Qwen3 235B A22B Instruct 2507 with Jev
Qwen3 235B A22B Instruct 2507 is a model from Qwen, released 2025-07-21. It costs $0.087 per million input tokens and $0.350 per million output tokens, reads up to 262K tokens of context, and writes up to 235,929 tokens in one reply. Through llm11, set model to qwen/qwen3-235b-a22b-2507.
- Input price
- $0.087 / 1M
- Output price
- $0.350 / 1M
- Context window
- 262K tokens
- Max output
- 236K tokens
- Cached input
- $0.018 / 1M
- Released
- 2025-07-21
- Accepts
- text
Read from the provider's prompt cache
Read from the live catalogue and refreshed daily. At blended list price, 82% of the 332 priced models we can call cost more.
Using Qwen3 235B A22B Instruct 2507 with Jev
Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Qwen3 235B A22B Instruct 2507 does the answering when Jev sends it work, or when you name it yourself. Qwen3 235B A22B Instruct 2507 falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool.
Jev is new, so we have not published results for Qwen3 235B A22B Instruct 2507 with and without it, and this page does not invent any. Every response comes with a receipt that names the model that answered and what it cost against your most expensive model, so you can measure the pairing on your own traffic.
What a request costs
List price arithmetic, the same sum a receipt does. llm11 adds nothing per request; the only fee is on buying credits.
| Request | Tokens in / out | One | A thousand |
|---|---|---|---|
| Short chat turn | 500 / 200 | $0.00011 | $0.114 |
| Question over retrieved documents | 4,000 / 500 | $0.00052 | $0.525 |
| Long document summary | 30,000 / 1,000 | $0.00297 | $2.97 |
Cheaper models to try
The catalogue has no benchmark score for Qwen3 235B A22B Instruct 2507, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Google Gemma 4 31B | $0.090 | $0.340 | 262K | |
| Mistral Ministral 3 8B 2512 | $0.150 | $0.150 | 262K | |
| Mistral Voxtral Small 24B 2507 | $0.100 | $0.300 | 33K | |
| Qwen Qwen3 14B | $0.120 | $0.240 | 131K |
Call it
Same OpenAI request shape. Naming the model pins it, so nothing is routed, and the answer is still checked.
python
from openai import OpenAI
client = OpenAI(base_url="https://www.llm11.com/v1", api_key="llm11_live_...")
res = client.chat.completions.create(
model="qwen/qwen3-235b-a22b-2507",
messages=[{"role": "user", "content": "Hello"}],
)More from Qwen
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Qwen3.8 Max Prime | $4.00 | $12 | 1M | |
| Qwen3.8 Omni Flash | $0.150 | $0.470 | 1M | |
| Qwen3.8 Max (0902) | $2.00 | $6.00 | 1M | |
| Qwen3.8 Flash | $0.150 | $0.470 | 1M | |
| Qwen3.8 27B | $0.045 | $4.40 | 1M | |
| Qwen3.8 2.4T A95B | $2.00 | $6.00 | 1.05M |
Questions
- What is Qwen3 235B A22B Instruct 2507 with Jev?
- Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. Qwen3 235B A22B Instruct 2507 does the answering when Jev sends it work, or when you name it yourself. Qwen3 235B A22B Instruct 2507 falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Qwen3 235B A22B Instruct 2507 a System One model?
- No. Qwen3 235B A22B Instruct 2507 answers requests. The System One model is Jev, which decides which model answers each one, so the two do different jobs and llm11 uses both.
- How much does Qwen3 235B A22B Instruct 2507 cost?
- $0.087 per million input tokens and $0.350 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00052, so a thousand of them is about $0.525. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Qwen3 235B A22B Instruct 2507 context window?
- 262,144 tokens, with up to 235,929 tokens in a single reply.
- Does Qwen3 235B A22B Instruct 2507 support tool calling and structured output?
- The catalogue lists tool calling and structured output, but it does not list reasoning controls.
- Can I use Qwen3 235B A22B Instruct 2507 through llm11?
- Yes. Set model to qwen/qwen3-235b-a22b-2507 on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Qwen3 235B A22B Instruct 2507?
- Routing decisions are made by Jev, TypeSafe AI's System One model. Qwen3 235B A22B Instruct 2507 falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool.
- What is a cheaper alternative to Qwen3 235B A22B Instruct 2507?
- Nearest in price and below it: Google Gemma 4 31B at $0.090 in and $0.340 out, Mistral Ministral 3 8B 2512 at $0.150 in and $0.150 out and Mistral Voxtral Small 24B 2507 at $0.100 in and $0.300 out. The catalogue has no benchmark score for Qwen3 235B A22B Instruct 2507, so this is a price ordering. It does not claim these answer as well.