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DeepSeek VL2 vs GPT-3.5 Turbo
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 32.7% higher average benchmark score. DeepSeek VL2 offers 238.1K more tokens in context window than GPT-3.5 Turbo. GPT-3.5 Turbo is $4807.50 cheaper per million tokens. DeepSeek VL2 supports multimodal inputs. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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OpenAI
GPT-3.5 Turbo is a language model developed by OpenAI. The model shows competitive results across 8 benchmarks. Notable strengths include DROP (70.2%), MMLU (69.8%), HumanEval (68.0%). The model is available through 2 API providers.
1 year newer
GPT-3.5 Turbo
OpenAI
2023-03-21
DeepSeek VL2
DeepSeek
2024-12-13
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek VL2
Input:$9.50
Output:$4800.00
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GPT-3.5 Turbo
Input:$0.50
Output:$1.50($4807.50 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 20 common benchmarks
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DeepSeek VL2
Average Score:49.6%(+32.7%)
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GPT-3.5 Turbo
Average Score:16.9%
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Knowledge Cutoff
Training data recency comparison
GPT-3.5 Turbo
2021-09-30
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 VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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GPT-3.5 Turbo
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DeepSeek VL2
Avg Score:49.6%(+32.7%)
Providers:1
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GPT-3.5 Turbo
Avg Score:16.9%
Providers:2