Model Comparison

GPT-5.6 Luna vs Llama 3.3 70B InstructWhich is better in 2026?

GPT-5.6 Luna significantly outperforms across most benchmarks. Llama 3.3 70B Instruct is 11.3x cheaper per token.

Verdict: GPT-5.6 Luna vs Llama 3.3 70B Instruct — which is better?

GPT-5.6 Luna (by OpenAI) and Llama 3.3 70B 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 1 benchmarks (GPQA), while Llama 3.3 70B Instruct is better at 0 benchmarks. GPT-5.6 Luna significantly outperforms across most benchmarks.

On price, Llama 3.3 70B Instruct is roughly 11.3x 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 1 of 1 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 3.3 70B Instruct if…

  • cost matters — it's about 11.3x cheaper per token
  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-5.6 Luna outperforms in 1 benchmarks (GPQA), while Llama 3.3 70B Instruct is better at 0 benchmarks.

GPT-5.6 Luna significantly outperforms across most benchmarks.

Sat Jul 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Llama 3.3 70B Instruct costs less

For input processing, GPT-5.6 Luna ($1.00/1M tokens) is 5.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

For output processing, GPT-5.6 Luna ($6.00/1M tokens) is 30.0x more expensive than Llama 3.3 70B Instruct ($0.20/1M tokens).

In conclusion, GPT-5.6 Luna is more expensive than Llama 3.3 70B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Jul 18 2026 • llm-stats.com
OpenAI
GPT-5.6 Luna
Input tokens$1.00
Output tokens$6.00
Best providerOpenAI
Meta
Llama 3.3 70B Instruct
Input tokens$0.20
Output tokens$0.20
Best providerLambda
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-5.6 Luna accepts 1,050,000 input tokens compared to Llama 3.3 70B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
Meta
Llama 3.3 70B Instruct
Input128,000 tokens
Output128,000 tokens
Sat Jul 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.6 Luna supports multimodal inputs, whereas Llama 3.3 70B Instruct does not.

GPT-5.6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-5.6 Luna

Text
Images
Audio
Video

Llama 3.3 70B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-5.6 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.

GPT-5.6 Luna

Proprietary

Closed source

Llama 3.3 70B Instruct

Llama 3.3 Community License Agreement

Open weights

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while Llama 3.3 70B Instruct was released on 2024-12-06.

GPT-5.6 Luna is 19 months newer than Llama 3.3 70B Instruct.

GPT-5.6 Luna

Jul 9, 2026

1 weeks ago

1.6yr newer
Llama 3.3 70B Instruct

Dec 6, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Llama 3.3 70B Instruct's cutoff date is not specified.

We can confirm GPT-5.6 Luna's training data extends to 2026-02-16, but cannot make a direct comparison without Llama 3.3 70B Instruct's cutoff date.

GPT-5.6 Luna

Feb 2026

Llama 3.3 70B Instruct

Provider Availability

GPT-5.6 Luna is available from OpenAI. Llama 3.3 70B Instruct is available from Lambda, DeepInfra, Hyperbolic, Groq, Sambanova, Cerebras, Bedrock, Together, Fireworks.

GPT-5.6 Luna

openai logo
OpenAI
Input Price:Input: $1.00/1MOutput Price:Output: $6.00/1M

Llama 3.3 70B Instruct

lambda logo
Lambda
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.23/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
groq logo
Groq
Input Price:Input: $0.59/1MOutput Price:Output: $7.90/1M
sambanova logo
Sambanova
Input Price:Input: $0.60/1MOutput Price:Output: $1.20/1M
cerebras logo
Cerebras
Input Price:Input: $0.70/1MOutput Price:Output: $0.80/1M
bedrock logo
AWS Bedrock
Input Price:Input: $0.72/1MOutput Price:Output: $0.72/1M
together logo
Together
Input Price:Input: $0.88/1MOutput Price:Output: $0.88/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (1,050,000 tokens)
Supports multimodal inputs
Higher GPQA score (92.3% vs 50.5%)
Less expensive input tokens
Less expensive output tokens
Has open weights

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and Llama 3.3 70B Instruct side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
Llama 3.3 70B Instruct
Open in Playground
AI Model Comparison Table
Feature
OpenAI
GPT-5.6 Luna
Meta
Llama 3.3 70B Instruct

FAQ

Common questions about GPT-5.6 Luna vs Llama 3.3 70B Instruct.

Which is better, GPT-5.6 Luna or Llama 3.3 70B Instruct?

GPT-5.6 Luna significantly outperforms across most benchmarks. GPT-5.6 Luna is made by OpenAI and Llama 3.3 70B Instruct is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT-5.6 Luna compare to Llama 3.3 70B Instruct in benchmarks?

GPT-5.6 Luna scores Connectors: 99.9%, HealthBench Consensus: 95.1%, GPQA: 92.3%, Search and Function-Calling: 89.7%, Capture-the-Flag Challenges (Internal): 85.2%. Llama 3.3 70B Instruct scores IFEval: 92.1%, MGSM: 91.1%, HumanEval: 88.4%, MBPP EvalPlus: 87.6%, MMLU: 86.0%.

Is GPT-5.6 Luna cheaper than Llama 3.3 70B Instruct?

Llama 3.3 70B Instruct is 5.0x cheaper for input tokens. GPT-5.6 Luna costs $1.00/M input and $6.00/M output via openai. Llama 3.3 70B Instruct costs $0.20/M input and $0.20/M output via lambda.

What are the context window sizes for GPT-5.6 Luna and Llama 3.3 70B Instruct?

GPT-5.6 Luna supports 1.1M tokens and Llama 3.3 70B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5.6 Luna and Llama 3.3 70B Instruct?

Key differences include context window (1.1M vs 128K), input pricing ($1.00 vs $0.20/M), multimodal support (yes vs no), licensing (Proprietary vs Llama 3.3 Community License Agreement). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.6 Luna and Llama 3.3 70B Instruct?

GPT-5.6 Luna is developed by OpenAI and Llama 3.3 70B Instruct is developed by Meta.