- Context
- 262Ktokens
- Released
- 8mo ago
- Size
- 2Bparameters
Qwen3.5 2B belongs to Qwen3.5, the latest model series in Alibaba's Qwen family. Alibaba's launch announcement presents the series as a natively multimodal foundation model built for high-efficiency inference, saying it delivers strong performance in reasoning, coding, agent capabilities, and multimodal understanding while reducing inference costs for real-world deployment. The maker frames the launch as advancing its work in agentic AI.
- Multimodal model
- Open weights · 2B
- Accepts images, video
- Reasoning
- Tools
How it compares
Size class
Tiny2BAn open-weight model under 5 billion parameters, small enough for phones, laptops and edge devices.
Open models of a similar size from other labs
Vs. your stack
Add the models you use to see how this one compares.
Sign inAdditional source evidence
- Source model
- alibaba/qwen3.5-2b
- Source family
- qwen
- Last updated
- 2026-03-02
- Model context
- 262K
- Model output limit
- 82K
- Open weights
- Yes
- File attachments
- Yes
- Reasoning
- Yes
- Tool calling
- Yes
- Temperature control
- Yes
Downloadable weights
Complete source record (JSON)
{
"id": "alibaba/qwen3.5-2b",
"name": "Qwen3.5 2B",
"description": "Compact Qwen3.5 multimodal model for fast chat, reasoning, and tool use",
"family": "qwen",
"last_updated": "2026-03-02",
"attachment": true,
"reasoning": true,
"tool_call": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"video"
],
"output": [
"text"
]
},
"limit": {
"context": 262144,
"output": 81920
},
"release_date": "2026-03-02",
"open_weights": true,
"license": "Apache-2.0",
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/Qwen/Qwen3.5-2B"
}
]
}Frequently asked questions
Running locally
By our estimate, Qwen3.5 2B needs about 1.9 GB at Q4, 2.9 GB at Q8 and 5.1 GB at FP16 of VRAM. That covers the weights plus headroom for a short context, and longer contexts need more.
Yes, by our estimates Qwen3.5 2B fits on an 8 GB GPU at FP16 (about 5.1 GB) and at higher precision on larger cards.
Yes, a Mac with at least 8 GB of unified memory should run Qwen3.5 2B at Q4, which needs an estimated 1.9 GB. This assumes macOS gives the GPU about 75% of unified memory.
Privacy and data
Yes, Qwen3.5 2B has open weights, so you can run it on your own hardware and keep prompts on your own machines.
Capabilities and specs
Qwen3.5 2B has a 262K token context window. It can write up to 82K output tokens per response.
Yes, Qwen3.5 2B accepts images and video as input alongside text.
Yes, Qwen3.5 2B supports tool calling (function calling), so it can request calls to tools you define.
Yes, Qwen3.5 2B has a reasoning mode.
Quality and benchmarks
Similar models from other labs include Olmo Hybrid 7B Instruct (Ai2), Olmo Hybrid 7B Think (Ai2) and Nemotron Cascade 2 30B A3B (NVIDIA). They are the closest matches by kind and release date.
Olmo Hybrid 7B InstructQwen3.5 2B vs Olmo Hybrid 7B InstructOlmo Hybrid 7B ThinkQwen3.5 2B vs Olmo Hybrid 7B ThinkNemotron Cascade 2 30B A3BQwen3.5 2B vs Nemotron Cascade 2 30B A3B
Versions and lineage
Both have a 262K token context window.
Licensing and access
Qwen3.5 2B has open weights under the Apache-2.0 license, so you can download and run it yourself.
Yes, Qwen3.5 2B is released under the Apache 2.0 license, which allows commercial use. Check the license text for attribution terms.
Basics
Qwen3.5 2B was made by Qwen. It was released on March 2, 2026.
Yes, Qwen3.5 2B has open weights, so you can run it on your own hardware without API fees.
Generated from Vertical Tabs data, updated November 10, 2026.
Discussion
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