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Jamba 1.5 Mini vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 24.1% higher average benchmark score. Jamba 1.5 Mini offers 480.3K more tokens in context window than Phi 4. Both models have similar pricing. Overall, Phi 4 is the stronger choice for coding tasks.
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AI21 Labs
Jamba 1.5 Mini is a language model developed by AI21 Labs. The model shows competitive results across 8 benchmarks. It excels particularly in ARC-C (85.7%), GSM8k (75.8%), MMLU (69.7%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.
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Microsoft
Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
3 months newer
Jamba 1.5 Mini
AI21 Labs
2024-08-22
Phi 4
Microsoft
2024-12-12
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
Input:$0.07
Output:$0.14($0.39 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 17 common benchmarks
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Jamba 1.5 Mini
Average Score:26.4%
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Phi 4
Average Score:50.5%(+24.1%)
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Mini
2024-03-05
Phi 4
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
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Jamba 1.5 Mini
Avg Score:26.4%
Providers:2
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Phi 4
Avg Score:50.5%(+24.1%)
Providers:1