PyPI Stats
proroklab

vmas

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
PyPI GitHub
Downloads
Day
117
Week
845
Month
3.6K
Stars
563
Forks
107
Issues
7
Version
1.5.2

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
80
Popularity
58
Adoption
35
Community
40
How the maintenance status was determined
Last commit
88 days ago
Monthly downloads
3,567
Active
Activity within 30 days
• Stable
Activity within 31-180 days
Minimal
Activity within 181-365 days, or no activity data
At Risk
No activity for > 365 days, but > 10,000 monthly downloads
Archived
Repository flagged as archived on GitHub
How the popularity category was determined
Monthly downloads
3,567
Stars
563
Stars per 1k downloads
157.84
Industry Standard
> 10,000,000 monthly downloads
Hidden Gem
< 0.5 stars per 1k downloads and > 100,000 monthly downloads
• Community Favorite
> 5 stars per 1k downloads
Rising Star
Balanced ratio of stars to downloads
Unknown
Fewer than 1,000 monthly downloads, or no star data
How download momentum is calculated
Week daily avg
121
Month daily avg
119
Momentum
—
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
Momentum not reported for packages with < 5,000 monthly downloads — percentages are noisy at low volume.
Python version support tiers
requires_python
Not specified
Cutting Edge
Minimum supported version is 3.12 or newer
Modern
Minimum supported version is 3.9, 3.10, or 3.11
Legacy
Supports 3.8 or older (or Python 2)
• Unknown
No requires_python specified or unparseable
Package does not declare a minimum Python version.
License categories
License
GPLv3
Permissive
MIT, Apache, BSD, ISC, Unlicense, CC0, etc.
• Copyleft
GPL, LGPL, AGPL, MPL, EPL, etc.
Proprietary
Commercial, all rights reserved, custom EULAs
Unknown
No license specified, or none of the above match
How the release cadence was determined
Last release
177 days ago
Total releases
28
Releases/year
8.1
Rapid
Last release within 365 days and > 12 releases/year
• Regular
Last release within 365 days
Slow
Last release 366-730 days ago
Stalled
Last release > 730 days ago, or no releases
Unknown
No usable release date available
How contributor risk was determined
Contributors
19
Monthly downloads
3,567
High Load
≤ 2 contributors and ≥ 50,000 monthly downloads
Moderate Load
< 10 contributors and ≥ 500,000 monthly downloads
Low Load
< 25 contributors and ≥ 5,000,000 monthly downloads, or sole maintainer with ≥ 10,000 monthly downloads
• Balanced
Enough contributors for the package's popularity
Unknown
No contributor data available
Engagement
51
 
Issue Burden
12.4
per 1k stars
Discussions
0.0
per 1k stars
Fork Ratio
17.8%
contrib / forks
Stale Release
89d
 
PR Velocity
Quiet
 

Weekly Downloads

GitHub Stars

Not all downloads include detailed metadata. Breakdowns reflect the subset that does.

Downloads by OS

Linux 63
Windows 3
macOS 3

Python Versions

3.11
52.2% 36
3.10
26.1% 18
3.12
17.4% 12
3.13
4.3% 3

Top Countries

1. US US
59
2. DE DE
27
3. GB GB
5
4. CN CN
2
5. AE AE
1
6. HU HU
1
7. MT MT
1
8. SG SG
1

Dependencies

6
10 optional dependencies

Used By

2

Package Information

License
GPLv3
First Release
November 22, 2022
Last Release
5 months ago
Last Commit
2 months ago
Latest Version
1.5.2
Total Releases
28
Contributors
19
Open PRs
2
Archived
No
Author
Matteo Bettini
Topics
gym gym-environment marl multi-agent multi-agent-learning multi-agent-reinforcement-learning multi-agent-simulation multi-agent-systems multi-robot multi-robot-framework multi-robot-sim multi-robot-simulator multi-robot-systems pytorch rllib simulator vectorization vectorized robotics simulation
Tracking Since
January 6, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links