Model Comparison
DeepSeek R1 Distill Llama 8B vs DeepSeek-V3
Both models are evenly matched across the benchmarks.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Llama 8B outperforms in 2 benchmarks (AIME 2024, LiveCodeBench), while DeepSeek-V3 is better at 2 benchmarks (GPQA, MATH-500).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
DeepSeek-V3 has 663.0B more parameters than DeepSeek R1 Distill Llama 8B, making it 8256.2% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).
License
Usage and distribution terms
DeepSeek R1 Distill Llama 8B is licensed under MIT, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
MIT + Model License (Commercial use allowed)
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 8B was released on 2025-01-20, while DeepSeek-V3 was released on 2024-12-25.
DeepSeek R1 Distill Llama 8B is 1 month newer than DeepSeek-V3.
Jan 20, 2025
1.2 years ago
3w newerDec 25, 2024
1.3 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek-V3
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek R1 Distill Llama 8B vs DeepSeek-V3