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roboflow
rf-detr
Python2025–2026
roboflow / rf-detr

rf-detr

RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]

AI & Machine LearningLearning & Reference
Explore on GitHubRead Hacker News discussions
3Distinct people
9Mentions
0Explicit recommenders
10.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month9 dated mentions

Observed mentions: 2025-03-21 13:07:04 UTC to 2026-06-23 12:42:41 UTC.

01232025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsMar 20252025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2025-07-01 00:00:00 UTC to 2025-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsOct 20252025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsJun 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC110
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC000
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC211
Jul 20252025-07-01 00:00:00 UTC2025-08-01 00:00:00 UTC101
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC000
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC000
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC303
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC000
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC000
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC000
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC000
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC000
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC202

What Hacker News says

9 sources
yeldarb·Jun 23, 2026
It’s a big improvement if you’re already paying them but, given their aggressive approach to licensing, I can’t imagine why anyone would choose to use an Ultralytics model on a new project in 2026. You’re just asking to be shaken down and have to pay off a large bill down the line. RF-DETR is both faster and more accurate and truly open source with an Apache 2.0 license: https://github.com/roboflow/rf-detr Full disclosure: I’m one of the co-founders of Roboflow (we made RF-DETR, wrote this blog post, and are a sub-licensor of Ultralytics’ models.)
In An Introduction to YOLO26
yeldarb·Nov 19, 2025
We (Roboflow) have had early access to this model for the past few weeks. It's really, really good. This feels like a seminal moment for computer vision. I think there's a real possibility this launch goes down in history as "the GPT Moment" for vision. The two areas I think this model is going to be transformative in the immediate term are for rapid prototyping and distillation. Two years ago we released autodistill[1], an open source framework that uses large foundation models to create training data for training small realtime models. I'm convinced the idea was right, but too early; there wasn't a big model good enough to be worth distilling from back then. SAM3 is finally that model (and will be available in Autodistill today). We are also taking a big bet on SAM3 and have built it into Roboflow as an integral part of the entire build
Read the rest
and deploy pipeline[2], including a brand new product called Rapid[3], which reimagines the computer vision pipeline in a SAM3 world. It feels really magical to go from an unlabeled video to a fine-tuned realtime segmentation model with minimal human intervention in just a few minutes (and we rushed the release of our new SOTA realtime segmentation model[4] last week because it's the perfect lightweight complement to the large & powerful SAM3). We also have a playground[5] up where you can play with the model and compare it to other VLMs. [1] https://github.com/autodistill/autodistill [2] https://blog.roboflow.com/sam3/ [3] https://rapid.roboflow.com [4] https://github.com/roboflow/rf-detr [5] https://playground.roboflow.com
In Meta Segment Anything Model 3
yeldarb·Nov 19, 2025
We (Roboflow) have had early access to this model for the past few weeks. It's really, really good. This feels like a seminal moment for computer vision. I think there's a real possibility this launch goes down in history as "the GPT Moment" for vision. The two areas I think this model is going to be transformative in the immediate term are for rapid prototyping and distillation. Two years ago we released autodistill[1], an open source framework that uses large foundation models to create training data for training small realtime models. I'm convinced the idea was right, but too early; there wasn't a big model good enough to be worth distilling from back then. SAM3 is finally that model (and will be available in Autodistill today). We are also taking a big bet on SAM3 and have built it into Roboflow as an integral part of the entire build
Read the rest
and deploy pipeline[2], including a brand new product called Rapid[3], which reimagines the computer vision pipeline in a SAM3 world. It feels really magical to go from an unlabeled video to a fine-tuned realtime segmentation model with minimal human intervention in just a few minutes (and we rushed the release of our new SOTA realtime segmentation model[4] last week because it's the perfect lightweight complement to the large & powerful SAM3). We also have a playground[5] up where you can play with the model and compare it to other VLMs. [1] https://github.com/autodistill/autodistill [2] https://blog.roboflow.com/sam3/ [3] https://rapid.roboflow.com [4] https://github.com/roboflow/rf-detr [5] https://playground.roboflow.com
In Segment Anything 3
