Live your best raccoon life in this chaotic co-op sandbox for 1-4 players! Complete crazy missions, cause chaos, and outsmart a relentless Exterminator. ๐ฆ
Dumpster Gang is coming to Nintendo Switch 2 in March 2027. #IndieWorld@DumpsterGangHQ
Joining the coalition places Roboflow Labsโ work within a shared effort to advance those capabilities.
We see an opportunity to connect progress in frontier models with the breadth of tasks developers face outside the lab, and to help turn that progress into tools people can build with.
Roboflow Labs draws on what the 2M+ developers and Fortune 500 enterprises building on Roboflow are actually trying to solve.
That real-world task distribution shapes the research, benchmarks like RF100-VL, and data we bring to model builders.
More on Roboflow Labs: https://t.co/v5KcLQv4xx
Today weโre announcing that weโve partnered with NVIDIA and joined the Cosmos Coalition, a global initiative among leading AI labs, as a premiere provider of multi-modal data and post-training capabilities that advance frontier world model research.
We believe the next wave of the AI boom will be defined by what intelligence can do in the physical economy, and that vision is the bottleneck to unblock.
NVIDIA introduced the coalition in May 2026 to bring model builders, developers, and organizations building physical AI together around open world models.
The effort supports collaboration on models, research, and evaluation methods to advance systems that can understand and simulate the physical world.
More info: https://t.co/bgpK0LT8Wh
GPT-6.1 Terra beats Astra in our vision benchmarks
wtf OpenAI?
had to double-check the results
- text
- object detection
- counting
also ~47% faster and ~92% cheaper
โ leaderboards and examples
We are hosting the Visual Intelligence Summit on October 22 in SF.
The physical world is AI's biggest opportunity and the best way to advance humanity in our lifetimes. Few people are building for AI beyond the screen.
The Summit is for the people who see it differently and want to be at the frontier of bringing AI into the physical world.
If youโre building for that future, join us.
Ever wanted to know if you're cooked in an IRL game of chess? ๐
So I built Stockfish IRL. A camera watches a real board, tracks every move, and literally yells at you when you blunder.
Built with @roboflow ๐
livestream today sharing all the findings we have on using Argon for vision
TLDR: Google is back. Argon tops almost everything.
Argon is good enough that we started testing it on new areas where most VLMs aren't usable like segmentation, keypoints, and video reasoning
Exciting to have a model this good. Never been a better time to build with vision
Also, models hitting 90% on our evals means we are going to invest in expanding benchmarks. Stay tuned!
@lillyguisnet we didn't develop the COCO benchmark so no plans to expand that baseline
RF-DETR is made to be fine-tuned on custom data and not meant to be used as general detector
using VLMs to label data then train a custom RF-DETR is the way to go!
Gemini 4 Argon expands whatโs possible in computer vision
As models improve, your apps should too
Routing tasks to the right frontier or specialized model is how you can build production systems that scale with your accuracy, speed, and cost needs
Can't wait to see all the new products people ship with this one
Astra dethroned
Gemini 4 Argon is the best "vision" model
#1 for detection:
- tight, precise boxes
- dense scenes
#1 for text extraction:
- small text
- handwritten text
- complex tables
- rotated text
4ร cheaper than Astra at high
Gemini 4 Argon vs GPT-6 Astra YouTube stream
tomorrow, Oct 15th, 8 AM PT / 11 AM ET / 5 PM CET
save the time and see you tomorrow
- detection
- segmentation
- transcription
- data extraction
- efficiency and cost
what else?
link: https://t.co/Ww478jg9tb
@shelbrock_kevin@grok Try Auto-Label in Roboflow; you probably wonโt have to label something like this by hand these days. (You could also probably just hook our MCP up to Grok and let it run things for you.)
@lillyguisnet ahhhh super cool, thanks for sharing a bit more about what you're evaluating.
this is the overall score combining all evals across tasks
thanks for sharing your results! excited to see more for future models