Web tool Web
See official pricing source (opens in a new tab)
Unknown
For: Checking local model fit
Limits
- Pricing not stated on pages loaded
Includes
- Model grades S to F
- Device directory
1 more
- Playground
No API
Research & searchDocumented overviewLast checked Sep 29, 2026
CanIRun.ai: Pricing, Features & Best Use Cases
Detects your GPU or Mac and shows which open AI models can run locally, with VRAM needs, speed estimates and grades.
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Our take: Use CanIRun.ai to check, before downloading anything, which open text, coding, image and video models fit your GPU or Mac and how much VRAM each needs.
Main limitation: Fit grades and speeds are estimates, not benchmarks on your own machine, and no pricing information was visible on the pages loaded.
Who CanIRun.ai fits
Use CanIRun.ai to check, before downloading anything, which open text, coding, image and video models fit your GPU or Mac and how much VRAM each needs. Based on the vendor's documentation, not on a hands-on test.
Best for: Local LLM hobbyists
Also a good fit for
- Buyers choosing GPUs
Consider another tool if estimates only, not benchmarks on your machine
Or if
- Playground needs WebGPU browser support
- Pricing not stated on pages loaded
CanIRun.ai pricing and usage limits
Prices checked Sep 29, 2026 on the official US pricing page. Prices and limits change often.
Free access and trial conditions
No sign-in or paywall seen on the pages loaded; not an explicit free claim.
Not stated.
Paid plans: what changes as you upgrade
Usage caps, credits and extra costs
Not stated.
Not stated.
What is CanIRun.ai, and how does it work?
CanIRun.ai is a web tool that detects your GPU or Apple Silicon device and ranks open language, coding, image and video models by whether they fit. It lists VRAM requirements, speed estimates and a letter grade per model. It also has a device directory (about 300 devices), a two-device comparison page, a tier list, and a browser playground that runs models locally with WebGPU.
What you provide and what you get back
You provide
- Auto-detected GPU or Apple Silicon device (or a chosen device)
- Filters for task, lab and license
You get back
- Per-model grade from S to F
- VRAM requirement per quantization
- Speed estimates
Where you can use it
- Platforms
- Web
- Account
- Not required
- Model types
- Text and coding, image, video, lightweight
- Quantizations
- Q2_K to F16 shown per model
- Devices
- About 300 GPUs and Macs
- Playground
- WebGPU, on-device
Best use cases for CanIRun.ai
Scenarios are worked out by our editors from the documentation; the actual result depends on your input and plan.
Checking if a model fits your GPU
- Who
- Local LLM hobbyists
- You provide
- The auto-detected GPU and VRAM
- Expected result
- A graded list showing which models run comfortably, tight or too heavy
- Plan needed
- Web tool
- Limitation
- Estimates, not measured benchmarks source (opens in a new tab)
Choosing a device for local AI
- Who
- Buyers comparing GPUs and Macs
- You provide
- A device from the directory of about 300 devices
- Expected result
- Which models each device can run
- Plan needed
- Web tool
- Limitation
- Directory may lag new hardware source (opens in a new tab)
Comparing two devices
- Who
- Buyers deciding between two options
- You provide
- Two chosen devices
- Expected result
- A side-by-side view of fit
- Plan needed
- Web tool
- Limitation
- Compare page speeds are estimates source (opens in a new tab)
Trying a small model in the browser
- Who
- Curious users
- You provide
- A model from the playground
- Expected result
- Local inference via WebGPU with no API key
- Plan needed
- Web tool
- Limitation
- Needs WebGPU browser; model must download first source (opens in a new tab)
CanIRun.ai features and their limits
Automatic GPU/Mac detection
Detects your GPU or Apple Silicon and shows VRAM, bandwidth and RAM. Starts the check without manual spec entry.
Model grades S to F
Grades every model from S to F by fit on the chosen device. Shows at a glance what runs comfortably.
Filters by task, lab and license
Narrows the model list by task (text, image, video, lightweight), lab and license. Finds models relevant to your use.
Device directory of 302 devices
Lists about 300 devices with tier list and compare pages. Helps shopping for hardware.
CanIRun.ai: strengths and limits
Where CanIRun.ai is strong
- Covers text, coding, image and video models One check across model types documented source (opens in a new tab)
- Playground runs on-device with no API keys Try models without accounts or cloud cost documented source (opens in a new tab)
- Large device directory Check hardware you do not own documented source (opens in a new tab)
- No sign-in seen on the pages loaded Quick use without account documented source (opens in a new tab)
- Lists license per model See Apache, MIT or non-commercial terms at a glance documented source (opens in a new tab)
Limitations to check before paying
- Estimates only, not benchmarks Real speed may differ documented source (opens in a new tab)
- Playground needs WebGPU browser support Older browsers cannot run it documented source (opens in a new tab)
- Pricing not stated on pages loaded Cost status is unconfirmed documented source (opens in a new tab)
- Playground models must be downloaded first Needs bandwidth and storage documented source (opens in a new tab)
- Pricing, privacy and docs pages return 404 No stated data policy documented source (opens in a new tab)
How to use CanIRun.ai for checking which local AI models fit your GPU
Set up CanIRun.ai
- Open canirun.ai in a recent browser
- Let the page detect your GPU or choose a device from the directory
- Pick a task: text and coding, image, video or lightweight
Example: checking which local AI models fit your GPU
- Read the count of models that fit comfortably
- Filter by lab or license
- Open a model to see VRAM per quantization
- Try a small model in the playground if WebGPU is available
Review and export the result
- Compare the VRAM figure with your actual free memory
- Run the model in your own runtime and note real speed
Privacy, data use and commercial rights
Summarized from the vendor's current policies; this is not legal advice and a vendor's badge is not an independent audit.
How your inputs and outputs are handled
The page reads your device hardware to estimate fit; playground inference runs on-device.
Not stated.
Not stated.
Commercial use and plan restrictions
Not stated.
None stated.
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CanIRun.ai FAQ
What does CanIRun.ai check?
It detects your GPU or Apple Silicon and grades open models from S to F by whether they fit, with VRAM and speed estimates. source (opens in a new tab)
Which model types does it cover?
Text and coding, image and video models, plus a lightweight group of 4B-and-under models. source (opens in a new tab)
Are the speeds measured on my machine?
No. They are estimates, not benchmarks. source (opens in a new tab)
What does the playground need?
A WebGPU-capable browser, and models must be downloaded before running on-device. source (opens in a new tab)
Can I check a device I do not own?
Yes. The device directory lists about 300 devices and a compare page sets two side by side. source (opens in a new tab)
Sources and review methodology
Official sources and verification dates
- CanIRun.ai home homepage · checked Oct 1, 2026
- Devices homepage · checked Oct 1, 2026
- Playground homepage · checked Oct 1, 2026
Not verified: Pricing; Privacy and data policy; API.
How we documented and maintain this page
Every fact about CanIRun.ai above comes from the 3 official pages listed here, last compared on Sep 29, 2026; we have not run CanIRun.ai ourselves, so it has no editorial score. How we check and re-check pages.
Article updated Oct 10, 2026; prices checked Sep 29, 2026. Outbound links to vendors are plain links; we do not earn commissions. How we review · Report an error