Google Colab Alternative With Free GPU: 4 Options for 2026
Google Colab alternative with free GPU: Kaggle, Lightning AI, Paperspace and JupyterLab compared on weekly hours and restarts, plus one closed option.
•4 min read•Code Editors, IDEs & Playgrounds
Verdict:Kaggle is the first free GPU notebook to try, with a weekly quota of about 30 hours. Lightning AI gives a one-time allowance, and Paperspace's free GPU works only in private workspaces.
Quick comparison
| Tool | Price | Platforms | Best for | Tested |
|---|---|---|---|---|
| Kaggle Notebooks | Free; weekly GPU quota of about 30 hours, sometimes higher | Web browser | A free GPU with a visible weekly quota and sessions of up to 9 hours | Docs only |
| Lightning AI | Free plan with up to 30 credits in total (about 80 GPU hours on interruptible machines); Pro $20 a month billed annually | Web browser | A Colab-like Studio with a one-time free allowance and a choice of GPUs | Docs only |
| Paperspace | Free plan lists a free M4000 GPU for private-workspace notebooks | Web browser | Light GPU experiments when Kaggle's quota is used up | Docs only |
| JupyterLab | Free, open source (BSD-3-Clause); runs on your own hardware | Windows, macOS, Linux | People who own a GPU and want no session limits or sign-in | Docs only |
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Good fit if
- You ran out of Colab's free GPU and want to keep training without paying
- You can work in shorter sessions and save checkpoints
- A free allowance that can change is acceptable for learning projects
Not ideal if
- You need a guaranteed GPU for a deadline or a long unattended run
- You need a specific GPU model every time
- You cannot put your notebook in a private workspace or on a third-party service
If you have run out of Colab's free GPU, try Kaggle Notebooks first: its documentation describes a weekly GPU quota of 30 hours, sometimes higher. Lightning AI is next, with a one-time free allowance. Paperspace gives a free GPU only in private workspaces, and JupyterLab works if you own a GPU. Skip Amazon SageMaker Studio Lab, which many older roundups still list but which AWS says is closed to new customers.
What matters for a free GPU notebook
Four checks separate the options:
- How many free GPU hours, and do they reset? A weekly quota refills; a one-time allowance does not.
- Session length and restarts. Long training needs a session that survives, or checkpoints that make restarts harmless.
- Can you still sign up? Several free services have changed or closed.
- What you give up. Free tiers differ on storage, privacy and which GPU you get.
Colab itself is clear about the trade-off. According to Colab's FAQ, resources "are not guaranteed and not unlimited," usage limits sometimes fluctuate, and free notebooks can run for at most 12 hours depending on availability. The FAQ adds that runtimes time out when idle and that GPU types vary over time. Colab does not publish its limits, so the number of hours you get is not something you can plan around.
Kaggle Notebooks
Kaggle Notebooks is a free hosted Jupyter environment from Kaggle, the data-science competition site. According to Kaggle's efficient-GPU documentation, the weekly GPU quota is 30 hours or sometimes higher, and individual sessions can run up to 9 hours.
The advantage over Colab is that the quota is a number you can read. You can plan a week of work against 30 hours and save checkpoints when a session ends.
In a June 2023 fast.ai forum thread, a learner who had used up Colab's free GPU credits on a course project was pointed to Kaggle, because the course instructor had mentioned it. The thread is old, so treat it as a pointer, not as current advice.
Kaggle fits coursework, competitions and experiments you can split into sessions of a few hours. Its quotas and GPU models can change, so read your account's quota display before a deadline.
Lightning AI
Lightning AI offers cloud workspaces it calls Studios. According to Lightning's pricing page, the free plan includes up to 30 credits in total, not per month: 5 on registration and 25 more if you add a card. Up to 30 credits buys about 80 GPU hours on interruptible machines.
The free plan allows 1 active Studio, and free Studios "require restart every 4 hours," per the page. Sessions on A100, H100 and H200 GPUs are limited to 4 hours, while T4, L4 and L40S sessions are listed as unlimited. Pro costs $20 a month billed annually, or $50 billed monthly.
The pricing page describes the credits as a one-time total, not a monthly refill, so plan it as a trial that you stretch.
Choose Lightning if you want a choice of GPUs for a single project. Skip it if you want a refilling free quota and would rather not add a card to get the full 30 credits.
Paperspace
Paperspace is a cloud platform for GPU notebooks, and its documentation now sits on DigitalOcean's site. According to the Paperspace pricing docs, a free GPU (the M4000) is listed on the Free, Pro and Growth plans. The same page says free machines "can only be used for Notebooks in private workspaces," and the Free plan includes 5 GB of base storage.
