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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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AnthropicClaude Opus 4

Claude Opus 4 is deprecated and can no longer be run. Details and evals are still available on its model page.

MistralMistral Small 3.1 24B
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Models in this comparison

Anthropic

Claude Opus 4 vs Mistral Small 3.1 24B: Overview

Claude Opus 4

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

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

PropertyClaude Opus 4Mistral Small 3.1 24B
OrganizationAnthropicMistral
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateMay 2025Mar 2025
Context Window200K128K
Parameters24B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$15.00$0.351
Output $/1M$75.00$0.555
Vision Tasks
CaptioningDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
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 Time19.74s
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)