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DeepSeek-V2.5 vs Qwen2-VL-72B-Instruct
Comprehensive side-by-side LLM comparison
Qwen2-VL-72B-Instruct supports multimodal inputs. DeepSeek-V2.5 is available on 3 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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Alibaba Cloud / Qwen Team
Qwen2-VL 72B was developed as a large vision-language model, designed to handle multimodal tasks combining visual and textual understanding. Built with 72 billion parameters for integrated vision and language processing, it enables applications requiring sophisticated analysis of images alongside text.
3 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
2024-08-29
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Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Qwen2-VL-72B-Instruct
2023-06-30
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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:0.0%
Providers:3
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Qwen2-VL-72B-Instruct
Avg Score:0.0%
Providers:0