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Qwen/Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 is the Qwen3's new model with scaling the thinking capability of Qwen3-235B-A22B, improving both the quality and depth of reasoning.

ReasoningTool callingCachingJSON schema
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Specifications

Context window262K tokens
Max outputN/A
API typechat
AddedMay 27, 2026
Model IDdeepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507
Data retentionNo
Used for trainingNo
Provider location🇺🇸 US
Privacy policyDeepInfra Privacy Policy→

Benchmarks

Benchmarks haven't been published yet for this exact variant.

Some variants (region-specific deployments, highspeed tiers) share benchmarks with their base model. Check the base model page or the DeepInfra Inc. models overview.

Pricing

Prices updated July 24, 2026
Input / 1M
$0.23
Output / 1M
$2.30
Cache write
N/A
Cache read / 1M
$0.20
Estimated cost
100K input + 10K output$0.0460
1M input + 100K output$0.46
10M input + 1M output$4.60

Requesty charges exactly what the upstream provider charges, no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to deepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507.

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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="deepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

print(response.choices[0].message.content)

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Frequently asked questions

How much does Qwen/Qwen3-235B-A22B-Thinking-2507 cost?
Qwen/Qwen3-235B-A22B-Thinking-2507 is priced at $0.23 per million input tokens and $2.30 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of Qwen/Qwen3-235B-A22B-Thinking-2507?
Qwen/Qwen3-235B-A22B-Thinking-2507 has a context window of 262K tokens. That's roughly 350 words of input you can fit in a single prompt.
What can Qwen/Qwen3-235B-A22B-Thinking-2507 do?
Qwen/Qwen3-235B-A22B-Thinking-2507 supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use Qwen/Qwen3-235B-A22B-Thinking-2507 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "deepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run Qwen/Qwen3-235B-A22B-Thinking-2507 through Requesty?
Yes. Qwen/Qwen3-235B-A22B-Thinking-2507 runs through Requesty's OpenAI-compatible API, served from DeepInfra Inc.. You do not host the model yourself: point base_url at Requesty, set the model to "deepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Access Qwen/Qwen3-235B-A22B-Thinking-2507 through Requesty

One API key, 600+ models, OpenAI-compatible. No markup on provider prices, automatic failover, and smart caching built-in.

All DeepInfra Inc. models