Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...
At a glance
- Context window
- 262Ktokens
- Max output
- 236Ktokens
- Knowledge to
- —
- Released
- 2026
Capabilities
Benchmarks
- Coding index
- 39
Standard evaluations
| Benchmark | Score | Tasks |
|---|---|---|
| gpqa_diamond | 0.74 | 3,552 |
| tau_bench_verified_airline | 0.68 | 1,044 |
Source: Artificial Analysis · as of Sep 16, 2026
Performance
Reference uptime
100%
Median latency
1,048 ms
Throughput
26.1 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
- #46
- Rank change, 7 days
- 0
Daily tokens · 90 days
47.4B
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="google/gemma-4-26b-a4b-it",
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.