Compare
How Clusy compares.
Honest, side-by-side looks at the tools people weigh against Clusy, including the cases where the other tool wins.
Every notebook tool, on one screen
16notebooks and editors on the five questions that actually decide the choice. Facts come from each vendor's own documentation, last checked .
| Tool | Runs | GPU | AI | Collaboration | Licence |
|---|---|---|---|---|---|
| ClusyOurs | Cloud | Free CPU, up to H200 | Researches, then runs it | Share and fork | Proprietary |
| Jupyter Notebook | Local | Yours | Via extension | JupyterHub | BSD-3 |
| JupyterLab | Local | Yours | Via extension | Add-on / Hub | BSD-3 |
| marimo | Local or cloud | molab preview | Bring your agent | Share as app | Apache-2.0 |
| Google Colab | Cloud | Free T4, paid to A100 | Gemini | Share a link | Proprietary |
| Kaggle Notebooks | Cloud | ~30 h/week free | Minimal | Fork and comment | Proprietary |
| Deepnote | Cloud | By plan | Autonomous agent | Live multiplayer | Proprietary |
| Hex | Cloud | Not a focus | Agent stack | Live multiplayer | Proprietary |
| Databricks Notebooks | Cloud platform | You configure | Assistant | Governed co-editing | Proprietary |
| Amazon SageMaker Studio | Cloud platform | Any instance | Amazon Q | Shared spaces | Proprietary |
| VS Code + Jupyter | Local or remote | Yours | Copilot | Live Share | MIT core |
| Streamlit | Self-deployed | Your host | None | Ship an app | Apache-2.0 |
| Lightning AI Studios | Cloud | T4 to H200 | Assistance | Share a studio | Proprietary |
| JetBrains Datalore | Cloud or on-prem | Connect your own | JetBrains assist | Live multiplayer | Proprietary |
| CoCalc | Cloud or on-prem | Limited | Assistance | Live multiplayer | Source-available |
| Cursor | Local | Yours | Repo-wide agent | Git | Proprietary |
Plans and pricing, side by side
Clusy is the best value on this page. No other tool gives you every frontier model, an H200, and checkpoint storage that scales to 2 TB.
US list prices at the monthly billing rate, before annual discounts, taken from each vendor's own pricing page, machine documentation and AI documentation, last checked . N/A means the vendor has no plan at that rung, not that we could not find one.
What each plan costs
The published price at every rung, with the machine you get for it underneath.
| Tool | Free | Entry | Team | Top tier |
|---|---|---|---|---|
| ClusyOurs | $0Unlimited projects · 8 vCPU / 8 GB · 5 GB checkpoints | $12Plus · T4 GPU · 16 GB RAM · 30 GB checkpoints | $30Pro · 32 GB RAM · 24 GB VRAM · 100 GB checkpoints | $90–$200Max 10x/30x · up to 128 GB RAM · H200 141 GB · 2 TB checkpoints |
| Deepnote | $03 seats · 5 projects · 2 vCPU / 5 GB | $49 / seatTeam · 4 vCPU / 16 GB default | $49 / seatSame rung. No separate team tier | CustomEnterprise · SSO, audit logs, HIPAA |
| Hex | $0Community · Small, 4 CPU / 4 GB | $36 / seatProfessional · Medium, 4 CPU / 8 GB | $75 / seatTeam · Medium, agents, unlimited apps | CustomEnterprise · SSO, BYOK, single tenant |
| Google Colab | $02 vCPU / 13 GB · 107 GB disk · 12 h cap | $9.99Pro · 100 compute units a month | N/ANo team plan. Colab Enterprise is separate | $49.99Pro+ · 500 units · 24 h execution |
| JetBrains Datalore | $0CPU S 2 vCPU / 4 GB · 120 h · 10 GB | $35 / seatCloud · 750 h of CPU L, 4 vCPU / 16 GB | N/ASame Cloud plan | CustomOn-Premises, self-hosted |
| Lightning AI | $01 Studio · 4 CPU · 100 GB per Studio · 15 credits | Not publishedNo price listed on the site | TeamsRequired for A100, H100 and H200 | CustomEnterprise |
| CoCalc | $03 GB disk · no internet · idles at 30 min | Quote-basedSite licence. No public seat price | Course licencePriced per student | CustomOn-premises Kubernetes |
Scroll the table sideways to see every column.
