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GPT-5.6 Luna vs GPT-6 Luna

GPT-5.6 Luna and GPT-6 Luna are closely matched at 44.9 and 44.5 on the LLM Stats Score. GPT-6 Luna is 2.3x cheaper per token.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-5.6 Luna and GPT-6 Luna are closely matched on the overall LLM Stats Score at 44.9 and 44.5.

In the 4 individual benchmarks reported for both models, GPT-6 Luna wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, GPT-6 Luna is roughly 2.3x 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 GPT-5.6 Luna

  • you want predictable pricing at $0.20/M input and $1.20/M output

Choose GPT-6 Luna

  • you value its reported benchmark strengths — it wins 3 of 4 exact shared results
  • cost matters — it's about 2.3x cheaper per token
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Core performance indexes
44.9
#35
44.5
#40
43.5
#40
40.0
#58
36.3
#21
31.4
#47
31.4
#34
31.8
#30
Cost, coverage & limits
Benchmark wins
1 of 4
3 of 4
Input price
$0.20 / M
$0.10 / M
Output price
$1.20 / M
$0.50 / M
Context window
1,050,000
1,050,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GPT-5.6 Luna
GPT-6 Luna
22.5#43
22.1#47
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

45 reported for GPT-5.6 Luna · 5 for GPT-6 Luna

4 shared

GPT-5.6 Luna outperforms in 1 benchmarks (DeepSWE 1.1), while GPT-6 Luna is better at 3 benchmarks (Agents' Last Exam, FrontierCode 1.1, OSWorld 2.0).

GPT-6 Luna shows notably better performance in the majority of benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT-6 Luna costs less

For input processing, GPT-5.6 Luna ($0.20/1M tokens) is 2.0x more expensive than GPT-6 Luna ($0.10/1M tokens).

For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 2.4x more expensive than GPT-6 Luna ($0.50/1M tokens).

In conclusion, GPT-5.6 Luna is more expensive than GPT-6 Luna.*

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

Lowest available price from all providers
Tue Sep 22 2026 • llm-stats.com
OpenAI
GPT-5.6 Luna
Input tokens$0.20
Output tokens$1.20
Best providerOpenAI
OpenAI
GPT-6 Luna
Input tokens$0.10
Output tokens$0.50
Best providerOpenAI
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,050,000 tokens. Both models can generate responses up to 128,000 tokens.

OpenAI
GPT-5.6 Luna
Input1,050,000 tokens
Output128,000 tokens
OpenAI
GPT-6 Luna
Input1,050,000 tokens
Output128,000 tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-5.6 Luna and GPT-6 Luna support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-5.6 Luna

Text
Images
Audio
Video

GPT-6 Luna

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-5.6 Luna

Proprietary

Closed source

GPT-6 Luna

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-5.6 Luna was released on 2026-07-09, while GPT-6 Luna was released on 2026-09-22.

GPT-6 Luna is 3 months newer than GPT-5.6 Luna.

GPT-5.6 Luna

Jul 9, 2026

2 months ago

GPT-6 Luna

Sep 22, 2026

0 days ago

2mo newer

Knowledge Cutoff

When training data ends

GPT-5.6 Luna has a knowledge cutoff of 2026-02-16, while GPT-6 Luna has a cutoff of 2026-05-18.

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 GPT-5.6 Luna (2026-02-16).

GPT-5.6 Luna

Feb 2026

GPT-6 Luna

May 2026

3 mo newer

Provider Availability

GPT-5.6 Luna is available from OpenAI. GPT-6 Luna is available from OpenAI.

GPT-5.6 Luna

openai logo
OpenAI
Input Price:Input: $0.20/1MOutput Price:Output: $1.20/1M

GPT-6 Luna

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-5.6 Luna and GPT-6 Luna side-by-side, then vote on the output you prefer.

GPT-5.6 Luna
✓ Preferred
GPT-6 Luna
Open in Playground

FAQ

Common questions about GPT-5.6 Luna vs GPT-6 Luna.

Which is better, GPT-5.6 Luna or GPT-6 Luna?

GPT-5.6 Luna and GPT-6 Luna are closely matched on the LLM Stats Score at 44.9 and 44.5. GPT-5.6 Luna is made by OpenAI and GPT-6 Luna is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-5.6 Luna compare to GPT-6 Luna 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%. GPT-6 Luna scores DeepSWE 1.1: 66.6%, OSWorld 2.0: 52.7%, Agents' Last Exam: 50.9%, FrontierCode 1.1: 42.4%, AutomationBench v1.0.6: 20.7%.

Is GPT-5.6 Luna cheaper than GPT-6 Luna?

GPT-6 Luna is 2.0x cheaper for input tokens. GPT-5.6 Luna costs $0.20/M input and $1.20/M output via openai. GPT-6 Luna costs $0.10/M input and $0.50/M output via openai.

What are the context window sizes for GPT-5.6 Luna and GPT-6 Luna?

GPT-5.6 Luna supports 1.1M tokens and GPT-6 Luna supports 1.1M 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 GPT-6 Luna?

Key differences include LLM Stats Score (44.9 vs 44.5), input pricing ($0.20 vs $0.10/M). See the full comparison above for benchmark-by-benchmark results.