Can I run Qwen3 235B A22B locally?

No. The weights are not publicly released, so the model is API-only and cannot be self-hosted.

What does it cost and how long is the context?

Pricing is $0.45 per million input tokens and $1.82 per million output tokens, with a 131,072-token context window.

What is the difference between thinking mode and non-thinking mode?

The model can switch between a slower, chain-of-thought reasoning mode suited to math and complex problems, and a faster direct-response mode for simpler tasks — both available within the same model.

Qwen3 235B A22B

1456°

#llm #qwen #reasoning #math #coding #research

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Guides for this model

Open weights vs open source vs API-only: what you are actually allowed to do

How to choose an AI model in October 2026: the closed source news, then the open weights worth downloading

What is a GGUF file? Quantized models explained (Q4, Q8, fp8, NF4)

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Qwen | 131,072 token context | $0.45/M input, $1.82/M output. Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...

Captain's notes

Written by Captain, the house editor

Notes from 2026-10-13

Qwen3 235B A22B is a mixture-of-experts model from Qwen that runs 22 billion parameters per forward pass despite a 235B total parameter count, keeping inference costs reasonable for its capability tier. Its headline feature is a built-in toggle between a deliberate thinking mode for hard reasoning tasks and a faster non-thinking mode for everyday work. At under $2 per million output tokens it sits well below most frontier-class models.

Known for

Hybrid thinking/non-thinking modes switchable within a single deployment
MoE architecture: 235B total params, only 22B active per pass
Strong on complex reasoning and math problems
Competitive output pricing for a model of this capability
128k token context window

Watch out for

Weights are not public; you are renting access via API, not running it yourself.
131k context is solid but falls short of the 200k+ long-context tier.
Thinking mode increases output token count, so costs climb on complex queries.

Best for

Prompts to try

Multi-step logic puzzle

Five people each own a different pet and drink a different beverage. Use the following clues to determine who owns the fish: the person who drinks tea lives next to the cat owner; the dog owner drinks coffee; the person in the middle house drinks milk; the bird owner lives in the first house; the fish owner does not drink water. Show your reasoning step by step.

Competitive math problem

A sequence is defined by a(1) = 1, a(2) = 1, and a(n) = a(n-1) + a(n-2) + n for n ≥ 3. Find a closed-form expression or recurrence solution for a(n), and compute a(10). Show all working.

Architecture trade-off analysis

I need to store 50 million user events per day and query them for both real-time dashboards and monthly aggregations. Compare a columnar data warehouse approach against a time-series database for this workload. Cover write throughput, query latency, cost at scale, and operational complexity. Give a concrete recommendation.

Compare with

Qwen3 30B A3B Thinking 2507
API-only model
81,920 token context · $0.20/M input, $2.40/M output
Qwen3 VL 235B A22B Thinking
API-only model
131,072 token context · $0.40/M input, $4.00/M output
Qwen3.8 Max (0902)
API-only model
1,000,000 token context · $2.00/M input, $6.00/M output
Qwen3 VL 32B Instruct
API-only model
131,072 token context · $0.10/M input, $0.42/M output

More text models from qwen

Questions people ask

Can I run Qwen3 235B A22B locally?: No. The weights are not publicly released, so the model is API-only and cannot be self-hosted.
What does it cost and how long is the context?: Pricing is $0.45 per million input tokens and $1.82 per million output tokens, with a 131,072-token context window.
What is the difference between thinking mode and non-thinking mode?: The model can switch between a slower, chain-of-thought reasoning mode suited to math and complex problems, and a faster direct-response mode for simpler tasks — both available within the same model.

Captain's verdict
A rare case where MoE economics and a genuine reasoning mode land in the same model at a price that does not sting.

Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.

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Updated Oct 22, 2026

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This model has no popularity data from any source yet, so it carries a stand-in number below 7,000° that keeps the lists complete. It never ranks above a model with data. The breakdown appears here as soon as a source reports it.

Glossary: the terms used here

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Full model (checkpoint): The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
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Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

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