Which models you get, by plan
Two of these vendors will not say which models they run. One gives you Google's and only Google's. One has no assistant at all. Clusy names every model and lets you pick. Bring your own key works on every plan, including free — connect an Anthropic or OpenAI key and Sonnet 5, Opus 4.8 and GPT-5.6 Sol bill to your account at zero Clusy credits. Hex gates the same feature behind an Enterprise quote.
| Tool | Free | Entry | Team | Top tier |
|---|---|---|---|---|
| ClusyOurs | Auto + BYOKAuto routes to the best value model | 3 models + BYOKAuto · DeepSeek V4 Flash · DeepSeek V4 Pro | Every open model + BYOKAdds Kimi K3, GLM 5.2 and Qwen 3.8 Max | Every model + BYOKAdds Claude Sonnet 4.6, Opus 5 and GPT-5.6 Sol |
| Deepnote | 5 calls a monthPlus 10 completions. Model unstated | GPT-5.5, Sonnet 4.6Drawn down from a monthly AI credit | GPT-5.5, Sonnet 4.6Same rung | Unlimited AIEnterprise |
| Hex | Agent trialNotebook Agent, trial only | Not publishedHex does not name its providers | Not publishedAdds Threads and semantic agents | Your own keyBYOK, Enterprise only |
| Google Colab | GeminiGoogle's models only | GeminiNo Claude, no GPT, no choice | N/ANo team plan | GeminiSame models, more compute |
| JetBrains Datalore | N/ANo AI assistant on the free plan | Datalore AIJetBrains assistance. Models unstated | N/ASame Cloud plan | Datalore AIOn-Premises |
| Lightning AI | N/AAn environment, not an agent. Run your own | N/ANo built-in assistant | N/ANo built-in assistant | N/ANo built-in assistant |
| CoCalc | Cheapest modelsCoCalc covers the low-cost ones | Choice of providersBetter models cost extra. Names unstated | Choice of providersSame | Self-hosted LLMPrivate model on a compute server |
Scroll the table sideways to see every column.
Hardware, storage and retention
Every figure is the top of that vendor's published range, with the free-tier figure underneath it. Where a vendor prices hardware by the hour, the rate is shown instead of a plan spec.
| Tool | Max CPU / RAM | GPU | Storage | Retention |
|---|---|---|---|---|
| ClusyOurs | 8 vCPU / 128 GB8 vCPU / 8 GB on free | T4 → H200T4, L4, A10, L40S, A100, H100, H200. In the plan | 5 GB → 2 TBSaved kernel state. Notebooks and files are not metered | No expiryFree sandbox released after 3 idle days. State kept |
| Deepnote | 16 vCPU / 128 GBHigh memory machine, Team plan | K80, V10016 GB VRAM · $50/mo GPU credit | Not publishedNo per-plan figure given | 7 → 30 daysUnlimited on Enterprise only |
| Hex | 16 CPU / 128 GB4XL, pay-as-you-go on Team+ | L4, A10G6 CPU / 27 GB · $2.93–$4.06 per hour | Not publishedWarehouse-first. Data stays in your warehouse | 7 → 30 daysUnlimited on the $75 plan |
| Google Colab | 2 vCPU / 13 GBHigh-RAM runtime costs extra compute units | T4 → A100Free T4 when capacity allows | 107 GBEphemeral disk. Files live in Drive | N/ARuntime discarded at the 12 or 24 h cap |
| JetBrains Datalore | 48 vCPU / 96 GBCPU XXL at 5.33 credits per hour | 1 → 8 GPUsGPU S to Multi-GPU L · 2.25–36.3 credits/h | 10 → 20 GB10 GB free · 20 GB on Cloud | Paid onlyNo version history on free |
| Lightning AI | Rented by the minuteFree Studio is 4 CPU, restarts every 4 h | T4 → H200H100 $2.00/h · H200 $2.60/h · paid tiers only | 100 GB per StudioPlus 10 GB shared Teamspace Drive | Files onlyFilesystem persists, the kernel does not |
| CoCalc | 16 GB RAM / 3 CPUTypical project maximum, 3 shared CPUs | T4 → H100Compute servers, billed by the second | 3 → 15 GB3 GB free · 15 GB typical paid max | File historyNo kernel state |
Scroll the table sideways to see every column.
