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DeepSeek-V3 vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 17.3% higher average benchmark score. Jamba 1.5 Large offers 249.9K more tokens in context window than DeepSeek-V3. DeepSeek-V3 is $8.63 cheaper per million tokens. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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
DeepSeek
2024-12-25
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3
Input:$0.27
Output:$1.10($8.63 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 3 common benchmarks
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DeepSeek-V3
Average Score:74.5%(+17.3%)
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Jamba 1.5 Large
Average Score:57.2%
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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 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Jamba 1.5 Large
2 providers
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DeepSeek-V3
Avg Score:74.5%(+17.3%)
Providers:1
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Jamba 1.5 Large
Avg Score:57.2%
Providers:2