GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while...
At a glance
- Context window
- 1.3Mtokens
- Max output
- 131Ktokens
- Knowledge to
- —
- Released
- 2026
Capabilities
Benchmarks
- Intelligence index
- 42
- Coding index
- 72
- Agentic index
- 51
Design Arena
| Category | Elo | Win rate |
|---|---|---|
| models · 3d | 1,354 | 59.5 |
| models · uicomponent | 1,339 | 55.8 |
| models · svg | 1,313 | 57.1 |
| models · gamedev | 1,312 | 47.7 |
| models · codecategories | 1,299 | 49.7 |
| models · asciiart | 1,287 | 55.9 |
| models · website | 1,285 | 48.5 |
| models · dataviz | 1,276 | 50.6 |
Standard evaluations
| Benchmark | Score | Tasks |
|---|---|---|
| gpqa_diamond | 0.86 | 594 |
| tau_bench_verified_airline | 0.75 | 100 |
Source: Artificial Analysis, Design Arena · as of Sep 16, 2026
Performance
Uptime on IranRouter
15%
Reference uptime
99.9%
Median latency
1,898 ms
Throughput
32.7 tok/s
IranRouter uptime comes from our own automated probes; the reference figures are daily measurements of this model's upstream routes. Each card shows a 30-day average, and a day without data stays empty.
Popularity
- Current rank
- #3
- Rank change, 7 days
- 0
Daily tokens · 90 days
1.6T
Ranked by daily token volume across the global model market; the figure above the chart is the daily average.
Supported parameters
Parameters this model accepts; anything else is ignored.
Quick start
from openai import OpenAI
client = OpenAI(
api_key="ir-...",
base_url="https://iranrouter.com/v1",
)
resp = client.chat.completions.create(
model="z-ai/glm-5.3-flash",
messages=[{"role": "user", "content": "سلام!"}],
)
print(resp.choices[0].message.content)Only base_url and the key change; the rest of your code stays as it is.