Three differences that decide the bill
Every frontier model, not one vendor's
Colab gives you Gemini and nothing else. Hex and Datalore will not say what they run. Clusy Max puts Claude Sonnet 4.6, Opus 5, GPT-5.6 Sol and every open model behind one switch, and bringing your own Anthropic or OpenAI key works on every plan, including free.
A free tier that actually runs
Deepnote's free plan allows five AI calls a month, Hex gives you a trial of its agent, and Datalore gives you no assistant at all. Clusy's free plan runs a real model on an 8 vCPU sandbox with unlimited projects and 5 GB of checkpoint storage.
An H200 included, not metered
Everywhere else the top GPU is billed by the hour on top of the subscription, at $2.60 to $4.06. Clusy Max is $200 a month with H100 and H200 up to 141 GB VRAM already in the plan.
State survives the session
Colab discards the runtime at the 12-hour cap, and none of these tools checkpoint a kernel. Clusy forks a branch with the live namespace intact, and keeps that saved state between sessions on every plan.
The honest exception: if all you want is a GPU and a blank notebook, with no agent and nothing to keep, Colab Pro at $9.99 a month is cheaper than anything here, ours included.
Common questions about notebook pricing
- How much does Clusy cost?
- Clusy has five plans: Free at $0 with the Auto model on an 8 vCPU, 8 GB sandbox and 5 GB of checkpoint storage; Plus at $12 a month adding DeepSeek V4 Flash and V4 Pro, a T4 GPU with 16 GB RAM and 30 GB of checkpoint storage; Pro at $30 a month adding every open model, the L4 and A10 GPUs, 32 GB RAM and 100 GB; and Max at $90 a month for 10x the Plus usage with an A100, 64 GB RAM and 512 GB, or $200 a month for 30x the Plus usage with H100 and H200 GPUs, 128 GB RAM and 2 TB. Checkpoint storage counts the saved kernel state a project keeps between sessions, so notebooks, files and uploads do not fill it.
- How does Clusy pricing compare to Deepnote and Hex?
- Deepnote's Team plan is $49 per seat a month when billed monthly, and Hex is $36 per seat for Professional rising to $75 per seat for Team. Clusy starts at $12 a month with a T4 GPU included, reaches every open model and 24 GB of VRAM at $30, and every frontier model at $90. Deepnote and Hex also meter GPU time separately, while Clusy includes GPU access up to an H200 in the Max plan.
- Which AI models can you use in Clusy?
- The free plan includes the Auto model, which routes each request to the best value model. Plus at $12 a month adds DeepSeek V4 Flash and V4 Pro. Pro at $30 a month adds every open model, including Kimi K3, GLM 5.2 and Qwen 3.8 Max. Max adds every frontier model, including Claude Sonnet 4.6, Claude Opus 5 and GPT-5.6 Sol. Bringing your own Anthropic or OpenAI key works on every plan including free, and those calls cost zero Clusy credits.
- Which notebook platform gives you an H200 GPU?
