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Jamba 1.5 Large vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Jamba 1.5 Large offers 256.0K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $9.85 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
5 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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Pricing Comparison
Cost per million tokens (USD)
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Jamba 1.5 Large
Input:$2.00
Output:$8.00
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($9.85 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
2024-03-05
Phi-4-multimodal-instruct
2024-06-01
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-multimodal-instruct
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Jamba 1.5 Large
Avg Score:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1