Claude Opus 4.1 vs Mistral Small 3.1 24B
Compare Claude Opus 4.1 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 4.1 vs Mistral Small 3.1 24B: Overview
Claude 4.1 Opus, released by Anthropic in August 2025, is the upgraded flagship of the Claude 4 family, building on Opus 4 with stronger reasoning and agentic capabilities. Like its predecessor, it is multimodal and optimized for text, code, and tool use, with support for large context windows suited to multi-file codebases, technical workflows, and long-horizon problem solving.
On benchmarks, Opus 4.1 improves coding performance, reaching ~74.5% on SWE-Bench Verified compared to Opus 4’s ~72.5%. It demonstrates more precise debugging, refactoring, and orchestration of agentic tasks while maintaining similar safety and alignment safeguards. It is best suited for enterprise-scale software development, research automation, and advanced reasoning workflows where reliability and depth of analysis are critical.
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 4.1 vs Mistral Small 3.1 24B Comparison Table
| Property | Claude Opus 4.1 | Mistral Small 3.1 24B |
|---|---|---|
| Organization | Anthropic | Mistral |
| Category | closed | open |
| Modality | multimodal | multimodal |
| Release Date | Aug 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 | 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 | 59.7% | |
| Avg Response Time | 7.09s | |
| Median input tokensincl. image tokens | 2.0K | |
| Median output tokens | 140 | |
| Est. cost / taskon this benchmark | $0.040 | |
| Defect Detection | 73.3%(11/15) | |
| Document Understanding | 88.9%(8/9) | |
| Object Counting | 0%(0/10) | |
| Object Understanding | 64.3%(9/14) | |
| Spatial Understanding | 63.2%(12/19) | |
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