# GLM 5.3 — API, capabilities & pricing | Y-API

> GLM 5.3 builds on the GLM 5.2 base model with revised post-training for complex coding and long-running tasks. OpenRouter documents always-on reasoning for this entry, a meaningful distinction when budgeting output.

This is the markdown representation of https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3. Generated by `scripts/generate-seo-assets.mjs` from the same copy the page renders — do not edit by hand.

Model ID: `z-ai/glm-5.3`

Sources reviewed: 2026-10-04. Y-API catalog snapshot: 2026-10-04.

## Choosing this model

Selection advice by Y-API. The checks below are suggested evaluations, not published test results.

### Where to start

Consider it for bug fixes that span implementation, tests and a final review. Supply the acceptance conditions first and evaluate whether the patch actually meets them without weakening tests.

### What to watch for

Do not assume a no-thinking switch is available: the reference page says reasoning cannot be disabled. Budget for reasoning and final text, and inspect truncation when the visible answer is unexpectedly empty.

## Model specifications

These are OpenRouter model-level specifications, not a Y-API compatibility test. A particular route may accept fewer input formats, parameters or tokens. Verify the features you need with a small request; a successful text response does not validate vision or tool calling.

| Field | Value |
| --- | --- |
| Context window | 1,048,576 tokens |
| Input | Text |
| Output | Text |
| Listed on OpenRouter | 2026-08-18 |
| Parameters listed by OpenRouter | `frequency_penalty`, `include_reasoning`, `logit_bias`, `logprobs`, `max_tokens`, `min_p`, `parallel_tool_calls`, `presence_penalty`, `reasoning`, `reasoning_effort`, `repetition_penalty`, `response_format`, `seed`, `stop`, `structured_outputs`, `temperature`, `tool_choice`, `tools`, `top_k`, `top_logprobs`, `top_p` |

## Estimate your cost

| Price basis | Input / 1M tokens | Output / 1M tokens |
| --- | --- | --- |
| Account credit | $1.40 | $5.00 |
| Cash equivalent | $0.14 | $0.50 |

$1 paid adds $10 of credit. Cash equivalent = credit consumed ÷ 10; this is not the model publisher’s list price.

Input tokens / request: 1000. Output tokens / request: 500. Number of requests: 1000.

Estimated credit consumed: $3.90. Estimated cash equivalent: $0.39.

Illustrative token budget, not measured usage or a quote. Includes input and output; excludes separate media charges, cache discounts and retries. Include billed reasoning tokens in your output budget where applicable. Actual billing follows usage returned by the service.

### Same token budget, different models

| Model | Estimated credit consumed | Estimated cash equivalent |
| --- | --- | --- |
| [GLM 5.3](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3) | $3.90 | $0.39 |
| [GLM 5.2](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.2) | $3.60 | $0.36 |
| [GLM 5.3 Flash](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3-flash) | $0.40 | $0.04 |

## Use the API

These minimal, text-only requests use the exact Y-API model ID. They do not demonstrate image, audio, video, file or tool support. The output limit also needs room for reasoning; an empty answer with finish_reason=length can mean the budget was exhausted.

Set the TOKEN environment variable to a key from your console. Run this on your server or locally; never expose a key in browser code or a public repository.

### A task to try

A payment webhook can be delivered twice and out of order. Propose an idempotency design and tests proving it will not credit an account twice.

```bash
curl --fail-with-body --silent --show-error --max-time 120 \
  'https://api.y-api.bestvirtualgoods.com/v1/chat/completions' \
  -H "Authorization: Bearer ${TOKEN:?Set TOKEN first}" \
  -H 'Content-Type: application/json' \
  --data-binary @- <<'JSON'
{
  "model": "z-ai/glm-5.3",
  "messages": [
    {
      "role": "user",
      "content": "A payment webhook can be delivered twice and out of order. Propose an idempotency design and tests proving it will not credit an account twice."
    }
  ],
  "max_tokens": 4096
}
JSON
```

```python
import json
import os
import sys
import urllib.error
import urllib.request

payload = {
  "model": "z-ai/glm-5.3",
  "messages": [
    {
      "role": "user",
      "content": "A payment webhook can be delivered twice and out of order. Propose an idempotency design and tests proving it will not credit an account twice."
    }
  ],
  "max_tokens": 4096
}

request = urllib.request.Request(
    "https://api.y-api.bestvirtualgoods.com/v1/chat/completions",
    data=json.dumps(payload).encode("utf-8"),
    headers={
        "Authorization": "Bearer " + os.environ["TOKEN"],
        "Content-Type": "application/json",
    },
    method="POST",
)
try:
    with urllib.request.urlopen(request, timeout=120) as response:
        result = json.load(response)
    print(json.dumps(result, ensure_ascii=False, indent=2))
except urllib.error.HTTPError as error:
    print(error.read().decode("utf-8"), file=sys.stderr)
    raise SystemExit(1)
```

### How to evaluate the result

Require a durable uniqueness constraint and an atomic state transition. Include concurrent duplicates and out-of-order delivery in the tests; an in-memory set is not enough.

## Before you choose

### Can I turn reasoning off on GLM 5.3?

The reviewed OpenRouter page says no. It lists selectable effort levels rather than a disabled mode. Y-API parameter forwarding still needs its own compatibility check.

## Sources & scope

Technical facts come from the cited model page and, where available, its linked publisher card. A card describes that checkpoint; it is not proof of the weights a gateway serves. Prices come only from the Y-API catalog. We do not claim measured latency, uptime or benchmark scores for this endpoint.

- [OpenRouter model page & specifications](https://openrouter.ai/z-ai/glm-5.3)
- [Publisher model card linked by OpenRouter](https://huggingface.co/zai-org/GLM-5.3)
- [Y-API catalog & prices (JSON)](https://y-api.bestvirtualgoods.com/models.json)

## Models to compare

Compare these alternatives on the same inputs. Their descriptions explain different roles; a lower price does not establish equivalent quality.

### [GLM 5.2](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.2)

GLM 5.2 is Z.ai’s text-reasoning model for long-horizon engineering. Its publisher highlights a million-token context and IndexShare, which reuses sparse-attention indexing work for long inputs.

### [GLM 5.3 Flash](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3-flash)

GLM 5.3 Flash introduces native multimodality to the GLM 5 series. Unlike the text-only GLM 5.3 entry, its new base architecture combines sparse and linear attention for visual and long-context workloads.

## Links

- HTML version of this page: https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3
- Site index for agents: https://y-api.bestvirtualgoods.com/llms.txt
- Full reference (single file): https://y-api.bestvirtualgoods.com/llms-full.txt
- OpenAPI 3.1 spec: https://y-api.bestvirtualgoods.com/openapi.json
- Model catalog (JSON, no key needed): https://y-api.bestvirtualgoods.com/models.json
- API base URL: `https://api.y-api.bestvirtualgoods.com/v1`
- Contact: support@bestvirtualgoods.com
- Model catalog: https://y-api.bestvirtualgoods.com/models
- Integration guide: https://y-api.bestvirtualgoods.com/docs