No session length is listed for the free GPU, so none is given here. In the same June 2023 thread, one reply warns that Paperspace's free machines are limited and not always available.
Paperspace is a backup for light experiments once Kaggle's weekly quota is gone. Do not rely on it for long training runs or time-limited work.
JupyterLab on your own machine
JupyterLab is the open-source notebook interface behind most of these services. It is free under the BSD-3-Clause license, and it runs on your own hardware, so there are no session timeouts or hosted limits. You supply the compute, and JupyterLab brings no GPU.
This is the only option here that needs no account. It makes sense if you already have a computer with a GPU, and for any work where you do not want to upload your data. For a code editor setup around it, see free Python IDE options.
A free option that is now closed: SageMaker Studio Lab
Amazon SageMaker Studio Lab was a free JupyterLab service that did not need an AWS account. AWS's documentation now states that it is no longer open to new customers, and that existing customers can continue as normal. If a guide tells you to sign up for it, that guide is out of date.
Comparison
| Option | Free GPU allowance | Session or restart limit | Sign-up | Best for |
|---|---|---|---|---|
| Kaggle Notebooks | About 30 hours a week, sometimes higher | Up to 9 hours | Account | Coursework and competitions |
| Lightning AI | Up to 30 credits in total (about 80 GPU hours) | Free Studios restart every 4 hours | Account; card for full credits | One project with a choice of GPU |
| Paperspace | Free M4000, hours not stated | Not stated | Account | Light experiments |
| JupyterLab | Your own GPU | None | None | Local work and private data |
| Colab (for reference) | Not published | At most 12 hours, idle timeout | Account | Quick prototypes |
How to choose
A student with a course project. Start on Kaggle, use the visible weekly quota, and save checkpoints at the end of every session. Keep Lightning's one-time credits for the training run that matters most.
Someone fine-tuning or testing a model. Use Lightning for the GPU choice, and watch the 4-hour restart on the free plan. To run models yourself, see our free LLM page.
Someone who already owns a GPU. Run JupyterLab locally and skip session limits entirely. For browser coding environments without a GPU, see Replit alternatives.
Limits of this review
No service was signed up for or run, so GPU speed and real availability were not measured. Kaggle's quota figures date from 2026-10-22 and were not re-checked. Colab Pro prices, Paperspace session hours and Kaggle account requirements are not stated because no official page gave them. Community opinion from Reddit was not collected.
FAQ
What is the best free Google Colab alternative with a GPU?
Kaggle Notebooks is the first to try. Kaggle's documentation describes a weekly GPU quota of 30 hours, sometimes higher, and sessions of up to 9 hours. Lightning AI is second, with up to 30 free credits in total that cover about 80 GPU hours on interruptible machines.
Why does the Colab free GPU keep disconnecting?
Colab does not promise it. Its FAQ says resources are not guaranteed and not unlimited, usage limits sometimes fluctuate, free notebooks can run for at most 12 hours depending on availability, and runtimes time out when idle. GPU types also vary over time.
Is there a Colab alternative without login?
Only one you run yourself. JupyterLab is free, open source and works on your own machine, so there is no account, but it brings no GPU. The hosted services here need an account; Lightning's pricing page, for example, gives 5 credits on registration.
Can I keep a free GPU notebook running overnight?
Not reliably on a free plan. Colab's FAQ says free notebooks run at most 12 hours depending on availability, and runtimes time out when idle. Lightning's free Studios require a restart every 4 hours, and Kaggle sessions top out at 9 hours per its documentation. Save checkpoints so a restart costs little.
Is Amazon SageMaker Studio Lab still a free Colab alternative?
Not for new users. AWS's documentation says Studio Lab is no longer open to new customers, while existing customers can continue as normal. Many roundups still list it as a free GPU option, so check the date before following one.
What free GPU notebook do learners recommend instead of Colab?
In a June 2023 fast.ai forum thread, a learner who used up Colab's free GPU credits was pointed to Kaggle, and another reply offered Paperspace Gradient while warning that its free machines are limited and not always available. The thread is old, so check current limits on each official page.
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Kevin Fan
Kevin Fan is a SaaS founder. He runs Free Instead Of, which tracks free and open-source alternatives to paid software and checks each price and free-plan limit against the vendor's own pages.
Methodology
Google Colab's FAQ, Lightning AI's pricing page, Paperspace's pricing docs on DigitalOcean and AWS's SageMaker Studio Lab docs were opened on 2026-10-26. Three published roundups were reviewed for gaps, and one June 2023 learner thread on the fast.ai forum was read. Kaggle's quota figures come from its efficient-GPU documentation as recorded on 2026-10-22. No Reddit threads were used.