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Gemini 1.0 Pro vs Mistral Small 3.1 24B Base
Comprehensive side-by-side LLM comparison
Mistral Small 3.1 24B Base leads with 10.1% higher average benchmark score. Mistral Small 3.1 24B Base offers 215.0K more tokens in context window than Gemini 1.0 Pro. Mistral Small 3.1 24B Base is $1.60 cheaper per million tokens. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, Mistral Small 3.1 24B Base is the stronger choice for coding tasks.
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Gemini 1.0 Pro was developed as Google's initial production-ready multimodal model, designed to handle text and provide strong performance across diverse tasks. Built to serve as a versatile foundation for applications requiring reliable language understanding and generation, it introduced the Gemini architecture to developers and enterprises.
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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.
1 year newer
Gemini 1.0 Pro
2024-02-15
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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Gemini 1.0 Pro
Input:$0.50
Output:$1.50
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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30($1.60 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Gemini 1.0 Pro
Average Score:49.2%
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Mistral Small 3.1 24B Base
Average Score:59.3%(+10.1%)
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Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 1.0 Pro
1 providers
Throughput: 120 tok/s
Latency: 0.4ms
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Mistral Small 3.1 24B Base
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Gemini 1.0 Pro
Avg Score:49.2%
Providers:1
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Mistral Small 3.1 24B Base
Avg Score:59.3%(+10.1%)
Providers:1