Model Comparison
DeepSeek-V2.5 vs Llama 3.1 405B InstructWhich is better in 2026?
Llama 3.1 405B Instruct has a slight edge in benchmark performance. DeepSeek-V2.5 is 5.1x cheaper per token.
Verdict: DeepSeek-V2.5 vs Llama 3.1 405B Instruct — which is better?
DeepSeek-V2.5 (by DeepSeek) and Llama 3.1 405B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V2.5 outperforms in 1 benchmarks (MATH), while Llama 3.1 405B Instruct is better at 2 benchmarks (GSM8k, MMLU). Llama 3.1 405B Instruct has a slight edge in benchmark performance.
On price, DeepSeek-V2.5 is roughly 5.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 3.1 405B Instruct also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V2.5 if…
- cost matters — it's about 5.1x cheaper per token
Choose Llama 3.1 405B Instruct if…
- you want the strongest raw capability — it leads on 3 of 4 shared benchmarks
- you process long inputs — it offers a 128,000 token context window
- you want the most recent training data — it shipped Jul 2024
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 1 benchmarks (MATH), while Llama 3.1 405B Instruct is better at 2 benchmarks (GSM8k, MMLU).
Llama 3.1 405B Instruct has a slight edge in benchmark performance.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 6.4x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 3.2x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
In conclusion, Llama 3.1 405B Instruct is more expensive than DeepSeek-V2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 3.1 405B Instruct has 169.0B more parameters than DeepSeek-V2.5, making it 71.6% larger.
Context Window
Maximum input and output token capacity
Llama 3.1 405B Instruct accepts 128,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Llama 3.1 405B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Llama 3.1 405B Instruct uses Llama 3.1 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Llama 3.1 405B Instruct was released on 2024-07-23.
Llama 3.1 405B Instruct is 3 months newer than DeepSeek-V2.5.
May 8, 2024
2.1 years ago
Jul 23, 2024
1.9 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.
DeepSeek-V2.5
Llama 3.1 405B Instruct
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek-V2.5 vs Llama 3.1 405B Instruct.