Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Mistral AI

Devstral Medium

Mistral AI

Devstral Medium is a language model developed by Mistral AI. It achieves strong performance with an average score of 61.6% across 1 benchmarks. Notable strengths include SWE-Bench Verified (61.6%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2025, it represents Mistral AI's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

Qwen2.5 VL 32B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 63.6% across 28 benchmarks. It excels particularly in DocVQA (94.8%), Android Control Low_EM (93.3%), HumanEval (91.5%). The model shows particular specialization in code tasks with an average performance of 87.8%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen2.5 VL 32B Instruct

Alibaba

2025-02-28

Mistral AI

Devstral Medium

Mistral AI

2025-07-10

4 months newer

Performance Metrics

Context window and performance specifications

Mistral AI

Devstral Medium

Larger context
Max Context:256.0K
Alibaba

Qwen2.5 VL 32B Instruct

Max Context:-
Parameters:33.5B

Performance comparison across key benchmark categories

Mistral AI

Devstral Medium

general
+1.5%
61.6%
Alibaba

Qwen2.5 VL 32B Instruct

general
60.1%

Provider Availability & Performance

Available providers and their performance metrics

Mistral AI

Devstral Medium

1 providers

Mistral AI

Throughput: 137.1 tok/s
Latency: 0.23ms
Alibaba

Qwen2.5 VL 32B Instruct

0 providers
Mistral AI

Devstral Medium

Avg Score:0.0%
Providers:1
Alibaba

Qwen2.5 VL 32B Instruct

Avg Score:0.0%
Providers:0