Grok-2 vs Llama 3.1 405B Instruct
Grok-2 and Llama 3.1 405B Instruct are closely matched at 11.4 and 14.7 on the LLM Stats Score. Llama 3.1 405B Instruct is 4.5x cheaper per token.
xAI · Meta · Updated for 2026
Which is better?
Grok-2 and Llama 3.1 405B Instruct are closely matched on the overall LLM Stats Score at 11.4 and 14.7.
In the 5 individual benchmarks reported for both models, Grok-2 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Llama 3.1 405B Instruct is roughly 4.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Grok-2
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
- you want the most recent training data — it shipped Aug 2024
Choose Llama 3.1 405B Instruct
- cost matters — it's about 4.5x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Grok-2 · 18 for Llama 3.1 405B Instruct
Grok-2 outperforms in 4 benchmarks (GPQA, MATH, MMLU, MMLU-Pro), while Llama 3.1 405B Instruct is better at 1 benchmark (HumanEval).
Grok-2 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, Grok-2 ($2.00/1M tokens) is 2.2x more expensive than Llama 3.1 405B Instruct ($0.89/1M tokens).
For output processing, Grok-2 ($10.00/1M tokens) is 11.2x more expensive than Llama 3.1 405B Instruct ($0.89/1M tokens).
In conclusion, Grok-2 is more expensive than Llama 3.1 405B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Llama 3.1 405B Instruct can generate longer responses up to 128,000 tokens, while Grok-2 is limited to 8,000 tokens.
Input capabilities
Documented input modalities across available providers
Grok-2 supports multimodal inputs, whereas Llama 3.1 405B Instruct does not.
Grok-2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Grok-2
Llama 3.1 405B Instruct
License
Usage and distribution terms
Grok-2 is licensed under a proprietary license, 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.
Proprietary
Closed source
Llama 3.1 Community License
Open weights
Release Timeline
When each model was launched
Grok-2 was released on 2024-08-13, while Llama 3.1 405B Instruct was released on 2024-07-23.
Grok-2 is 1 month newer than Llama 3.1 405B Instruct.
Aug 13, 2024
2.1 years ago
3w 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
Grok-2 is available from xAI. Llama 3.1 405B Instruct is available from Lambda, DeepInfra, Fireworks, Bedrock, Together, Hyperbolic, Google, Replicate.
Grok-2
Llama 3.1 405B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Grok-2 and Llama 3.1 405B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Grok-2 vs Llama 3.1 405B Instruct.