APIUp to 28% cheaper than official pricesTry the API →
Hermes
Back to News

Microsoft's Mage-VL-Cowork Beats 27B Models at Desktop Control With Just 4B Parameters

Microsoft released Mage-VL-Cowork , a 4B hybrid computer-use agent under Apache-2.0. Scores 66.0% on OSWorld-Verified, best among 4B models, versus 72.4% human reference. Dynamically switches between GUI clicks ( computer_use ) and shell commands ( bash ) per turn.

Microsoft's Mage-VL-Cowork Beats 27B Models at Desktop Control With Just 4B Parameters
Source
AlphaSignal
Published
Author
AlphaSignal
Read
2 min read

Takeaways

  • Microsoft released Mage-VL-Cowork , a 4B hybrid computer-use agent under Apache-2.0.
  • Scores 66.0% on OSWorld-Verified, best among 4B models, versus 72.4% human reference.
  • Dynamically switches between GUI clicks ( computer_use ) and shell commands ( bash ) per turn.
  • Finished a LibreOffice Calc task in 39 seconds versus 9:56 for Qwen3.6-27B, 15.3x faster.
  • Trained via five-stage curriculum plus GRPO; RL alone added 10.16 points and cut tokens 25.4%.
  • Full code, evaluation harness, and docker container on GitHub .

Microsoft has released Mage-VL-Cowork , a 4-billion-parameter vision-language model that operates desktop applications through screenshots, GUI actions and shell commands. On each turn, it selects either mouse-and-keyboard control or a persistent Bash and Python environment.

The model scored 66.0% on OSWorld-Verified with a 50-step limit, the highest result among the 4B-scale models in Microsoft’s comparison and 6.4 percentage points below the 72.4% human reference. The Apache-2.0 checkpoint occupies 9.5 GB in bfloat16 and can be self-hosted. That figure covers the weights alone; total memory use also depends on the serving framework, context length and runtime overhead.

One policy, two action channels

Mage-VL-Cowork exposes two tools within a shared turn format. computer_use provides 11 GUI primitives, including pointer, click and typing operations, with coordinates normalized to [0, 999] . bash provides a persistent shell and Python environment. The host harness, which connects model outputs to the operating system, executes the selected action.

GUI-only agents repeatedly process screenshots and reproduce structured edits through clicks. Shell access gives the model a direct route for tasks such as modifying spreadsheets, transforming files and validating outputs, while the GUI remains available for applications or controls without a practical command-line interface.

A LibreOffice Calc example in Microsoft’s report shows the potential latency difference for one task: merging ranges, adding labels and a column chart, then saving the workbook.

AgentParametersStepsTimePrimary method
Mage-VL-Cowork4B639 secondsPython workbook manipulation
Qwen3.6-27B27B399 minutes 56 secondsGUI interaction

The 15.3-times speedup applies to this Calc example and should be treated as task-specific rather than a benchmark-wide latency result.

A 4B model reaches 66%

Reporting is indexed from AlphaSignal. Rights remain with the original publisher and cited sources.

Read original report

Sources

  1. 01huggingface.co
  2. 02microsoft.github.io
  3. 03github.com
  4. 04huggingface.co