Qwen3 235B A22B Instruct 2507
qwen/qwen3-235b-a22b-instruct-2507The open MoE workhorse of the Qwen family, 235B parameters, 22B active, priced for production volume.
Model overview
Context window
256K
tokens
Input price
—
quoted on request
Output price
—
quoted on request
Weekly volume
—
tokens / week
Open weights
Yes
self-hostable
Capabilities
5
of 11 tags
Description
Qwen3 235B A22B Instruct 2507 is a language model from Alibaba Qwen. Webparam does not stock this model yet and can source it on request — tell us what you need it for and we will come back with availability and a price. Alibaba Qwen’s stated focus is the broadest open model family in the world. Its mean it can also be self-hosted under its licence.
Capabilities
- Tool calling
- Calls functions you define and returns their arguments as structured data, the basis of agents.
- JSON mode
- Constrains the response to valid JSON matching a schema you supply.
- Streaming
- Emits tokens as they are generated, so answers appear progressively rather than all at once.
- Open weights
- The parameters are published, so the model can be inspected, fine-tuned and self-hosted under its licence.
- Long context
- Built for inputs well beyond the mainstream window, whole repositories, archives or corpora.
Strengths & weaknesses
Strengths
- Open weights with permissive licence
- MoE efficiency keeps prices low
- 256K context standard
Weaknesses
- Long product name confuses model pickers
- Creative writing trails flagships
Pricing
Free| Rate | Price | Unit |
|---|---|---|
| Input | $0.00 | per 1M tokens |
| Output | — not charged | — |
Free at the point of use; fair-use rate limits apply to the free tier. Illustrative placeholder pricing.
Context window
256Ktokens
covers prompt and response together, so a long input leaves less room for the answer.
Supported features
| Feature | Support |
|---|---|
| Tool calling | Supported |
| JSON mode | Supported |
| Streaming | Supported |
| Vision input | Not supported |
| Audio input | Not supported |
| Long context | Supported |
| Open weights | Supported |
| Reasoning | Not supported |
| Fine-tunable | Not supported |
| Batch | Not supported |
| Caching | Not supported |
Example use cases
High-volume pipelines
Open weights with permissive licence
Self-host candidates
MoE efficiency keeps prices low
RAG generation
256K context standard
Comparison
| Attribute | Qwen3 235B A22B Instruct 2507 | DeepSeek V3.2 | Llama 4 Maverick |
|---|---|---|---|
| Context window | 256K | 128K | 1M |
| Input price | $0.00 | $0.00 | $0.00 |
| Output price | — not charged | — not charged | — not charged |
| Tool calling | Supported | Supported | Supported |
| JSON mode | Supported | Supported | Supported |
| Vision input | Not supported | Not supported | Supported |
| Open weights | Supported | Supported | Supported |
| Prompt caching | Not supported | Supported | Not supported |
Best value in each row is highlighted. Illustrative placeholder data.
Provider information
View Alibaba Qwen →Alibaba Qwen · 通义千问 · Hangzhou, China · est. 2023 (Model lab; parent Alibaba founded 1999)
Alibaba's Qwen family spans every size class from edge models to frontier MoE systems, most released with open weights. Its breadth (chat, coding, vision, embeddings) and permissive licensing made it the default base model for much of the global open-source ecosystem.
Recent releases
Documentation
Frequently asked questions
Input is billed at $0.00 per 1M tokens, and there is no separate output charge. Every figure on this page is an illustrative placeholder.