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DeepSeek-V3.1 vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 34.1% higher average benchmark score. Jamba 1.5 Large offers 184.3K more tokens in context window than DeepSeek-V3.1. DeepSeek-V3.1 is $8.73 cheaper per million tokens. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.1 was developed as an incremental advancement over DeepSeek-V3, designed to refine the mixture-of-experts architecture with improved training techniques. Built to enhance quality and efficiency while maintaining the open-source philosophy, it represents continued iteration on DeepSeek's flagship model line.
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AI21 Labs
Jamba 1.5 Large was developed by AI21 Labs using a hybrid architecture combining transformer and state space models, designed to provide efficient long-context understanding. Built to handle extended documents and conversations with computational efficiency, it represents AI21's innovation in efficient large-scale model design.
4 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
DeepSeek-V3.1
DeepSeek
2025-01-10
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.00($8.73 cheaper)
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Jamba 1.5 Large
Input:$2.00
Output:$8.00
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V3.1
Average Score:79.3%(+34.1%)
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Jamba 1.5 Large
Average Score:45.2%
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
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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DeepSeek-V3.1
2 providers
DeepInfra
Novita
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Jamba 1.5 Large
2 providers
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DeepSeek-V3.1
Avg Score:79.3%(+34.1%)
Providers:2
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Jamba 1.5 Large
Avg Score:45.2%
Providers:2