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Jamba 1.5 Large vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 15.1% higher average benchmark score. Jamba 1.5 Large is available on 2 providers. Overall, Phi 4 Mini Reasoning is the stronger choice for coding 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.
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Microsoft
Phi-4 Mini Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
8 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Jamba 1.5 Large
Average Score:36.9%
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Phi 4 Mini Reasoning
Average Score:52.0%(+15.1%)
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
2024-03-05
Phi 4 Mini Reasoning
2025-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Jamba 1.5 Large
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Throughput: 42 tok/s
Latency: 0.3ms
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Phi 4 Mini Reasoning
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Jamba 1.5 Large
Avg Score:36.9%
Providers:2
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Phi 4 Mini Reasoning
Avg Score:52.0%(+15.1%)
Providers:0