GPT-6 Luna vs MAI-Code-1.1-Flash
GPT-6 Luna leads the LLM Stats Score 44.3 to 27.8. GPT-6 Luna is 2.3x cheaper per token.
OpenAI · Microsoft · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.3 to 27.8, ranking #42 overall.
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.
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 44.3 and ranks #42 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 2.3x cheaper per token
- 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 MAI-Code-1.1-Flash
- you want predictable pricing at $0.20/M input and $1.20/M output
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Luna · 2 for MAI-Code-1.1-Flash
GPT-6 Luna and MAI-Code-1.1-Flashdon'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) is 2.0x cheaper than MAI-Code-1.1-Flash ($0.20/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.4x cheaper than MAI-Code-1.1-Flash ($1.20/1M tokens).
In conclusion, MAI-Code-1.1-Flash is more expensive than GPT-6 Luna.*
* 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 MAI-Code-1.1-Flash's 256,000 tokens. Only GPT-6 Luna specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both GPT-6 Luna and MAI-Code-1.1-Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Luna
MAI-Code-1.1-Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-6 Luna was released on 2026-09-22, while MAI-Code-1.1-Flash was released on 2026-08-11.
GPT-6 Luna is 1 month newer than MAI-Code-1.1-Flash.
Sep 22, 2026
1 weeks ago
1mo newerAug 11, 2026
1 months ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while MAI-Code-1.1-Flash'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 MAI-Code-1.1-Flash's cutoff date.
May 2026
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Provider Availability
GPT-6 Luna is available from OpenAI. MAI-Code-1.1-Flash is available from GitHub Copilot.
GPT-6 Luna
MAI-Code-1.1-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and MAI-Code-1.1-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs MAI-Code-1.1-Flash.