zerojames·Jul 1, 2025
Roboflow | Solutions Architects, Implementation Engineer, Developer Advocate, Full Stack Engineers | Full-time (Remote, SF, NYC) | https://roboflow.com/careers?ref=whoishiring0725 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform [1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment. Over 1 million engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. We now host the largest collection of open source computer vision datasets and pre-trained models [2]. We are pushing forward the CV ecosystem with open source projects like RF-DETR [3] and Supervision [4]. And we've built one of the most comprehensive resources for software engineers to learn to use compu
Read the rest
ter vision with our popular blog [5] and YouTube channel [6]. We have several openings available but are primarily looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. Our engineering culture is built on a foundation of autonomy & we don't consider an engineer fully ramped until they can "choose their own loss function". At Roboflow, engineers aren't just responsible for building things but also for helping us figure out what we should build next. We're builders & problem solvers; not just coders. (For this reason we also especially love hiring past and future founders.) We're currently hiring for full-stack engineers to help build our product, field engineers that work directly with our customers to solve their business needs with computer vision, and several technical roles on the sales team. We raised our Series B round at the end of last year, led by GV. With this round, we will continue building the open source tools, platform, and community so developers and enterprises can deploy computer vision applications to production. [7] [1]: https://roboflow.com/?ref=whoishiring0725 [2]: https://roboflow.com/universe?ref=whoishiring0725 [3]: https://github.com/roboflow/rf-detr [4]: https://github.com/roboflow/supervision [5]: https://blog.roboflow.com/?ref=whoishiring0725 [6]: https://www.youtube.com/@Roboflow [7]: https://blog.roboflow.com/series-b/
In Ask HN: Who is hiring? (July 2025)
zerojames·Jun 2, 2025
Roboflow | Solutions Architects, Implementation Engineer, Developer Advocate, Full Stack Engineers | Full-time (Remote, SF, NYC) | https://roboflow.com/careers?ref=whoishiring0625 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform [1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment. Over 1 million engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. We now host the largest collection of open source computer vision datasets and pre-trained models [2]. We are pushing forward the CV ecosystem with open source projects like RF-DETR [3] and Supervision [4]. And we've built one of the most comprehensive resources for software engineers to learn to use compu
Read the rest
ter vision with our popular blog [5] and YouTube channel [6]. We have several openings available but are primarily looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. Our engineering culture is built on a foundation of autonomy & we don't consider an engineer fully ramped until they can "choose their own loss function". At Roboflow, engineers aren't just responsible for building things but also for helping us figure out what we should build next. We're builders & problem solvers; not just coders. (For this reason we also especially love hiring past and future founders.) We're currently hiring for full-stack engineers to help build our product, field engineers that work directly with our customers to solve their business needs with computer vision, and several technical roles on the sales team. We raised our Series B round at the end of last year, led by GV. With this round, we will continue building the open source tools, platform, and community so developers and enterprises can deploy computer vision applications to production. [7] [1]: https://roboflow.com/?ref=whoishiring0625 [2]: https://roboflow.com/universe?ref=whoishiring0625 [3]: https://github.com/roboflow/rf-detr [4]: https://github.com/roboflow/supervision [5]: https://blog.roboflow.com/?ref=whoishiring0625 [6]: https://www.youtube.com/@Roboflow [7]: https://blog.roboflow.com/series-b/
In Ask HN: Who is hiring? (June 2025)
zerojames·Mar 21, 2025Submission

Show HN: RF-DETR, SOTA Real-Time Object Detection Model

The Roboflow ML team has been actively working on RF-DETR, a real-time, transformer-based object detection model architecture. The model architecture is now public and open source (Apache 2.0). RF-DETR-large is the first real-time model to exceed 60 AP on the Microsoft COCO benchmark [1] and achieve strong speeds compared to other models at the base size. On an NVIDIA T4 GPU, RF-DETR-Base achieves 160 FPS. RF-DETR is designed to transfer well to identify real-world objects that aren’t usually found in common training datasets, such as those found in industrial environments, wildlife settings, lab images, thermal, and novel research areas. This is measured using the new RF100-VL benchmark [2] developed in partnership with researchers from CMU. If you try out the model, let us know! We have a fine-tuning guide to get you started with traini
Read the rest
ng models. [3] [1]: https://cocodataset.org [2]: https://github.com/roboflow/rf100-vl [3]: https://blog.roboflow.com/train-rf-detr-on-a-custom-dataset/
2 points · Open discussion

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