Ultralytics vs Roboflow
How the two compare on model licenses, pricing, training and deployment, from each vendor’s own pages (checked November 2026), with Pictograph as a third option.
Ultralytics vs Roboflow, feature by feature
What each one trains, licenses, and deploys, with Pictograph beside them.
| Feature | Ultralytics | Roboflow | Pictograph |
|---|---|---|---|
| Models you can train | YOLO26, YOLO11, YOLOv8, YOLOv5 | RF-DETR, YOLO, Roboflow 3.0, VLMs | RF-DETR, YOLOX, Segformer |
| License of a model you train | AGPL-3.0, or a paid Enterprise License | Apache 2.0 (RF-DETR); YOLO needs an add-on to self-host | Apache 2.0 (RF-DETR, YOLOX) |
| SAM-assisted labeling | SAM 2.1, SAM 3, SAM 3.1 | SAM 3 | SAM3: point, box, and text |
| Training GPUs | 26 types, from $0.24 / hr | Managed, paid in credits | A10G, A100, H100, priced in USD |
| Cloud endpoint hardware | CPU (1 to 8 vCPU) | CPU or GPU | TensorRT on T4, L4, A100 |
| Endpoint regions | 42 | US | US east and west |
| Live camera input | RTSP, browser webcam | RTSP, WebRTC, webcam | |
| Agent support | Agent Skills (Claude Code, Codex) | MCP server | CLI, Claude Code plugin, 38 tools |
| Run models on your own hardware | The ultralytics package (AGPL) | Free, with Roboflow Inference | ONNX, TensorRT, ExecuTorch |
Where Ultralytics leads
The YOLO ecosystem itself: the open-source ultralytics package and its community, export to 22 formats (TensorRT, CoreML, LiteRT and more) for Jetson, Raspberry Pi and phones, 26 training GPUs priced by the hour, and endpoints in 42 regions.
Where Roboflow leads
Breadth. Roboflow Universe’s public datasets and models, the most model families to train (RF-DETR, YOLO, classifiers, vision-language models), low-code Workflows, over-the-air edge fleets, and enterprise compliance including SOC 2 Type II.
Where Pictograph fits
Real-time GPU inference from code or a coding agent. Every deployment runs a TensorRT engine built for its GPU (T4 vs L4 latency, measured), takes RTSP and WebRTC video, and serves Apache 2.0 RF-DETR or YOLOX models (which one?).
Comparing one of them with Pictograph? See Pictograph vs Ultralytics and Pictograph vs Roboflow.
How the pricing compares
Publicly listed prices, checked November 2026.
| Feature | Ultralytics | Roboflow | Pictograph |
|---|---|---|---|
| Free plan | $0, a one-time $5 credit ($25 with a work email) | $0, 10 credits a month | $0, $5 of compute a month |
| Entry paid plan | $29 per seat / mo (Pro) | $39 / mo (Core) | $29 / mo flat (Core) |
| Compute it includes | $30 of credits per seat / mo | 20 credits / mo | $29 of compute / mo |
| Seats | 1 on Free, up to 5 on Pro | Unlimited admin seats | 1 on Free, 5 Core, 15 Pro, 50 Team |
| Five people, entry paid plan | $145 / mo | $39 / mo | $29 / mo |
| Ship a trained model closed-source | Enterprise License | RF-DETR included; YOLO is an add-on | Included |
Ultralytics bills per seat and Roboflow in credits ($2.86 to $6 each on Core). Pictograph’s plans are flat, and every operation is priced in US dollars before it runs.
Ultralytics vs Roboflow FAQ
What is the difference between Ultralytics and Roboflow?
Ultralytics makes the YOLO models and the ultralytics Python package, and its hosted Ultralytics Platform labels data, trains YOLO26, YOLO11, YOLOv8 and YOLOv5, and deploys them. Roboflow is a broader platform: it trains its own Apache 2.0 RF-DETR, YOLO models, classifiers and vision-language models, and adds Roboflow Universe, Workflows, edge fleet management and an MCP server. The sharpest difference is the license of the model you ship: Ultralytics YOLO is AGPL-3.0 unless you buy its Enterprise License, while RF-DETR is Apache 2.0.
Which is cheaper, Ultralytics or Roboflow?
It depends on team size and how much compute you use. Both start free. Ultralytics Platform Pro is $29 per seat a month with $30 of credits per seat, so five people pay about $145 a month. Roboflow Core is $39 a month for 20 credits with unlimited admin seats, and larger credit packs run up to $1,399 a month for 500 credits. Pictograph Core is $29 a month flat for five members, with $29 of compute priced per operation in US dollars.
Can I use Ultralytics YOLO models commercially?
Yes, under AGPL-3.0 or with a paid license. The ultralytics package and its YOLO models are AGPL-3.0, and so are Ultralytics Platform’s Free and Pro plans: shipping a YOLO model inside a closed-source product or service means releasing your source or buying Ultralytics’ Enterprise License. Roboflow’s plans cover YOLO licensing while the model runs on Roboflow’s cloud, and running it commercially on your own hardware is a paid add-on there too.
Can Roboflow train YOLO models?
Yes. Roboflow trains YOLO26, YOLO11 and YOLOv8 alongside RF-DETR, Roboflow 3.0, classifiers such as DINOv3, ViT and ResNet, and vision-language models. Ultralytics Platform trains Ultralytics YOLO models only. Pictograph trains RF-DETR (detection, segmentation and keypoint), YOLOX and Segformer, and its YOLOX vs RF-DETR guide shows when each detector wins.
Which one deploys models to GPUs for real-time video?
Ultralytics Platform’s dedicated endpoints run on CPU (1 to 8 vCPU, per its docs) in 42 regions, and take RTSP cameras and the browser webcam. Roboflow’s dedicated deployments run on CPU or GPU in US data centers, at 1 credit an hour for a GPU, and Roboflow streams cameras in its cloud. Pictograph deploys every model as a TensorRT engine built for a T4, L4 or A100 GPU in US east or west, and takes RTSP, WebRTC and webcam streams with results for every frame.
Is there an alternative to both?
Pictograph covers the same label, train and deploy loop for developers and coding agents: SAM3 auto-annotation from a point, box or text prompt, RF-DETR and YOLOX training under Apache 2.0, and GPU endpoints with live video, driven from a CLI, a typed Python SDK, REST or a Claude Code plugin. Plans are flat rather than per seat, and every operation has a price in US dollars before it runs.