Text Generation

GLM

GLM 5.3 Flash API

GLM 5.3 Flash: multimodal reasoning, coding and tool use with a 1M-token context window. Thinking is always enabled with low, high or max effort.

24H Status Monitor

24h success rate: 97%

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Model:

glm-5.3-flash

Price: 0.28 credits per 1K input tokens · ≈ $0.0001 · 0.98 credits per 1K output tokens · ≈ $0.0005High stability with detailed usage records on the APIAny platform.

Examples

Prompt preset — no generated result yet

Model

glm-5.3-flash

Prompt309 (suggested: 2,000)

Temperature1

Sampling temperature.

Max tokens32768

1131072

Output budget includes reasoning and final answer tokens.

Reasoning effort

Optional reasoning effort. Leave unset to use the model default. Higher effort can use more tokens and time.

USD estimate ≈ $0.0165: $999 tier: $1 = 2,000 credits.

Preview

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History

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Input

0.28 credits/1K

≈ $0.0001

Output

0.98 credits/1K

≈ $0.0005

Cache

0.08 credits/1K

≈ $0.000041

Context

Max output

131k

Pricing

Model ID

Type

Quality

Price

glm-5.3-flash

Text Generation

Input tokens

0.28 credits per 1K input tokens · ≈ $0.0001

glm-5.3-flash

Text Generation

Cache read tokens

0.08 credits per 1K cached input tokens · ≈ $0.000041

glm-5.3-flash

Text Generation

Output tokens

0.98 credits per 1K output tokens · ≈ $0.0005

glm-5.3-flash

Text Generation

Minimum request

0.28 credits minimum · ≈ $0.0001

Model IDglm-5.3-flash

TypeText Generation

QualityInput tokens

Price0.28 credits per 1K input tokens · ≈ $0.0001

Model IDglm-5.3-flash

TypeText Generation

QualityCache read tokens

Price0.08 credits per 1K cached input tokens · ≈ $0.000041

Model IDglm-5.3-flash

TypeText Generation

QualityOutput tokens

Price0.98 credits per 1K output tokens · ≈ $0.0005

Model IDglm-5.3-flash

TypeText Generation

QualityMinimum request

Price0.28 credits minimum · ≈ $0.0001

API Reference

Call this model through a standard REST API. Authenticate with your API key, then pick an endpoint below to see its parameters and examples.

Authentication

Every request needs a Bearer token in the Authorization header. Create an API key in the console.

Authorization: Bearer YOUR_API_KEY

POSThttps://apiany.ai/v1/chat/completions

Request parameters

Parameter	Type	Required	Notes
`model`	string	Required	Model identifier to invoke. Use this model's ID.
`messages`	array	Required	Conversation history in OpenAI chat format (role + content).
`stream`	boolean	Optional	When true, the response streams back as server-sent events.

Request example

curl "https://apiany.ai/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "glm-5.3-flash",
  "messages": [
    {
      "role": "user",
      "content": "Rewrite the following fictional Chinese refund policy as a polite concise English customer-support reply, then provide a Chinese back-translation. Policy: 未使用的积分包可在购买后7天内申请退款；已使用的积分不退款；审核一般需要2个工作日。 Customer purchased 3 days ago and has used no credits. Do not promise approval or invent a refund arrival time."
    }
  ],
  "temperature": 1,
  "max_tokens": 32768,
  "reasoning_effort": "max"
}'

Response example

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "model": "glm-5.3-flash",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 12,
    "completion_tokens": 18,
    "total_tokens": 30
  }
}

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Parameter

Type

Required

Notes

model

string

Required

Model identifier to invoke. Use this model's ID.

messages

array

Required

Conversation history in OpenAI chat format (role + content).

stream

boolean

Optional

When true, the response streams back as server-sent events.

curl "https://apiany.ai/v1/chat/completions" \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "glm-5.3-flash", "messages": [ { "role": "user", "content": "Rewrite the following fictional Chinese refund policy as a polite concise English customer-support reply, then provide a Chinese back-translation. Policy: 未使用的积分包可在购买后7天内申请退款；已使用的积分不退款；审核一般需要2个工作日。 Customer purchased 3 days ago and has used no credits. Do not promise approval or invent a refund arrival time." } ], "temperature": 1, "max_tokens": 32768, "reasoning_effort": "max" }'

{ "id": "chatcmpl-abc123", "object": "chat.completion", "model": "glm-5.3-flash", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Hello! How can I help?" }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 12, "completion_tokens": 18, "total_tokens": 30 } }