- Clusy Max includes H100 and H200 GPUs up to 141 GB VRAM in its $200 a month 30x tier. Lightning AI offers an H200 but gates it to paid tiers and bills roughly $2.60 an hour on top of the subscription. Hex offers only L4 and A10G GPUs at $2.93 to $4.06 an hour. Deepnote lists K80 and V100 GPUs. Google Colab tops out at A100 class, spent from a compute-unit balance.
- Which notebook platform keeps your work the longest?
- Clusy puts no retention window on your work, on any plan: on Plus, Pro and Max an idle sandbox stays paused, and on Free the idle sandbox is released after 3 days while the project and its saved kernel state stay restorable. Deepnote keeps 7 days of revision history on free and 30 days on Team, with unlimited history only on Enterprise. Hex keeps 7 days on free and 30 on Professional, with unlimited history from its $75 per seat plan. Google Colab discards the runtime at its 12 or 24 hour cap.
- Which notebook platform has the best free tier?
- Clusy's free plan runs a real language model with unlimited projects on an 8 vCPU, 8 GB sandbox with 5 GB of checkpoint storage for saved kernel state. Deepnote's free plan allows 5 AI calls and 10 completions a month across 3 seats and 5 projects. Hex's Community plan offers a trial of its Notebook Agent on a 4 CPU, 4 GB machine. JetBrains Datalore includes no AI assistant on its free plan.
Research assistants, which do a different job
These come up in the same searches. They read and synthesize what has already been written, and they stop there. Clusy's agent also researches with citations, but it treats that as the first half and then runs the code. For a formal systematic review, or for a broad survey of an unfamiliar field, the tools below go deeper than we do.
| Tool | Runs | GPU | AI | Collaboration | Licence |
|---|---|---|---|---|---|
| ChatGPT data analysis | Cloud | None | It is the AI | Share a chat | Proprietary |
| NotebookLM | Cloud | None | Grounded Q&A | Share a notebook | Proprietary |
| Perplexity | Cloud | None | Search and synthesis | Share a thread | Proprietary |
| Elicit | Cloud | None | Literature review | Shared reviews | Proprietary |
| OpenAI deep research | Cloud | None | Agentic web research | Share a chat | Proprietary |
Head to head
Clusy vs Jupyter Notebook
Jupyter is the notebook standard: open source, local, endlessly extensible — and entirely manual. Clusy keeps the notebook you know but puts an AI agent in the driver's seat: describe the outcome, and it plans, writes, and executes cells on managed cloud compute while you stay in control of every line.
Read the comparisonClusy vs Google Colab
Colab made cloud notebooks and free GPUs accessible to everyone — and it's still where much of the world learns ML. Clusy targets the step after that: an agent that does the work end to end, on persistent projects, with compute that scales from a free sandbox to H200s.
Read the comparisonClusy vs Hex
These two are often shortlisted together but aim at different jobs. Hex is a polished analytics workspace where data teams build SQL-and-Python notebooks and publish them as apps for stakeholders. Clusy is an AI IDE for notebooks where ML work — training, fine-tuning, evaluation — gets done end to end on real GPUs.
Read the comparisonClusy vs Deepnote
Deepnote modernized the cloud notebook: real-time collaboration, SQL blocks, a deep integration catalog, and an AI mode that writes and runs blocks on its own. Both of us put an agent in the notebook, so the honest comparison is about everything around it: what hardware it can reach, which model drives it, and what happens when you want to try five variants.
Read the comparisonClusy vs marimo
Both start from the same complaint (the notebook, as inherited, is a bad research artifact) and fix opposite halves of it. marimo rebuilds the format so notebooks are reproducible and diffable. Clusy rebuilds the workflow so an agent writes and runs the notebook on compute you did not have to provision.
Read the comparisonClusy vs Kaggle Notebooks
Kaggle is the best free classroom in machine learning: real GPUs, real datasets, and hundreds of thousands of notebooks to learn from. Clusy is what the work looks like after the classroom: private projects, an agent doing the execution, and hardware sized for the run rather than the quota.
