Qwen3.6 35B-A3B, the Alibaba Cloud (Qwen) model in numbers

What you need to know

Released on April 17, 2026, Qwen3.6 35B-A3B is one of the 12 Alibaba Cloud (Qwen) models tracked on this site. Its weights are published: you can download it and run it on your own servers, or use one of the 39 API providers that list it on models.dev. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money. That makes it 6 months old as of October 22, 2026.

We file it under open-weight models (68 models in this category on the site).

What it costs

Qwen3.6 35B-A3B costs $0.17 per million input tokens and $1 per million output tokens (median of 39 providers, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.005; a thousand of those tasks, $5.4.

That is in line with open-weight models, whose median output price is $1.

To estimate your own budget, use the agent cost calculator.

What do independent benchmarks say?

According to results published by Epoch AI (checked on October 22, 2026), Qwen3.6 35B-A3B has a capability index of 55.3 out of 100, computed on 4 benchmarks from our basket.

It is not among the top 30 of the weekly ranking.

• GPQA Diamond (PhD-level science questions): 84.8% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 86.7% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 20.4% — the best tracked model, GPT-6 Astra, reaches 93.7%
• Terminal-Bench (agent tasks in a terminal): 24.6% — the best tracked model, GPT-5.5, reaches 84.7%

Context and capabilities

Its context window reaches 262,144 tokens, roughly 393 pages of text at 500 words per page: enough for a long report or several contracts at once. A single answer can run to 65,536 tokens.

It accepts as input: text, image and video.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

The weights are published on Hugging Face (Qwen/Qwen3.6-35B-A3B). See also our list of open-source models.

What is it good for?

Given its category, Qwen3.6 35B-A3B is mainly aimed at projects where you want control over your data or hosting, or want to adapt the model to your field.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Comparable models

In the same category, the models closest to Qwen3.6 35B-A3B are:

• MiniMax-M3 (MiniMax, index 55.5)
• Qwen3.5 397B-A17B (Alibaba Cloud (Qwen), index 59.2)
• DeepSeek V3.2 (DeepSeek, index 59.8)
• Qwen3.5 9B (Alibaba Cloud (Qwen), index 49.6)