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DeepSeek-V2.5 vs Llama 3.2 3B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 8.6% higher average benchmark score. Llama 3.2 3B Instruct offers 239.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. DeepSeek-V2.5 is available on 3 providers. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 is a language model developed by DeepSeek. It achieves strong performance with an average score of 71.1% across 15 benchmarks. It excels particularly in GSM8k (95.1%), MT-Bench (90.2%), HumanEval (89.0%). The model is available through 3 API providers. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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Meta
Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Llama 3.2 3B Instruct
Meta
2024-09-25
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28
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Llama 3.2 3B Instruct
Input:$0.01
Output:$0.02($0.39 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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DeepSeek-V2.5
Average Score:39.5%(+8.6%)
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Llama 3.2 3B Instruct
Average Score:30.9%
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:39.5%(+8.6%)
Providers:3
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Llama 3.2 3B Instruct
Avg Score:30.9%
Providers:1