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Jamba 1.5 Mini vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Jamba 1.5 Mini offers 256.3K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. 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 Mini was created as a more compact hybrid model, designed to bring the benefits of Jamba's architecture to resource-conscious deployments. Built to provide long-context capabilities with reduced computational requirements, it enables efficient processing of extended inputs in practical applications.
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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 Mini
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 Mini
Input:$0.20
Output:$0.40
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($0.45 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Mini
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 Mini
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Throughput: 100 tok/s
Latency: 0.3ms
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Phi-4-multimodal-instruct
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Jamba 1.5 Mini
Avg Score:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1