DeepSeek-V3.2-Exp vs Llama 3.1 405B Instruct
DeepSeek-V3.2-Exp leads the LLM Stats Score 28.2 to 14.7. DeepSeek-V3.2-Exp is 2.9x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
DeepSeek-V3.2-Exp leads the overall LLM Stats Score 28.2 to 14.7, ranking #135 overall.
In the 2 individual benchmarks reported for both models, DeepSeek-V3.2-Exp wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3.2-Exp is roughly 2.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2-Exp also accepts a larger context window (163,840 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-V3.2-Exp
- overall performance matters — it scores 28.2 and ranks #135 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 2.9x cheaper per token
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Sep 2025
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
14 reported for DeepSeek-V3.2-Exp · 18 for Llama 3.1 405B Instruct
DeepSeek-V3.2-Exp outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Llama 3.1 405B Instruct is better at 0 benchmarks.
DeepSeek-V3.2-Exp 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-V3.2-Exp ($0.27/1M tokens) is 3.3x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 2.2x cheaper than Llama 3.1 405B Instruct ($0.89/1M tokens).
In conclusion, Llama 3.1 405B Instruct is more expensive than DeepSeek-V3.2-Exp.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.2-Exp has 280.0B more parameters than Llama 3.1 405B Instruct, making it 69.1% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to Llama 3.1 405B Instruct's 128,000 tokens. Llama 3.1 405B Instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, 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
Open weights
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Llama 3.1 405B Instruct was released on 2024-07-23.
DeepSeek-V3.2-Exp is 14 months newer than Llama 3.1 405B Instruct.
Sep 29, 2025
11 months ago
1.2yr newerJul 23, 2024
2.2 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-V3.2-Exp is available from Novita. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.
DeepSeek-V3.2-Exp
Llama 3.1 405B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3.2-Exp and Llama 3.1 405B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3.2-Exp vs Llama 3.1 405B Instruct.