Model reference · open weights
A3-Qwen3.5 is an open-weight language model from McGill-NLP. A3-Qwen3.5-9B (BF16) weighs 18.8 GB; the smallest configuration that runs it is RTX 4090 24 GB.
Summary of the McGill-NLP/A3-Qwen3.5-9B model card, 2026-10-01
What it is
| Released by | McGill-NLP |
|---|---|
| Released | 2026-04-06 |
| Parameters | 9.4B |
| VRAM | 18.8 GB for the weights |
What it runs on
| Card | Requests at once | Context max | Memory | |
|---|---|---|---|---|
| 8K each | 32K each | |||
| RTX 3060 12 GB … RTX 4060 Ti 16 GB 2 smaller cards | — | — | — | |
| RTX 3090 24 GB | 6 | 2 | 69K | 23.4 GB |
| RTX 4090 24 GB | 6 | 2 | 68K | 23.4 GB |
| RTX 5090 32 GB | 27 | 8 | all 256K | 31.0 GB |
| L40S 48 GB | 61 | 19 | all 256K | 44.0 GB |
| A100 80 GB | 154 | 48 | all 256K | 78.2 GB |
| H100 80 GB | 139 | 43 | all 256K | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | 181 | 57 | all 256K | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | 217 | 68 | all 256K | 107 GB |
| H200 141 GB | 300 | 94 | all 256K | 138 GB |
| B200 180 GB | 401 | 126 | all 256K | 176 GB |
| 2× RTX 4060 Ti 16 GB tensor parallel | 20 | 6 | 227K | 15.4 GB a card |
| 2× RTX 4090 24 GB tensor parallel | 63 | 20 | all 256K | 23.4 GB a card |
| 2× RTX 3090 24 GB tensor parallel | 63 | 20 | all 256K | 23.4 GB a card |
| Requests at once | 8K tokens each | 32K tokens each |
|---|---|---|
| 1 | 21.3 GB | 22.1 GB |
| 5 | 22.8 GB | 26.8 GB |
| 8 | 23.9 GB | 30.4 GB |
| 16 | 26.9 GB | 39.8 GB |
| 32 | 32.8 GB | 58.6 GB |
| 64 | 44.7 GB | 96.3 GB |
One card, with vLLM's small-card settings.
Builds
| Build | Params | Precision | Weights | Smallest setup |
|---|---|---|---|---|
| A3-Qwen3.5-9B (above) ↗ | 9.4B | BF16 | 18.8 GB | RTX 4090 24 GB |
| A3-Qwen3.5-4B ↗ | 5.2B | BF16 | 10.4 GB | RTX 4060 Ti 16 GB |
| A3-Qwen3.5-2B ↗ | 2.7B | BF16 | 5.4 GB | RTX 3060 12 GB |
From the model card
| 💾 Code | 📄 Paper | 🌐 Website |
|---|---|---|
| 🤗 Dataset | 🤖 Models | 📦 PyPI |
Structured Distillation of Web Agent Capabilities Enables Generalization
Xing Han Lù, Siva Reddy
A3-Qwen3.5-9B is a 9B multimodal web agent fine-tuned from Qwen/Qwen3.5-9B on A3-Synth, a synthetic dataset generated using the Agent-as-Annotators (A3) framework.
The model achieves 41.5% on WebArena, surpassing closed-source models such as Claude 3.5 Sonnet (36.0%) and GPT-4o (31.5%) under the same evaluation protocol.
Serve with vLLM:
vllm serve McGill-NLP/A3-Qwen3.5-9B --tensor-parallel-size 2 --max-model-len 65536 --enforce-eager --dtype bfloat16
| Model | Parameters | Link |
|---|---|---|
| A3-Qwen3.5-9B | 9B | McGill-NLP/A3-Qwen3.5-9B |
| A3-Qwen3.5-4B | 4B | McGill-NLP/A3-Qwen3.5-4B |
| A3-Qwen3.5-2B | 2B | McGill-NLP/A3-Qwen3.5-2B |
@misc{lu2026structured,
title={Structured Distillation of Web Agent Capabilities Enables Generalization},
author={Xing Han Lù and Siva Reddy},
year={2026},
eprint={2604.07776},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2604.07776},
}
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.