GPT-5.6 Luna vs Laguna S 2.1
GPT-5.6 Luna and Laguna S 2.1 are closely matched at 46.5 and 41.4 on the LLM Stats Score. Laguna S 2.1 is 3.6x cheaper per token.
OpenAI · Poolside · Updated for 2026
Which is better?
GPT-5.6 Luna and Laguna S 2.1 are closely matched on the overall LLM Stats Score at 46.5 and 41.4.
In the 4 individual benchmarks reported for both models, GPT-5.6 Luna wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Laguna S 2.1 is roughly 3.6x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.6 Luna
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
Choose Laguna S 2.1
- cost matters — it's about 3.6x cheaper per token
- you want the most recent training data — it shipped Jul 2026
- 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
44 reported for GPT-5.6 Luna · 6 for Laguna S 2.1
GPT-5.6 Luna outperforms in 4 benchmarks (DeepSWE 1.1, SWE-Bench Pro, Terminal-Bench 2.1, Toolathlon), while Laguna S 2.1 is better at 0 benchmarks.
GPT-5.6 Luna significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5.6 Luna ($0.20/1M tokens) is 2.0x more expensive than Laguna S 2.1 ($0.10/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 6.0x more expensive than Laguna S 2.1 ($0.20/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than Laguna S 2.1.*
* 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 Laguna S 2.1's 1,048,576 tokens. Only GPT-5.6 Luna specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
GPT-5.6 Luna supports multimodal inputs, whereas Laguna S 2.1 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
Laguna S 2.1
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while Laguna S 2.1 uses OpenMDW License v1.1.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
OpenMDW License v1.1
Open weights
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while Laguna S 2.1 was released on 2026-07-21.
Laguna S 2.1 is 0 month newer than GPT-5.6 Luna.
Jul 9, 2026
1 months ago
Jul 21, 2026
1 months ago
1w newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Laguna S 2.1'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 Laguna S 2.1's cutoff date.
Feb 2026
—
Provider Availability
GPT-5.6 Luna is available from OpenAI. Laguna S 2.1 is available from Poolside.
GPT-5.6 Luna
Laguna S 2.1
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and Laguna S 2.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs Laguna S 2.1.