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GLM 5 Turbo API: toman pricing and code

z-ai/glm-5-turbo

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Input · per 1M tokens
348,150 toman
Output · per 1M tokens
1,160,500 toman
One 1,000-word request ≈
1,961 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 69,630 toman / 1M.Pricing and top-ups

GLM 5 Turbo example: JSON output against a schema

The example is picked from this model's own capabilities. Drop in your key and it runs as is.

from openai import OpenAI
import json

client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")

schema = {
    "name": "ticket",
    "schema": {
        "type": "object",
        "properties": {
            "category": {"type": "string", "enum": ["fani", "mali", "forush"]},
            "priority": {"type": "integer", "minimum": 1, "maximum": 5},
            "summary": {"type": "string"},
        },
        "required": ["category", "priority", "summary"],
        "additionalProperties": False,
    },
    "strict": True,
}

resp = client.chat.completions.create(
    model="z-ai/glm-5-turbo",
    messages=[{"role": "user", "content": "Ticket: "For two days I cannot download my invoice and I was charged twice.""}],
    response_format={"type": "json_schema", "json_schema": schema},
)
print(json.loads(resp.choices[0].message.content))

What is GLM 5 Turbo good for?

GLM 5 Turbo comes from Z.ai (GLM); in uttapen you reach it with the model id "z-ai/glm-5-turbo". It accepts up to 202,752 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 131,072 tokens. On price it sits in the "mid-range" band — cheaper than 265 and dearer than 141 of the other paid models in the catalogue.

What it can do beyond plain text: it supports tool calling, so it can invoke your own functions with valid arguments; it returns schema-valid JSON through response_format, ready to hand to your code; it has a reasoning mode that pays off on multi-step problems, maths and debugging. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper. Keep in mind that reasoning tokens are output tokens and do appear on the bill.

Pricing is 348,150 toman per 1M input tokens and 1,160,500 per 1M output tokens. A 1,000-word round trip on GLM 5 Turbo lands near 1,961 toman. It supports cached input: repeated context is billed at 69,630 toman per 1M, which matters a lot if your system prompt is long. You are always charged for the usage the request actually reported, never for the estimate, and a failed request costs nothing.

The closest alternative with the same capabilities from a different provider is GPT-3.5 Turbo 16k: GLM 5 Turbo works out roughly 1.3× cheaper, and its context window is larger. Both run on the same key and the same code, so trying the other one is a single string change.

To make the figure concrete: 100,000 toman of credit buys roughly 51 thousand-word requests on GLM 5 Turbo, and every 1,000 toman is about 510 words of round trip. A job with one million input tokens and one million output tokens comes to 1,508,650 toman in total. Filling this model's 202,752-token window costs 70,588 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "z-ai/glm-5.1", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 1.3× dearer (1,961 against 1,509 toman). The context windows differ too: 202,752 against 204,800 tokens. Maximum answer length differs as well: 131,072 against 128,000 tokens. On parameters the other takes frequency_penalty, logit_bias, logprobs, min_p.

Z.ai (GLM) has 17 models in our catalogue; the cheapest is GLM Flash Latest at 116 toman per thousand words and the dearest GLM 5.3 at 2,188. Among the less common parameters it accepts top_k — all through the standard request body. It does not support seed, structured_outputs, which most models here do, so test before switching if your code relies on them. By context size the nearest option from another provider is MiniMax M2 at 204,800 tokens.

Good fits: product chatbots and internal assistants, where cost and quality have to balance, logic puzzles and code review, agents that reach out to APIs and databases, extracting data against a fixed schema, analysing a long document or codebase in one request.

Provider's own description

GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows...

Three real jobs, priced on this model

Each figure is derived from the prices above and moves when they do.

JobTokensCost
One chat turn with a medium history1,500 in + 400 out986 toman
Summarising a ten-page document4,000 in + 600 out2,089 toman
Classifying a thousand short rows120,000 in + 20,000 out64,988 toman

Frequently asked

How do I call GLM 5 Turbo from Iran?
Sign up with your mobile number, top the wallet up in toman, create an API key, then in the official OpenAI SDK point base_url at https://api.uttapen.ir/v1 and set model to "z-ai/glm-5-turbo". Nothing else in your code changes.
What does GLM 5 Turbo cost in toman?
348,150 toman per 1M input tokens and 1,160,500 toman per 1M output tokens; a 1,000-word request is around 1,961 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does GLM 5 Turbo take?
Up to 202,752 tokens per request, roughly 152k words. A single answer can reach 131,072 tokens.
Does GLM 5 Turbo support streaming and tool calling?
Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Structured output through response_format works too.