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DeepSeek-V3.2-Exp vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 37.3% higher average benchmark score. Jamba 1.5 Large offers 282.6K more tokens in context window than DeepSeek-V3.2-Exp. DeepSeek-V3.2-Exp is $9.32 cheaper per million tokens. Overall, DeepSeek-V3.2-Exp is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.2-Exp was introduced as an experimental release, designed to test new architectural innovations and training methodologies. Built to explore the boundaries of mixture-of-experts design, it serves as a research preview for techniques that may be incorporated into future stable releases.
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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.
1 year newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2-Exp
Input:$0.27
Output:$0.41($9.32 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-V3.2-Exp
Average Score:82.5%(+37.3%)
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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-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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Jamba 1.5 Large
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DeepSeek-V3.2-Exp
Avg Score:82.5%(+37.3%)
Providers:2
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Jamba 1.5 Large
Avg Score:45.2%
Providers:2