GLM-5.3
Z.ai
Z.ai's GLM-5.3 reasoning model with a context window of about 1M tokens.
Reasoningnewus-eu-hosted
zai-org/glm-5.3
Also callable as glm-5.3
Call it
Base URL https://api.thetoken.dev/v1, your API key in TOKEN_API_KEY. This model reasons before it answers; stream the response to see output as it arrives.
from openai import OpenAIimport os
client = OpenAI(base_url="https://api.thetoken.dev/v1", api_key=os.environ["TOKEN_API_KEY"])stream = client.chat.completions.create( model="zai-org/glm-5.3", messages=[{"role": "user", "content": "Explain failover in one sentence."}], stream=True,)for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="")import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.thetoken.dev/v1", apiKey: process.env.TOKEN_API_KEY });const stream = await client.chat.completions.create({ model: "zai-org/glm-5.3", messages: [{ role: "user", content: "Explain failover in one sentence." }], stream: true,});for await (const chunk of stream) process.stdout.write(chunk.choices[0]?.delta?.content ?? "");curl https://api.thetoken.dev/v1/chat/completions \ -H "Authorization: Bearer $TOKEN_API_KEY" \ -H "Content-Type: application/json" \ -d '{"model": "zai-org/glm-5.3", "messages": [{"role": "user", "content": "Explain failover in one sentence."}]}'import anthropicimport os
client = anthropic.Anthropic(base_url="https://api.thetoken.dev", api_key=os.environ["TOKEN_API_KEY"])message = client.messages.create( model="zai-org/glm-5.3", max_tokens=1024, messages=[{"role": "user", "content": "Explain failover in one sentence."}],)print(message.content)from langchain_openai import ChatOpenAIimport os
llm = ChatOpenAI(model="zai-org/glm-5.3", base_url="https://api.thetoken.dev/v1", api_key=os.environ["TOKEN_API_KEY"])print(llm.invoke("Explain failover in one sentence.").content)Providers
Requests go to the first provider and move down the list if it fails. TOKEN's price applies whichever provider serves the request.
| # | Provider | Precision (as the provider states it) | Data location | us-eu-hosted |
|---|---|---|---|---|
| 1 | Fireworks AI | FP8 native · checked October 19, 2026 | Not stated | No |
| 2 | Novita AI | FP8 native · checked October 19, 2026 | US | Yes |
| 3 | Z.ai | NATIVE native · checked October 19, 2026 | SG | No |
Performance
Measured on TOKEN's streamed requests; shown from 10 requests in a window.
| Window | TTFT p50 | TTFT p90 | Output speed p50 | Output speed p90 |
|---|---|---|---|---|
| Last 24 hours | … | … | … | … |
| Last 7 days | … | … | … | … |
TTFT is the time from TOKEN receiving the request to the first token. Output speed is tokens per second after the first token. p50 is the median; p90 is the time 9 in 10 requests beat.
Availability
Request success: the share of real requests answered, after any failover; errors count against it. Last 30 days, one bar per day:
- 24 hours: …
- 7 days: …
- 30 days: …
Endpoint availability: a request to this model every 5 minutes from outside our infrastructure (Better Stack), on the status page. Method: Reliability.
Capabilities
| Input | text |
|---|---|
| Output | text |
| Reasoning | Yes, adjustable effort |
| Tool calling | Yes |
| Structured output (JSON schema) | Yes |
| Maximum output | 128K |
| Context window | 1,040,000 tokens |
As stated by Z.ai, checked October 24, 2026: docs.z.ai, docs.z.ai, huggingface.co.
Questions
Who makes GLM-5.3?
GLM-5.3 is made by Z.ai and was released on August 18, 2026. TOKEN serves the maker's released weights through upstream providers; it does not train or modify the model.
What is the context window of GLM-5.3?
1,040,000 tokens (1M). The maker states a maximum output of 128K tokens.
At what precision does TOKEN serve GLM-5.3?
The first provider in the routing order serves FP8, the maker's own native release format. TOKEN never routes to a quantized copy; a provider that does not state its precision is used only as a labelled backup.
Which providers serve GLM-5.3 on TOKEN?
Fireworks AI, Novita AI and Z.ai, in that routing order. If one fails, the request moves to the next.
How much does GLM-5.3 cost?
$1.54 per 1M input tokens and $4.84 per 1M output tokens (cached input $0.29), the same whichever provider answers. You pay from prepaid credit in USD; each top-up carries a 5.5% credit purchase fee, shown at checkout.
Does GLM-5.3 support tool calling, images or reasoning?
Tool calling: Yes. Image input: No. Reasoning: Yes, with adjustable effort. Structured (JSON schema) output: Yes.
Where are my requests processed?
At the provider that answers: not stated by the provider, US and SG. Keys in the us-eu-hosted group only use US and EU hosts.
Does TOKEN store my prompts or responses?
No. TOKEN keeps token counts and request metadata for billing and logs, not the content of prompts or responses. See the privacy policy.
What happens if a provider of GLM-5.3 fails?
TOKEN retries the request on the next provider in the routing order, up to three times, without any change on your side.
Will GLM-5.3 be retired without notice?
No. TOKEN gives at least 30 days of notice before a model is retired.