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Gemini 1.0 Pro vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
Jamba 1.5 Large leads with 5.9% higher average benchmark score. Jamba 1.5 Large offers 471.0K more tokens in context window than Gemini 1.0 Pro. Gemini 1.0 Pro is $8.00 cheaper per million tokens. Overall, Jamba 1.5 Large is the stronger choice for coding tasks.
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Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
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AI21 Labs
Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). 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.
6 months newer
Gemini 1.0 Pro
2024-02-15
Jamba 1.5 Large
AI21 Labs
2024-08-22
Pricing Comparison
Cost per million tokens (USD)
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Gemini 1.0 Pro
Input:$0.50
Output:$1.50($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 15 common benchmarks
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Gemini 1.0 Pro
Average Score:29.0%
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Jamba 1.5 Large
Average Score:34.9%(+5.9%)
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Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
Jamba 1.5 Large
2024-03-05
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 1.0 Pro
1 providers
Throughput: 120 tok/s
Latency: 0.4ms
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Jamba 1.5 Large
2 providers
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Gemini 1.0 Pro
Avg Score:29.0%
Providers:1
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Jamba 1.5 Large
Avg Score:34.9%(+5.9%)
Providers:2