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Jamba 1.5 Mini vs o4-mini
Comprehensive side-by-side LLM comparison
o4-mini leads with 49.1% higher average benchmark score. Jamba 1.5 Mini offers 212.3K more tokens in context window than o4-mini. Jamba 1.5 Mini is $4.90 cheaper per million tokens. o4-mini supports multimodal inputs. Overall, o4-mini is the stronger choice for coding tasks.
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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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OpenAI
o4-mini was created as part of the next generation of OpenAI's reasoning models, designed to continue advancing the balance between analytical capability and operational efficiency. Built to bring cutting-edge reasoning techniques to applications requiring quick turnaround, it represents the evolution of compact reasoning-focused models.
7 months newer
Jamba 1.5 Mini
AI21 Labs
2024-08-22
o4-mini
OpenAI
2025-04-16
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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($4.90 cheaper)
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o4-mini
Input:$1.10
Output:$4.40
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Jamba 1.5 Mini
Average Score:32.3%
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o4-mini
Average Score:81.4%(+49.1%)
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Mini
2024-03-05
o4-mini
2024-05-31
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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o4-mini
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Jamba 1.5 Mini
Avg Score:32.3%
Providers:2
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o4-mini
Avg Score:81.4%(+49.1%)
Providers:1