Model Comparison
GPT-5.6 Luna vs Llama 3.2 11B InstructWhich is better in 2026?
GPT-5.6 Luna significantly outperforms across most benchmarks. Llama 3.2 11B Instruct is 45.0x cheaper per token.
Verdict: GPT-5.6 Luna vs Llama 3.2 11B Instruct — which is better?
GPT-5.6 Luna (by OpenAI) and Llama 3.2 11B Instruct (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT-5.6 Luna outperforms in 2 benchmarks (GPQA, MMMU-Pro), while Llama 3.2 11B Instruct is better at 0 benchmarks. GPT-5.6 Luna significantly outperforms across most benchmarks.
On price, Llama 3.2 11B Instruct is roughly 45.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-5.6 Luna if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Llama 3.2 11B Instruct if…
- cost matters — it's about 45.0x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5.6 Luna outperforms in 2 benchmarks (GPQA, MMMU-Pro), while Llama 3.2 11B Instruct is better at 0 benchmarks.
GPT-5.6 Luna significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($1.00/1M tokens) is 20.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
For output processing, GPT-5.6 Luna ($6.00/1M tokens) is 120.0x more expensive than Llama 3.2 11B Instruct ($0.05/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than Llama 3.2 11B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Luna accepts 1,050,000 input tokens compared to Llama 3.2 11B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Both GPT-5.6 Luna and Llama 3.2 11B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
Llama 3.2 11B Instruct
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while Llama 3.2 11B Instruct uses Llama 3.2 Community License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Llama 3.2 Community License
Open weights
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while Llama 3.2 11B Instruct was released on 2024-09-25.
GPT-5.6 Luna is 22 months newer than Llama 3.2 11B Instruct.
Jul 9, 2026
1 weeks ago
1.8yr newerSep 25, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
GPT-5.6 Luna has a knowledge cutoff of 2026-02-16, while Llama 3.2 11B Instruct has a cutoff of 2023-12-31.
GPT-5.6 Luna has more recent training data (up to 2026-02-16), making it potentially better informed about events through that date compared to Llama 3.2 11B Instruct (2023-12-31).
Feb 2026
2.2 yr newerDec 2023
Provider Availability
GPT-5.6 Luna is available from OpenAI. Llama 3.2 11B Instruct is available from DeepInfra, Sambanova, Bedrock, Groq, Together, Fireworks.
GPT-5.6 Luna
Llama 3.2 11B Instruct
Outputs Comparison
Key Takeaways
GPT-5.6 Luna
View detailsOpenAI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and Llama 3.2 11B Instruct side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-5.6 Luna vs Llama 3.2 11B Instruct.