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GPT-5 nano vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 34.3% higher average benchmark score. GPT-5 nano offers 16.0K more tokens in context window than Jamba 1.5 Large. GPT-5 nano is $9.55 cheaper per million tokens. GPT-5 nano supports multimodal inputs. Overall, GPT-5 nano is the stronger choice for coding tasks.
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OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
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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.
11 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
GPT-5 nano
OpenAI
2025-08-07
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Pricing Comparison
Cost per million tokens (USD)
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GPT-5 nano
Input:$0.05
Output:$0.40($9.55 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 1 common benchmarks
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GPT-5 nano
Average Score:71.2%(+34.3%)
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Jamba 1.5 Large
Average Score:36.9%
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
2024-03-05
GPT-5 nano
2024-05-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-5 nano
2 providers
OpenAI
Throughput: 500 tok/s
Latency: 0.3ms
ZeroEval
Throughput: 500 tok/s
Latency: 0.3ms
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Jamba 1.5 Large
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GPT-5 nano
Avg Score:71.2%(+34.3%)
Providers:2
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Jamba 1.5 Large
Avg Score:36.9%
Providers:2