qwen-turboAlibaba Cloud
- api
- chat
- hosting
- Singapore
- model lab
- Alibaba (Qwen)
- weights
- closed
- added
- November 2024
- model id
- alibaba/qwen-turbo
capabilities 2/8
- input
- $0.05
- output
- $0.20
- cache write
- -
- cache read
- -
worked cost
| volume | cost |
|---|---|
| 100K in + 10K out | $0.0070 |
| 1M in + 100K out | $0.0700 |
| 10M in + 1M out | $0.70 |
Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing
no measured traffic for this endpoint yet. pricing above is the provider's own
| eval | Score as a share of 100 | /100 |
|---|---|---|
| MMLU Pro | 63.3 | |
| GPQA Diamond | 41.0 | |
| LiveCodeBench | 16.3 | |
| Intelligence Index | 6.4 | |
| Humanity's Last Exam | 4.1 | |
| 5 evals | mean | 26.2 |
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 2024-11-18.
- retention
- none
- trains on prompts
- no
- hosted in
- Singapore
Terms are the provider's, not Requesty's: routing a request here puts it under them. Alibaba Cloud Privacy Policy
Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.
alibaba/qwen-turbothis id pins the alibaba cloud deployment, with no routing and no failover. the managed id on the canonical page routes across all 1 providers instead
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="alibaba/qwen-turbo", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models
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. Its unique ability to switch seamlessly between a thinking mode for complex reasoning and a non-thinking mode for efficient dialogue ensures versatile, high-quality performance. Significantly outperforming prior models like QwQ and Qwen2.5, Qwen3 delivers superior mathematics, coding, commonsense reasoning, creative writing, and interactive dialogue capabilities. The Qwen3-30B-A3B variant includes 30.5 billion parameters (3.3 billion activated), 48 layers, 128 experts (8 activated per task), and supports up to 131K token contexts with YaRN, setting a new standard among open-source models.
questions 6
How much does qwen-turbo cost?
What is the context window of qwen-turbo?
How does qwen-turbo perform on benchmarks?
What can qwen-turbo do?
How do I use qwen-turbo with the OpenAI SDK?
Can I run qwen-turbo through Requesty?
more from alibaba cloud 8
| endpoint | ctx | in /M |
|---|---|---|
| qwen3.8-flash | 1.0M | $0.16 |
| qwen3.8-max | 1.0M | $2.00 |
| qwen3.7-plus | 1.0M | $0.32 |
| qwen3.7-max | 1.0M | $2.50 |
| qwen3.6-plus | 1M | $0.50 |
| qwen3-max | 262K | $0.86 |
| qwen3-coder-plus | 1.0M | $1.00 |
| qwen3-coder-flash | 1.0M | $0.30 |
call qwen-turbo through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology