GPT-6 Luna vs Llama 3.1 8B Instruct
GPT-6 Luna leads the LLM Stats Score 44.5 to -2.6. Llama 3.1 8B Instruct is 8.9x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.5 to -2.6, ranking #41 overall.
On price, Llama 3.1 8B Instruct is roughly 8.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Luna also accepts a larger context window (1,050,000 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 GPT-6 Luna
- overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Llama 3.1 8B Instruct
- cost matters — it's about 8.9x 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
5 reported for GPT-6 Luna · 18 for Llama 3.1 8B Instruct
GPT-6 Luna and Llama 3.1 8B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Luna ($0.10/1M tokens) is 5.0x more expensive than Llama 3.1 8B Instruct ($0.02/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 16.7x more expensive than Llama 3.1 8B Instruct ($0.03/1M tokens).
In conclusion, GPT-6 Luna is more expensive than Llama 3.1 8B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Luna accepts 1,050,000 input tokens compared to Llama 3.1 8B Instruct's 131,072 tokens. Llama 3.1 8B Instruct can generate longer responses up to 131,072 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas Llama 3.1 8B Instruct does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Luna
Llama 3.1 8B Instruct
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while Llama 3.1 8B 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
GPT-6 Luna was released on 2026-09-22, while Llama 3.1 8B Instruct was released on 2024-07-23.
GPT-6 Luna is 26 months newer than Llama 3.1 8B Instruct.
Sep 22, 2026
0 days ago
2.2yr newerJul 23, 2024
2.2 years ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a knowledge cutoff of 2026-05-18, while Llama 3.1 8B Instruct has a cutoff of 2023-12-31.
GPT-6 Luna has more recent training data (up to 2026-05-18), making it potentially better informed about events through that date compared to Llama 3.1 8B Instruct (2023-12-31).
May 2026
2.4 yr newerDec 2023
Provider Availability
GPT-6 Luna is available from OpenAI. Llama 3.1 8B Instruct is available from DeepInfra, Lambda, Groq, Sambanova, Cerebras, Hyperbolic, Together, Fireworks, Bedrock.
GPT-6 Luna
Llama 3.1 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and Llama 3.1 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs Llama 3.1 8B Instruct.