AI model comparison

GLM 5.3 FlashX vs GPT-5.6 Luna

Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.

GLM-5.3-FlashX is the high-speed variant of Z.ai's GLM-5.3-Flash, a native multimodal model delivering inference speeds of up to 200 tokens/s.

Input / 1M
$0.37
Output / 1M
$1.25
Context
1.05M

GPT-5.6 Luna is a fast, cost-efficient model in OpenAI's GPT-5.6 series.

Input / 1M
$0.20
Output / 1M
$1.20
Context
1.05M

At a glance

Quick verdict

How the two models stack up on the things people ask about most.

Lower price

openai logo

GPT-5.6 Luna

1.4x cheaper for a typical chat

Higher intelligence score

Tie

Not enough benchmark data

Larger context window

openai logo

GPT-5.6 Luna

1.05M vs 1.05M tokens

Newer release

z-ai logo

GLM 5.3 FlashX

Released September 18, 2026

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

z-ai logoGLM 5.3 FlashXNot available
openai logoGPT-5.6 Luna37.3

Coding index

z-ai logoGLM 5.3 FlashXNot available
openai logoGPT-5.6 Luna71.4

Agentic index

z-ai logoGLM 5.3 FlashXNot available
openai logoGPT-5.6 Luna42.1

Pricing

GLM 5.3 FlashX vs GPT-5.6 Luna API pricing

Per-token API rates. Cheaper option highlighted.

Metricz-ai logoGLM 5.3 FlashXopenai logoGPT-5.6 Luna
Input tokensPer 1M tokens$0.37$0.20
Output tokensPer 1M tokens$1.25$1.20
Cached input (read)Per 1M tokens$0.09$0.02
Cache writePer 1M tokensNot available$0.25
Long-context pricingPer 1M tokens, for very long promptsSame rate at any length$0.40 in / $1.80 out above 272K
Web searchPer requestNot available$0.01

What it costs in practice

Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.

Chat message

2K in, 500 out

z-ai logoGLM 5.3 FlashX$1.37
openai logoGPT-5.6 Luna$1

Coding task

30K in, 4K out

z-ai logoGLM 5.3 FlashX$16.10$7.70 cached
openai logoGPT-5.6 Luna$10.80$5.40 cached

Long document summary

150K in, 2K out

z-ai logoGLM 5.3 FlashX$58$16 cached
openai logoGPT-5.6 Luna$32.40$5.40 cached

Specs

Context window and capabilities

How much each model can read, how much it can write, and what it accepts as input.

Metricz-ai logoGLM 5.3 FlashXopenai logoGPT-5.6 Luna
Context window1.05M tokens1.05M tokens
Max output131K tokens128K tokens
Input typesImage, Text, VideoFile, Image, Text
Output typesTextText
Reasoning effort levelsMax, High, LowMax, Extra high, High, Medium, Low, None
Default reasoning effortMaxMedium
Release dateSeptember 18, 2026July 9, 2026

Features

Supported features

API features available for each model.

Metricz-ai logoGLM 5.3 FlashXopenai logoGPT-5.6 Luna
Tool callingSupportedSupported
Structured outputsNot supportedSupported
JSON modeSupportedSupported
ReasoningSupportedSupported
TemperatureSupportedNot supported
Stop sequencesNot supportedNot supported
Deterministic seedNot supportedSupported
Verbosity controlNot supportedSupported

Our take

GPT-5.6 Luna is 1.4x cheaper for a typical chat. GPT-5.6 Luna has the larger context window (1.05M vs 1.05M tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.

FAQ

Frequently asked questions

Is GLM 5.3 FlashX or GPT-5.6 Luna cheaper?

GPT-5.6 Luna is cheaper for a typical chat (2K input tokens and 500 output tokens). GPT-5.6 Luna costs $0.20 per 1M input tokens and $1.20 per 1M output tokens, while GLM 5.3 FlashX costs $0.37 per 1M input tokens and $1.25 per 1M output tokens.

Which has a bigger context window, GLM 5.3 FlashX or GPT-5.6 Luna?

GPT-5.6 Luna supports up to 1.05M tokens of context, compared with 1.05M for GLM 5.3 FlashX.

Can I use GLM 5.3 FlashX and GPT-5.6 Luna at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see GLM 5.3 FlashX and GPT-5.6 Luna answer side by side and keep the better response.

z-ai logoopenai logo

Why choose? Ask both.

Send one prompt to GLM 5.3 FlashX and GPT-5.6 Luna at the same time. Compare the answers side by side and keep the best one.