glm-5.3-flashZ.AI
- endpoints
- 7
- regions
- 2
- best tok/s
- 169
- api
- chat
- released
- August 2026
- eu routing
- available
capabilities 5/8
The same weights cost 2.7x more on sference than on runware inc.. That is what the endpoints table is for.
| # | flags | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Global | 1.0M | $0.07 | $0.25 | $0.01 | 1.97s | 169.0 | zdr | ||
| 2 | Global | 1.0M | $0.15 | $0.50 | $0.03 | 1.90s | 40.0 | zdr | ||
| 3 | Global | 1.0M | $0.15 | $0.50 | $0.03 | 1.57s | 62.0 | - | zdr | |
| 4 | Global | 1.0M | $0.15 | $0.50 | $0.03 | 5.81s | 103.0 | zdr | ||
| 5 | Global | 1M | $0.15 | $0.50 | $0.03 | 5.71s | - | zdr | ||
| 6 | EU | 1M | $0.20 | $0.60 | $0.07 | 103ms | 79.0 | zdr | ||
| 7 | EU | 1.0M | $0.20 | $0.50 | $0.05 | 1.77s | 72.0 | zdr |
| provider | now | low | high | change |
|---|---|---|---|---|
| sference | 103ms | 30ms | 506ms | -82% |
| Fireworks AI | 1.57s | 1.09s | 1.54s | +8.5% |
| TensorX Ltd. | 1.77s | 999ms | 2.11s | -12% |
| DeepInfra Inc. | 1.90s | 874ms | 1.83s | -6.6% |
| Runware Inc. | 1.97s | 1.31s | 2.21s | +69% |
| Z.ai | 5.71s | 2.98s | 5.94s | +23% |
| Novita AI | 5.81s | 1.97s | 5.47s | -5.2% |
median wait before the first token lands. this is the number a user feels, and it moves with provider load through the day.
Lines are steps: each sample is one week of traffic held flat, not a slide from the week before. Click a name in the key to drop it from the plot. Measured through Sep 12.
| eval | Score as a share of 100 | /100 |
|---|---|---|
| GPQA Diamond | 91.2 | |
| Coding Index | 71.5 | |
| SciCode | 51.6 | |
| Intelligence Index | 41.9 | |
| Humanity's Last Exam | 39.9 | |
| 5 evals | mean | 59.2 |
Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2026-08-26.
glm-5.3-flashrequesty routes this id across every provider serving glm-5.3-flash, picking on price and health and failing over automatically. the id stays valid when a provider changes underneath it
Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="glm-5.3-flash", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models
GLM-5.3-Flash is a native multimodal model from Z.ai, suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead. Accepts text, image and video input.
questions 7
Which providers serve glm-5.3-flash?
How much does glm-5.3-flash cost?
Is glm-5.3-flash open weights?
What is the context window of glm-5.3-flash?
Which provider is fastest for glm-5.3-flash?
How do I use glm-5.3-flash with the OpenAI SDK?
Should I call glm-5.3-flash by its managed id or a provider id?
more from z.ai 6
| model | context | from /M | providers |
|---|---|---|---|
| glm-5.3 | 1.0M | $1.20 | 6 |
| glm-5.2-fast | 1M | $2.10 | 1 |
| glm-5.2 | 1.0M | $0.80 | 11 |
| glm-5.1 | 205K | $0.84 | 5 |
| glm-5 | 203K | $1.00 | 2 |
| glm-4.7 | 200K | $0.60 | 1 |
route glm-5.3-flash through one endpoint
One key for 7 providers on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology
