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glm-5.3-flash

Z.AI/Open weights/3 providers

GLM-5.3-Flash is a native multimodal model from Z.ai, suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead. Accepts text, image and video input.More

Which id to call

glm-5.3-flash

Requesty routes this id across every provider serving glm-5.3-flash, picking on price and health and failing over automatically. The id stays valid when a provider changes underneath it.

From /1M input

$0.14

$0.15 list

DeepInfra Inc.

Context

1.0M

131K output

Endpoints

3

1 region

Regions

1

chat

Capabilities 5/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

3 endpoints / 1 region

Providers serving glm-5.3-flash

Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.

Providers serving glm-5.3-flash, with pricing and measured performance. The best value in each column is highlighted.
RankPrivacy
1DeepInfra Inc.10% offGlobal1.0M$0.15$0.14$0.50$0.45$0.03zdr
2Novita AI10% offGlobal1.0M$0.15$0.14$0.50$0.45$0.03zdr
3Z.ai55% off until 9 Sep 2026Global1M$0.30$0.14$1.00$0.45$0.03zdr

A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.

model=

Which id to call

One base url, https://router.requesty.ai/v1, and one key for every id here.

glm-5.3-flash

Requesty routes this id across every provider serving glm-5.3-flash, picking on price and health and failing over automatically. The id stays valid when a provider changes underneath it.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="glm-5.3-flash", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

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More from Z.AI

Reference

glm-5.3-flash questions

Which providers serve glm-5.3-flash?

glm-5.3-flash is available from 3 providers through Requesty: DeepInfra Inc., Novita AI, Z.ai. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.

How much does glm-5.3-flash cost?

Pricing starts at $0.14 per million input tokens and $0.45 per million output tokens on DeepInfra Inc., the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

Is glm-5.3-flash open weights?

Yes. glm-5.3-flash is an open-weights model from Z.AI, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.

What is the context window of glm-5.3-flash?

glm-5.3-flash supports up to 1.0M tokens of context, with up to 131K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.

How do I use glm-5.3-flash with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "glm-5.3-flash" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

Should I call glm-5.3-flash by its managed id or a provider id?

Use the managed id, "glm-5.3-flash". Requesty picks which of the 3 providers serves each request based on price and health, and fails over when one degrades, so the id keeps working while the routing changes underneath it. Send a provider id like "deepinfra/glm-5.3-flash" only when you need one specific deployment and want no failover.

Route glm-5.3-flash through one endpoint

One key for 3 providers on this model and 600+ others. No markup on provider prices, automatic failover, caching built in.

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