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DeepSeek-V2.5 vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 6.0% higher average benchmark score. Jamba 1.5 Large offers 495.6K more tokens in context window than DeepSeek-V2.5. DeepSeek-V2.5 is $9.58 cheaper per million tokens. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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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.
3 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Jamba 1.5 Large
AI21 Labs
2024-08-22
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($9.58 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-V2.5
Average Score:83.9%(+6.0%)
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Jamba 1.5 Large
Average Score:77.9%
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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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:83.9%(+6.0%)
Providers:3
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Jamba 1.5 Large
Avg Score:77.9%
Providers:2