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Jamba 1.5 Large vs QvQ-72B-Preview
Comprehensive side-by-side LLM comparison
Jamba 1.5 Large leads with 27.2% higher average benchmark score. QvQ-72B-Preview supports multimodal inputs. Jamba 1.5 Large is available on 2 providers. Overall, Jamba 1.5 Large is the stronger choice for coding tasks.
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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.
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Alibaba Cloud / Qwen Team
QvQ-72B-Preview is a multimodal language model developed by Alibaba Cloud / Qwen Team. The model shows competitive results across 4 benchmarks. Notable strengths include MathVista (71.4%), MMMU (70.3%), MathVision (35.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
4 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
2024-12-25
Performance Metrics
Context window and performance specifications
Average performance across 12 common benchmarks
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Jamba 1.5 Large
Average Score:43.7%(+27.2%)
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QvQ-72B-Preview
Average Score:16.5%
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Knowledge Cutoff
Training data recency comparison
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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Jamba 1.5 Large
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Throughput: 42 tok/s
Latency: 0.3ms
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Jamba 1.5 Large
Avg Score:43.7%(+27.2%)
Providers:2
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QvQ-72B-Preview
Avg Score:16.5%
Providers:0