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GPT-4.1 mini vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
GPT-4.1 mini leads with 17.2% higher average benchmark score. GPT-4.1 mini offers 568.3K more tokens in context window than Jamba 1.5 Large. GPT-4.1 mini is $8.00 cheaper per million tokens. GPT-4.1 mini supports multimodal inputs. Overall, GPT-4.1 mini is the stronger choice for coding tasks.
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OpenAI
GPT-4.1 Mini was created as a smaller, more efficient variant of GPT-4.1, designed to provide strong capabilities with reduced computational requirements. Built to serve applications where speed and cost are priorities while maintaining solid performance, it extends the GPT-4.1 capabilities to resource-conscious deployments.
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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.
7 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
GPT-4.1 mini
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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GPT-4.1 mini
Input:$0.40
Output:$1.60($8.00 cheaper)
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Jamba 1.5 Large
Input:$2.00
Output:$8.00
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT-4.1 mini
Average Score:76.3%(+17.2%)
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Jamba 1.5 Large
Average Score:59.1%
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
2024-03-05
GPT-4.1 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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GPT-4.1 mini
2 providers
OpenAI
Throughput: 150 tok/s
Latency: 5ms
ZeroEval
Throughput: 150 tok/s
Latency: 5ms
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Jamba 1.5 Large
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GPT-4.1 mini
Avg Score:76.3%(+17.2%)
Providers:2
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Jamba 1.5 Large
Avg Score:59.1%
Providers:2