Read the comparisonClusy vs Databricks
Databricks is a platform decision: governed data, Spark at scale, and notebooks as the interface to it. Clusy is a workbench decision: an agent that runs ML experiments on managed GPUs, connected to the governed data you already have. These are complements more often than they are alternatives.
Read the comparisonClusy vs ChatGPT data analysis
Uploading a CSV to a chat assistant and getting a chart back is genuinely the fastest path to an answer: right up to the point where the answer needs to be reproducible, large, private, or trained on a GPU. Clusy keeps the plain-language interface and puts a real notebook and real compute underneath it.
Read the comparisonClusy vs Cursor
Cursor proved what an agent inside your editor can do, and a lot of people now want that feeling for data work. The catch is structural: Cursor is built around a repository on your machine, and notebooks are neither.
Read the comparisonClusy vs NotebookLM
These two get compared because they share a word. NotebookLM is a reading tool: it grounds answers in documents you give it. Clusy is an execution tool: it writes and runs code against data. Almost nobody needs both for the same task.
Read the comparisonClusy vs Perplexity
Perplexity is the fastest way to find what is already known and see where it came from. Clusy is for the part after that, when the answer does not exist yet and something has to be computed to produce it.
Read the comparisonClusy vs Elicit
Both call themselves research tools and both are, for opposite halves of research. Elicit works over the published record. Clusy works over your data and your compute.
Read the comparisonClusy vs OpenAI deep research
Both are agents that work autonomously for minutes at a time and hand back something substantial. What they do in those minutes could not be more different: one reads the internet, the other runs your code.
Read the comparisonOther tools, compared
Comparisons we are not part of. If the right answer to your question is a tool that isn't ours, these pages say so.
Alternatives guides
The best Cursor alternatives in 2026
Cursor set the bar for agentic coding, and most people looking past it are not unhappy with the agent. They want a different price, a different licence, a different editor, or they have realized their work is notebooks and data rather than a codebase.
Read the guideThe best Jupyter Notebook alternatives in 2026
Jupyter is still the lingua franca of data science — and still entirely manual: your machine, your environments, your every keystroke. A new generation of notebooks adds what Jupyter leaves out: AI that does real work, managed GPUs, collaboration, and reproducibility. Here's an honest map of the options, including when to stay put.
Read the guideThe best Google Colab alternatives in 2026
Colab is the world's on-ramp to ML — free GPUs, zero setup, a share link. People go looking for alternatives when the training run outgrows the session: runtimes recycle mid-epoch, compute units drain, and projects need to persist. Here's an honest map of where to go next.
Read the guideThe best marimo alternatives in 2026
marimo is the most convincing rethink of the notebook in a decade: reactive execution, plain-Python files, open source. People still go looking for something else: usually because they need a language it does not speak, a team workflow it does not have, or hardware it does not provide. Here is where they end up.
Read the guideThe best Deepnote alternatives in 2026
Deepnote is a genuinely good collaborative notebook, and most teams that look elsewhere are not unhappy with the editing experience. They are hitting a different wall: per-seat cost as the team grows, hardware that was never meant for training, or a need for notebooks that live in Git. Here is the honest map.
Read the guideThe best Hex alternatives in 2026
Hex is one of the best analytics workspaces built: warehouse-first SQL, Python for the last mile, and a publishing layer that stakeholders genuinely use. Teams look elsewhere when the deliverable stops being a report: when it becomes a portable notebook, a trained model, or a line item somebody wants smaller.
Read the guideThe best Kaggle Notebooks alternatives in 2026
Kaggle gives away more free GPU than anyone else and surrounds it with the largest library of public datasets and forkable notebooks in the field. The reasons to leave are narrow and specific: the weekly quota, the session cap, and the fact that it is a public-first platform for work that is often private.
Read the guide