GLM 5.3 Flash

Z.ai's efficiency tier in the GLM 5 family: a 320B Mixture-of-Experts with 18B active, text, image, and video input, 1M context, and MIT open weights.

Create with GLM 5

1 积分

What is GLM 5.3 Flash?

GLM 5.3 Flash launched August 26, 2026, after six days on OpenRouter as stealth model Ox Alpha.

01

320B total, 18B active

Only 8 of 288 experts fire per token: memory of a 320B model, compute of an 18B.

02

Natively multimodal

Vision came from the 30T-token pre-training corpus, not a retrofitted encoder.

03

Flash means cheap, not fast

Artificial Analysis measures 50.2 output tokens per second, below the 67 t/s class median.

GLM 5.3 Flash specs, size, and open-source status

Architecture, weights, and licensing from the Hugging Face model card and the zai-org/GLM-5 repository.

Model card

Architecture

Total parameters
320B

MoE, 45 layers, 8 of 288 experts.

Active parameters
18B

Compute of an 18B dense model.

Context window
1,048,576 tokens

Io Net caps at 262,144; Cloudflare 1,310,720.

Maximum output
131,072 tokens

Others list up to 1,179,648.

Modality
Text, image, video

Multimodal in, text out.

Weights and licensing

Size and license

Weights license
MIT

Commercial use and redistribution, no threshold.

Hugging Face
zai-org/GLM-5.3-Flash

A -BF16 variant and ModelScope mirror.

GitHub
zai-org/GLM-5

No standalone repo; GLM-5 is Apache-2.0.

Checkpoint size
~328 GB (FP8)

A multi-node job, not a workstation.

Serving stacks
SGLang, vLLM

Plus TokenSpeed, KTransformers, community GGUF.

Model card and OpenRouter endpoints API, August 2026.

Pricing / 04

GLM 5.3 Flash pricing: list price vs launch discount

Z.ai lists $0.15 input and $0.50 output per 1M tokens. The $0.075 / $0.25 quoted everywhere is a temporary 50% launch discount.

01

List price

$0.15

Per 1M input

Forecast your GLM 5.3 Flash cost here, not at the promotional rate.

02

List price

$0.50

Per 1M output

A steep 1:3.3 ratio — cap output first.

03

List price

$0.03

Per 1M cached input

A fifth of fresh input — what makes long context affordable.

04

Independent

$0.10

Blended price

Artificial Analysis, on a 7:2:1 cache/input/output mix.

A 2x spread for identical weights: Z.AI, Novita, and GMICloud discount; others charge list.

Benchmarks / 05

GLM 5.3 Flash benchmarks: vendor-reported and independent

Z.ai publishes its own table and picks the comparisons. The GLM 5.2 delta and Artificial Analysis survive scrutiny.

01

Z.ai-reported

Terminal-Bench 2.1

5.3 Flash84.3
Opus 4.885.0

GPT-5.6 Terra scores 87.4; the gap widens on hard tasks.

02

Z.ai-reported

DeepSWE v1.1

5.3 Flash63.4
GLM 5.246.2

Same family and method, a tenth of the price. AutomationBench: 48.8 vs 26.2.

03

Z.ai-reported

OfficeQA Pro

5.3 Flash62.4

Document and visual reasoning, reported ahead of Opus 4.8.

04

Artificial Analysis

57

Intelligence Index

Independent, against a ~27 median for similar open-weight models.

The most reliable GLM 5.3 Flash benchmark is your own backlog.

Capabilities / 06

What GLM 5.3 Flash can do

Built for agent harnesses: reasoning control, tools, structured output, and streaming over a million-token window.

01

Reasoning with effort control

On by default, with an adjustable effort level.

02

Function calling

Tools and tool choice; your app still validates every action.

03

Structured output

A response-format constraint returns parseable JSON.

04

Streaming responses

A 1.47s time to first token beats the median; throughput does not.

05

Image and video input

Paste a screenshot, diagram, or screen recording with your prompt.

06

Million-token context

The $0.03 cached-input rate keeps later turns cheap.

Comparison / 07

GLM 5.3 Flash vs DeepSeek V4 Flash

Both are cheap tiers of a frontier family shipping MIT weights. They split on modality, reasoning, and hardware.

Z.ai

GLM 5.3 Flash

Architecture
320B / 18B active

Hybrid KDA plus NoPE sparse MLA attention.

Input
Text, image, video

Natively multimodal.

Context / output
1M / 131K

Output ceiling varies by provider.

List price
$0.15 / $0.50

Before the launch discount.

Self-hosting
~328 GB FP8

MIT, but a multi-node job.

DeepSeek

DeepSeek V4 Flash

Architecture
284B / ~13B active

Non-reasoning by default.

Input
Text only

Screenshots need transcribing first.

Context / output
1M / 384K

Far larger response budget.

List price
$0.14 / $0.28

First-party, a flatter 1:2 ratio.

Self-hosting
MIT weights

Smaller slice, cheaper to serve.

