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Open weights, run inside a TEE. Inference happens sealed, so the prompt stays inside the enclave.
Released
Aug 2026Modalities
Text · Tool calling · Image inputBest reported price on SayGM
-2.1%In
Cached
Out
per Mtok*
Create an API key and set it as SAYGM_API_KEY in your terminal.
curl "https://api.saygm.com/v1/chat/completions" \
-H "Authorization: Bearer $SAYGM_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.3-flash-tee",
"messages": [
{
"role": "user",
"content": "Hello!"
}
]
}'SayGM's best reported rate for glm-5.3-flash-tee next to list price — 2.1% off.
Compare every GLM model across providers in our GLM pricing breakdown.
| Dimension | SayGM price | List price |
|---|---|---|
| Input | $0.146775per Mtok |
Explore the Z.ai lab and compare related models.
The best reported rate for glm-5.3-flash-tee on SayGM is $0.15 per million input tokens and $0.49 per million output tokens.
SayGM's best reported rate for glm-5.3-flash-tee is 2.1% off list price.
Yes. glm-5.3-flash-tee is served on SayGM's OpenAI-compatible chat/completions surface, so an unmodified OpenAI SDK pointed at SayGM's base URL works with it.
| Output | $0.48925per Mtok | $0.50 |
| Cache read | $0.029355per Mtok | $0.03 |
What buyers have actually paid on this model recently, across every provider and cache hits.
Input
$0.15
Cached input
$0.03
Output
$0.49
$0.50Requests are load balanced across every provider serving this model, each offering its own rate, so what you pay is a blend rather than a single number. These are the blended rates actually paid — priced at what a provider offered, capped at list.
Measured over 1 window: 291 requests and 30,056,589 input-side tokens. Most recent window closed 2026-11-13 10:39 UTC.
Every provider currently serving this model, ranked by discount.
| Provider | Discount | In | Out |
|---|---|---|---|
| Provider 1 | 2.1% off | $0.15 | $0.49 |
| Provider 2 | — | $0.15 | $0.50 |
Measured on the requests SayGM routed to this model.
Fixed-seed suites SayGM runs against this model.
What is private AI inference? →