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Mistral Small 3.1 24B Base vs Qwen2.5 7B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Mistral Small 3.1 24B Base offers 116.7K more tokens in context window than Qwen2.5 7B Instruct. Both models have similar pricing. Mistral Small 3.1 24B Base supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small 3.1 24B Base represents an updated iteration of the 24B foundation model, developed with architectural refinements and improved training. Built to provide enhanced base capabilities for fine-tuning, it incorporates learnings from previous versions for better downstream performance.
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Alibaba Cloud / Qwen Team
Qwen 2.5 7B was created as an efficient instruction-tuned model, designed to provide capable performance with just 7 billion parameters. Built for applications requiring reliable language understanding with minimal computational overhead, it serves as an accessible entry point to the Qwen 2.5 family.
5 months newer
Qwen2.5 7B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
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Pricing Comparison
Cost per million tokens (USD)
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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30($0.20 cheaper)
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Qwen2.5 7B Instruct
Input:$0.30
Output:
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:46.8%(+0.4%)
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Qwen2.5 7B Instruct
Average Score:46.3%
Provider Availability & Performance
Available providers and their performance metrics
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Mistral Small 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Qwen2.5 7B Instruct
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Mistral Small 3.1 24B Base
Avg Score:46.8%(+0.4%)
Providers:1
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Qwen2.5 7B Instruct
Avg Score:46.3%
Providers:1