GPT-6 Luna vs Llama 3.3 70B Instruct
GPT-6 Luna leads the LLM Stats Score 44.5 to 13.8. Llama 3.3 70B Instruct is 1.6x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.5 to 13.8, ranking #41 overall.
On price, Llama 3.3 70B Instruct is roughly 1.6x 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 3.3 70B Instruct
- cost matters — it's about 1.6x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Luna · 9 for Llama 3.3 70B Instruct
GPT-6 Luna and Llama 3.3 70B 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) costs the same as Llama 3.3 70B Instruct ($0.10/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.5x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).
In conclusion, GPT-6 Luna is more expensive than Llama 3.3 70B 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 3.3 70B Instruct's 131,072 tokens. Llama 3.3 70B 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 3.3 70B 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 3.3 70B Instruct
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while Llama 3.3 70B Instruct uses Llama 3.3 Community License Agreement.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.3 Community License Agreement
Open weights
Release Timeline
When each model was launched
GPT-6 Luna was released on 2026-09-22, while Llama 3.3 70B Instruct was released on 2024-12-06.
GPT-6 Luna is 22 months newer than Llama 3.3 70B Instruct.
Sep 22, 2026
0 days ago
1.8yr newerDec 6, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Llama 3.3 70B Instruct's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Llama 3.3 70B Instruct's cutoff date.
May 2026
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Provider Availability
GPT-6 Luna is available from OpenAI. Llama 3.3 70B Instruct is available from DeepInfra, Lambda, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.
GPT-6 Luna
Llama 3.3 70B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and Llama 3.3 70B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs Llama 3.3 70B Instruct.