Both are in the glm5.app model list, so one prompt runs through each.

Release timeline / 08

GLM 5.3 Flash release timeline, from Ox Alpha to open weights

Six days as an anonymous stealth model, then a full open-weight launch.

01

Aug 20 — Ox Alpha appears

`stealth/ox-alpha` lands on OpenRouter with no disclosed provider, free per token.

02

Aug 20-26 — agent tools pile in

The five heaviest consumers are agentic coding tools; OpenCode lists it free.

03

Aug 26 — GLM 5.3 Flash launches

Z.ai confirms the Ox Alpha lineage; model card, MIT weights, and pricing land together.

04

The preview ran on Chinese chips

A custom SGLang-derived engine, reported at roughly 3x. Vendor undisclosed.

05

Weights shipped on Hugging Face

`zai-org/GLM-5.3-Flash` plus a BF16 variant and ModelScope mirror. No GitHub repo.

06

Where the news breaks

OpenRouter first on pricing, Hugging Face on quantizations. For field reports, Reddit still says Ox Alpha.

Who it is for / 09

Who uses GLM 5.3 Flash?

Teams paying flagship rates for work that never needed flagship depth — and where it is wrong.

01

High-volume agentic coding

Tool calling at a tenth of the GLM 5.3 token price makes long agent loops affordable.

02

Repository-scale work

A million-token window keeps a codebase resident, so cross-file questions skip retrieval.

03

Visual debugging

Broken layouts, reproduction recordings, schemas in diagrams.

04

Teams pricing Z.ai against rivals

Compare against DeepSeek V4 Flash and Qwen in glm5.app Chat.

05

Self-hosters with a cluster

MIT weights and vLLM support are real, but 328 GB of FP8 rules out one box.

06

Not for latency-critical UIs

At ~50 output tokens per second it trails most price peers.

How to use GLM 5.3 Flash / 10

How to use GLM 5.3 Flash

Three routes: free browser chat, the glm5.app API, or the MIT weights on your own hardware.

01
01

Chat with GLM 5.3 Flash free

Pick GLM 5.3 Flash in Chat and attach screenshots. New accounts get free credits.

02
02

Call the glm5.app API

Send OpenAI-compatible requests to `https://glm5.app/api/v1` with model ID `glm-5.3-flash`.

03
03

Or self-host the weights

Pull `zai-org/GLM-5.3-Flash` and serve it with SGLang or vLLM — ~328 GB in FP8.

Integration specimen

Start with the GLM 5.3 Flash API

An OpenAI-compatible Chat Completions endpoint. Use model ID `glm-5.3-flash` at `https://glm5.app/api/v1`.

Open API documentation
Request previewcurl
curl https://glm5.app/api/v1/chat/completions \
  -H "Authorization: Bearer $GLM5_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm-5.3-flash",
    "messages": [{
      "role": "user",
      "content": "Read this stack trace and name the failing call site."
    }],
    "stream": true
  }'

GLM 5.3 Flash FAQ

Ox Alpha, pricing, benchmarks, parameters, Hugging Face, vLLM, DGX Spark, and DeepSeek V4 Flash.

Is GLM 5.3 Flash the same model as Ox Alpha?

Yes — it ran as `stealth/ox-alpha` for six days from August 20, 2026. Saved Ox Alpha chats are remapped automatically.


Is GLM 5.3 Flash the same as GLM 5.3?

No — different tiers, roughly a 10x price gap. Flash is the 320B-A18B multimodal model; GLM 5.3 is the text flagship.


What is GLM 5.3 Flash pricing?

Z.ai lists $0.15 per 1M input, $0.03 cached, $0.50 output. The quoted $0.075 / $0.25 is a temporary 50% launch discount.


Is GLM 5.3 Flash free?

The Ox Alpha preview was free; it is metered now. You can still try it free in glm5.app Chat.


How many parameters does GLM 5.3 Flash have, and how big is it?

320B total, 18B active per token, 45 layers routing 8 of 288 experts. The FP8 checkpoint is ~328 GB.


Is GLM 5.3 Flash on Hugging Face and GitHub?

Weights are on Hugging Face at `zai-org/GLM-5.3-Flash` under MIT. No dedicated GitHub repo — recipes live in `zai-org/GLM-5`.


Can I run GLM 5.3 Flash on vLLM or a DGX Spark?

vLLM, SGLang, TokenSpeed, and KTransformers are supported. 328 GB will not fit one DGX Spark; community reports cluster two at 4-bit.


GLM 5.3 Flash vs DeepSeek V4 Flash — which should I use?

Flash for visual input or deliberation; DeepSeek V4 Flash for a flatter 1:2 ratio or 384K output.


What does Reddit say about GLM 5.3 Flash?

Most hands-on reporting sits under the preview name, so search Reddit for Ox Alpha instead.


Start here

Start with GLM 5.3 Flash today

Run your hardest task through GLM 5.3 Flash free in the browser, then wire the model ID into your pipeline.