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DeepSeek-V3 vs Llama 3.2 3B Instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 20.0% higher average benchmark score. DeepSeek-V3 offers 6.1K more tokens in context window than Llama 3.2 3B Instruct. Llama 3.2 3B Instruct is $1.34 cheaper per million tokens. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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Meta
Llama 3.2 3B was created as an ultra-compact open-source model, designed to enable on-device and edge deployment scenarios. Built with just 3 billion parameters while retaining instruction-following abilities, it brings Meta's language technology to mobile devices, IoT applications, and resource-constrained environments.
3 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
DeepSeek-V3
DeepSeek
2024-12-25
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3
Input:$0.27
Output:$1.10
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Llama 3.2 3B Instruct
Input:$0.01
Output:$0.02($1.34 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V3
Average Score:77.9%(+20.0%)
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Llama 3.2 3B Instruct
Average Score:57.9%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Llama 3.2 3B Instruct
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DeepSeek-V3
Avg Score:77.9%(+20.0%)
Providers:1
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Llama 3.2 3B Instruct
Avg Score:57.9%
Providers:1