| Overall Score | 56.72% | |
| Avg Response Time | 19.74s | |
| Defect Detection | 66.7%(10/15) | |
| Document Understanding | 88.9%(8/9) | |
| Object Counting | 0%(0/10) | |
| Object Understanding | 64.3%(9/14) | |
| Spatial Understanding | 57.9%(11/19) | |