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glm-5.3-flash

glm/glm-5.3-flash

chat completionsContext: 262KToolsVisionReasoningJSON

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Official price$0.15 / $0.5 / 1M tokens

About this model

glm-5.3-flash is served through the Hermes AI OpenAI-compatible chat completions endpoint. Send the standard messages array; streaming, function tools, JSON output and reasoning settings pass through unchanged. You pay per token from prepaid credits, at the rates on the Pricing tab.

Property	Value
Model id	`glm/glm-5.3-flash`
Vendor	Zhipu
Context window	262,144 tokens
Capabilities	Tools, Vision, Reasoning, JSON, Streaming
Endpoint	`https://api.hermes-ai.net/api/v1/chat/completions`
Hermes AI price	Loading price…

Request

POST https://api.hermes-ai.net/api/v1/chat/completions · API key with the chat:create scope, or your signed-in session.

Field	Type	Notes
model	string	`glm/glm-5.3-flash`
messages	array	OpenAI chat messages: system, user, assistant and tool roles; text and image_url parts.
stream	boolean	Server-sent events with a final usage chunk.
max_tokens	integer	Output cap; also sizes the credit reservation.
tools / tool_choice	array / object	Function tools only.
response_format	object	JSON mode and JSON schema where the model supports it.
temperature, top_p, stop, seed, reasoning_effort		Passed through unchanged.

Response

Field	Notes
choices[].message / delta	The OpenAI chat completion shape.
usage	prompt_tokens, completion_tokens and prompt_tokens_details.cached_tokens as reported by the model.
hermes.charged_micros	Exact charge in USD micro-units (JSON responses). Streams expose it on GET /api/v1/chat/requests.
x-hermes-request	Request id header, also used in the billing ledger.
error.code	Documented Hermes error code; branch on it, not on the message.

Token prices

USD per 1M tokens. The tier is chosen by the prompt size of each request.

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How token billing works

When a request is accepted, Hermes reserves credits for the estimated prompt plus max_tokens of output (8,192 when you set none). Set max_tokens to keep the reservation small.
When the response finishes, the reservation is replaced by the exact charge from the usage the model reports: prompt tokens at the input rate, cached prompt tokens at the cache-read rate, completion tokens at the output rate. The remainder is released immediately.
If the model rejects the request nothing is charged. If a stream is interrupted after tokens were generated, the generated text is estimated and charged.

Code examples

Any OpenAI SDK works: set the base URL and your Hermes key.

shell

export HERMES_API_KEY=your_api_key

curl https://api.hermes-ai.net/api/v1/chat/completions \
  -H "Authorization: Bearer $HERMES_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "glm/glm-5.3-flash",
    "messages": [{"role": "user", "content": "Say hello in one sentence."}],
    "max_tokens": 200
  }'