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DeepSeek VL2 Tiny vs Jamba 1.5 Large
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Tiny supports multimodal inputs. Jamba 1.5 Large is available on 2 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2-Tiny was developed as an ultra-efficient vision-language model, designed for deployment in resource-constrained environments. Built to enable multimodal AI on edge devices and mobile applications, it distills vision-language capabilities into a minimal footprint for widespread accessibility.
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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.
3 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
DeepSeek VL2 Tiny
DeepSeek
2024-12-13
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Performance Metrics
Context window and performance specifications
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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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DeepSeek VL2 Tiny
0 providers
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Jamba 1.5 Large
2 providers
Bedrock
Throughput: 100 tok/s
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DeepSeek VL2 Tiny
Avg Score:0.0%
Providers:0
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Jamba 1.5 Large
Avg Score:0.0%
Providers:2