GLM-5.3-Flash vs GPT-6 Luna
GLM-5.3-Flash and GPT-6 Luna are closely matched at 48.8 and 43.1 on the LLM Stats Score. GPT-6 Luna is 1.2x cheaper per token.
Zhipu AI · OpenAI · Updated for 2026
Which is better?
GLM-5.3-Flash and GPT-6 Luna are closely matched on the overall LLM Stats Score at 48.8 and 43.1.
In the 2 individual benchmarks reported for both models, GPT-6 Luna wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-6 Luna is roughly 1.2x 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 GLM-5.3-Flash
- you need open weights you can self-host or fine-tune
Choose GPT-6 Luna
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.2x 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
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GLM-5.3-Flash · 5 for GPT-6 Luna
GLM-5.3-Flash outperforms in 0 benchmarks, while GPT-6 Luna is better at 2 benchmarks (Agents' Last Exam, DeepSWE 1.1).
GPT-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, GLM-5.3-Flash ($0.15/1M tokens) is 1.5x more expensive than GPT-6 Luna ($0.10/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) costs the same as GPT-6 Luna ($0.50/1M tokens).
In conclusion, GLM-5.3-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 GLM-5.3-Flash's 1,048,576 tokens. GLM-5.3-Flash can generate longer responses up to 1,048,576 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and GPT-6 Luna support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
GPT-6 Luna
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while GPT-6 Luna uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while GPT-6 Luna was released on 2026-09-22.
GPT-6 Luna is 1 month newer than GLM-5.3-Flash.
Aug 26, 2026
1 months ago
Sep 22, 2026
3 weeks ago
3w newerKnowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while GLM-5.3-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 GLM-5.3-Flash's cutoff date.
—
May 2026
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. GPT-6 Luna is available from OpenAI.
GLM-5.3-Flash
GPT-6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and GPT-6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs GPT-6 Luna.