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Jamba 1.5 Mini vs Mistral Small 3.1 24B Base
Comprehensive side-by-side LLM comparison
Mistral Small 3.1 24B Base leads with 10.0% higher average benchmark score. Jamba 1.5 Mini offers 256.3K more tokens in context window than Mistral Small 3.1 24B Base. Both models have similar pricing. 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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AI21 Labs
Jamba 1.5 Mini was created as a more compact hybrid model, designed to bring the benefits of Jamba's architecture to resource-conscious deployments. Built to provide long-context capabilities with reduced computational requirements, it enables efficient processing of extended inputs in practical applications.
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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.
6 months newer
Jamba 1.5 Mini
AI21 Labs
2024-08-22
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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Jamba 1.5 Mini
Input:$0.20
Output:$0.40
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Mistral Small 3.1 24B Base
Input:$0.10
Output:$0.30($0.20 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Jamba 1.5 Mini
Average Score:48.2%
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Mistral Small 3.1 24B Base
Average Score:58.2%(+10.0%)
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Mini
2024-03-05
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Jamba 1.5 Mini
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Throughput: 100 tok/s
Latency: 0.3ms
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Mistral Small 3.1 24B Base
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Jamba 1.5 Mini
Avg Score:48.2%
Providers:2
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Mistral Small 3.1 24B Base
Avg Score:58.2%(+10.0%)
Providers:1