Model reference · open weights
UI-Mate is an open-weight language model from tencent. UI-Mate-9B (BF16) weighs 18.8 GB; the smallest configuration that runs it is RTX 4090 24 GB.
Summary of the tencent/UI-Mate-9B model card, 2026-10-01
What it is
| Released by | tencent |
|---|---|
| Released | 2026-08-14 |
| 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 |
|---|---|---|---|---|
| UI-Mate-9B (above) ↗ | 9.4B | BF16 | 18.8 GB | RTX 4090 24 GB |
| UI-Mate-27B ↗ | 27.4B | BF16 | 54.7 GB | H100 80 GB |
From the model card
Show the workflow once. Let the agent adapt it to the task at hand.
Tencent HY Frontier
Project Page · GitHub · arXiv
UI-Mate-9B is an open-weight foundation GUI agent for long-horizon work across applications and operating systems. It observes live screenshots, reasons over the visible state, and produces structured keyboard and mouse actions for native desktop interaction.
It executes a task from a natural-language instruction and live screenshots alone, planning from what is currently on screen and re-planning as the interface changes.
UI-Mate is an agent checkpoint rather than a standalone visual-chat model. We recommend using the official prompt, response parser, and interaction harness from the UI-Mate repository.
| Checkpoint | Intended use |
|---|---|
| UI-Mate-27B | General computer use at 27B |
| UI-Mate-9B | General computer use at 9B |
| UI-Mate-democua-27B | Demonstration-guided computer use |
pyautogui.| Benchmark | UI-Mate-9B |
|---|---|
| OSWorld-Verified · average score | 66.2 |
| WindowsAgentArena · average score | 61.7 |
| OSWorkerBench · strict success | 34.00 |
| OSWorkerBench · progress | 66.55 |
See the project page for evaluation details and updates.
vLLM automatically downloads the checkpoint from Hugging Face Hub on first launch.
pip install -U vllm openai pillow
vllm serve tencent/UI-Mate-9B \
--trust-remote-code \
--served-model-name UI_Mate \
--port 8000 \
--tensor-parallel-size 1 \
--gpu-memory-utilization 0.85 \
--mm-encoder-tp-mode data \
--chat-template-content-format openai \
--limit-mm-per-prompt '{"image":6,"video":0}'
The default agent retains five screenshots in context. The server must therefore admit at least six images because the newest screenshot arrives before the oldest one is collapsed.
Confirm that the endpoint exposes the expected model name:
curl -s http://127.0.0.1:8000/v1/models
git clone https://github.com/Tencent/UI-Mate.git
cd UI-Mate
python examples/run_agent.py \
--base-url http://127.0.0.1:8000/v1
Run a complete recorded trajectory:
python examples/run_agent.py \
--replay \
--base-url http://127.0.0.1:8000/v1
Or provide your own screenshot:
python examples/run_agent.py \
--image /path/to/screen.png \
--instruction "Export this spreadsheet as HTML and open it in Chrome"
from agents.ui_mate_agent import UIMateAgent
agent = UIMateAgent(
base_url="http://127.0.0.1:8000/v1",
model="UI_Mate",
)
with open("screen.png", "rb") as f:
response, actions = agent.predict(
"Install the autoDocstring extension in VS Code.",
{"screenshot": f.read()},
)
print(response)
print(actions)
# Reset the interaction history before starting a new task.
agent.reset()
UI-Mate-9B is intended for research and development of screenshot-based GUI agents in controlled desktop environments.
Its behavior can be affected by application versions, screen layouts, display scaling, latency, and unexpected UI state. Benchmark performance does not guarantee reliable execution in arbitrary environments, and the model requires an external runtime to execute its predicted actions.
Computer-use agents can make mistakes, encounter prompt injection, or trigger consequential actions.
UI-Mate is released under the Apache License 2.0. Third-party components remain subject to their respective licenses. See the repository LICENSE for details.
@article{uimate2026,
title = {UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations},
author = {Tencent HY Frontier Team},
journal = {arXiv preprint arXiv:2608.15930},
year = {2026},
}
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.