qwen-turbo
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks.
text → text · made by Alibaba
$0.05→$0.2per Mtok in / out
Requesty
Sold by 2 ways
| Seller | Lane | Rate |
|---|---|---|
| Requesty aggregator | alibaba | $0.05per Mtok in$0.2per Mtok out$0.05per Mtok cachedrouter.requesty.ai · read 2026-08-28 |
| ElectronHub 0 ways | $0.1per Mtok in$0.3per Mtok out | |
| ElectronHub aggregatornot on the seller's list today | standard | $0.1per Mtok in$0.3per Mtok outapi.electronhub.ai · read 2026-10-18 |
Measured 3 standings
| Place | Board | Metric | Score |
|---|---|---|---|
| 56thof 108 | Math level 5 — Epoch AI | mean_score | 56.231 |
| 271stof 306 | OTIS Mock AIME 2024-2025 | mean_score | 6.111 |
| 275thof 326 | GPQA Diamond | mean_score | 41.793 |
About
qwen-turbo — a text model from Alibaba, placed 56th of 108 on Math level 5 — Epoch AI.
It takes text and returns text, with a context window of 1,000,000 tokens. It was published in November 2024, trained on material up to April 2024. Its sellers say it can reason step by step and call a tool. The catalogue files it under reasoning. It has been measured on 3 boards, and stands best at 56th of 108 on Math level 5 — Epoch AI.
Every current figure
- Maker
- Alibaba
- Register
- model
- Takes
- text
- Returns
- text
- Context
- 1,000,000 tokens
- Longest answer
- 16,384 tokens
- Published
- November 2024
- Knowledge to
- April 2024
- Licence
- not read
- Boards
- 3
- Best place
- 56th of 108 — Math level 5 — Epoch AI
Known as 1 name
alibaba/qwen-turbo