Alibaba

AQwen3.5-35B-A3BOPEN

Qwen3.5-35B-A3B (Alibaba): live API pricing, context window and the best open-source alternatives, tracked daily by olud.ai.

Context window
262K
tokens
Input price
$0.14
per M tokens
Output price
$1
per M tokens
Provider
Alibaba

Prices update automatically — checked hourly against provider list prices.

See model comparisons → Compare all model prices

Benchmarks & performance

Independent benchmark scores for Qwen3.5-35B-A3B, measured by Artificial Analysis. Higher is better. Measurement mode: Reasoning.

More intelligence per dollar than Claude Opus 5 (Fast).
For the same budget, Qwen3.5-35B-A3B delivers 7 times more capability. Open weights also mean you can self-host it and pay nothing per token.
Intelligence index29.3
GPQA84.5%
Humanity's Last Exam19.7%
Long Context Reasoning62.7%
SciCode37.7%
IFBench72.5%
τ²-Bench89.2%
Terminal-Bench Hard26.5%
💰 Blended price$0.688 / 1M tokens
📈 Value42.6 intelligence points per $
Benchmark data by Artificial Analysis

About this model

Qwen3.5-35B-A3B is an open-weight AI model by Alibaba. You can download and self-host it for free; the prices below are hosted-API list prices, tracked hourly, for when you prefer convenience over self-hosting.

Frequently asked questions

What is Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B is an AI language model from Alibaba. It is open-weight: you can download it and run it on your own hardware, for free. It scores 29.3 on the Artificial Analysis intelligence index.

Is Qwen3.5-35B-A3B free?

The weights are free and open — you can self-host Qwen3.5-35B-A3B and pay nothing per token. If you prefer a hosted API, list prices are $0.14 per million input tokens and $1 per million output tokens.

What is Qwen3.5-35B-A3B good at?

Independent benchmarks from Artificial Analysis give it GPQA 84.5%, Humanity's Last Exam 19.7%, Long Context Reasoning 62.7%, SciCode 37.7%, IFBench 72.5%, τ²-Bench 89.2%, Terminal-Bench Hard 26.5%.

Can I self-host Qwen3.5-35B-A3B?

Yes. Qwen3.5-35B-A3B has open weights, so you can download it and run it on your own GPU or server with tools like Ollama, vLLM or llama.cpp — with no per-token cost.

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