DeepSeek-V3 vs Llama 3.1 405B Instruct
DeepSeek-V3 and Llama 3.1 405B Instruct are closely matched at 15.7 and 14.7 on the LLM Stats Score. DeepSeek-V3 is 2.1x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V3 and Llama 3.1 405B Instruct are closely matched on the overall LLM Stats Score at 15.7 and 14.7.
In the 5 individual benchmarks reported for both models, DeepSeek-V3 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
- cost matters — it's about 2.1x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Dec 2024
Choose Llama 3.1 405B Instruct
- you want predictable pricing at $0.89/M input and $0.89/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V3 · 18 for Llama 3.1 405B Instruct
DeepSeek-V3 outperforms in 4 benchmarks (DROP, GPQA, MMLU, MMLU-Pro), while Llama 3.1 405B Instruct is better at 1 benchmark (IFEval).
DeepSeek-V3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 ($0.27/1M tokens) is 3.3x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
For output processing, DeepSeek-V3 ($0.89/1M tokens) costs the same as Llama 3.1 405B Instruct ($0.89/1M tokens).
In conclusion, Llama 3.1 405B Instruct is more expensive than DeepSeek-V3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 has 266.0B more parameters than Llama 3.1 405B Instruct, making it 65.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 accepts 131,072 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Llama 3.1 405B Instruct is limited to 128,000 tokens.
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), 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.
MIT + Model License (Commercial use allowed)
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Llama 3.1 405B Instruct was released on 2024-07-23.
DeepSeek-V3 is 5 months newer than Llama 3.1 405B Instruct.
Dec 25, 2024
1.7 years ago
5mo newerJul 23, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 is available from DeepSeek, DeepInfra. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.
DeepSeek-V3
Llama 3.1 405B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Llama 3.1 405B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Llama 3.1 405B Instruct.