Deepnote Pricing: Features, Pros, and Cons in 2026

Deepnote pricing splits by editor seat, so every collaborator who writes or runs code adds to your bill.

I checked Deepnote's live pricing page for 2026 and mapped out where the costs hide in each tier. Here's how each plan works, what it includes, and which one fits your team's workflow and budget.

Deepnote pricing: At a glance

Deepnote offers three pricing tiers, and your cost depends on how many editors your team needs and whether you require enterprise security features. Here's a quick comparison:

The Team plan includes $39 in AI credits, $280 in CPU credits, and $50 in GPU credits every month. I found that's typically enough for small-to-medium analysis work like dashboards, reports, and routine queries.

Teams running heavier workloads, like machine learning models or large dataset processing, will likely burn through credits faster and need to purchase more or move to Enterprise.

Deepnote also runs as an open-source project, which gives developers visibility into how the platform works under the hood. That doesn't change what you pay. The pricing tiers stay the same whether you're reading the code or not.

Deepnote pricing plans breakdown

Deepnote's pricing separates casual users from teams that need collaboration and automation features. Here's what each plan includes and who it's for:

Deepnote Free plan

• Price: Free
• What's included: Up to 3 editors, 5 projects, unlimited viewers, basic Deepnote AI, a handful of database connectors, 5 GB RAM machines, and 7-day revision history.
• Best for: Students, solo learners, and small teams evaluating the platform before committing to a paid plan.
• Pros: No cost, full notebook functionality, and unlimited viewers for sharing work.
• Cons: Editor and project caps fill up fast. Missing scheduled runs, premium integrations, and a longer revision history.

Deepnote Team plan

• Price: $49/editor/month monthly or $39/editor/month billed annually
• What's included: Everything in Free, plus unlimited viewers and notebooks, a monthly AI credit instead of unlimited usage, premium integrations, background execution, scheduled notebooks, and 30-day revision history.
• Best for: Data teams that collaborate on analysis, need database connections, or want automated reporting.
• Pros: Gives you the features you need for production work. A 14-day free trial is available.
• Cons: Per-editor pricing adds up quickly. A 10-person team pays $390 to $490 a month.

Deepnote Enterprise plan

• Price: Custom
• What's included: Everything in Team, plus unlimited AI usage, SSO and directory sync, audit logs, HIPAA compliance, and volume discounts.
• Best for: Organizations with strict security requirements, compliance needs, or large teams that need centralized control.
• Pros: Full security and governance features, plus AI usage without a credit cap.
• Cons: Requires sales conversations and contracts. Enterprise deals can run into tens of thousands a year.

The hidden cost drivers in each Deepnote tier

The plan cards make Deepnote look like a simple per-seat tool. I dug past them because the cost drivers are the AI credits and the compute, and neither shows up cleanly on the pricing table. Here’s what you can expect:

My honest read? The credits cover dashboards, reports, and routine queries just fine. Train a model or grind through a large dataset and you'll blow past them fast, so I’d budget for compute as a cost that moves month to month.

Is Deepnote free?

Yes, Deepnote has a genuine free plan that never expires, so it's more than a 14-day tease. You get unlimited Basic machines, unlimited viewers, and full notebook features for up to 3 editors and 5 projects.

The catch is what's locked behind the paywall. On Free, you don't get:

• Scheduled notebooks
• Premium warehouse connections (BigQuery, Snowflake, Redshift)
• Machines bigger than 5 GB
• Background execution
• A GPU

Revision history also stops at 7 days, and your machine sleeps after 15 idle minutes.

I'd upgrade the moment you outgrow the 3-editor cap or need to connect a production database and schedule recurring reports. Until then, Free covers solo work and small experiments.

Is Deepnote free for students?

Yes. Deepnote runs a free Education plan that hands students and educators all of Deepnote's features, plus the ability to invite unlimited educators and students.

You can verify eligibility in three ways:

• Sign up with a school email
• Connect the GitHub Student Developer Pack
• Upgrade in the app under Settings, then Upgrade, then Education plan.

You'll need a school email address to qualify. Deepnote accepts students and educators from accredited colleges, universities, and K-12 schools. It also extends to massive open online courses (MOOCs), nonprofits, and similar institutions.

Deepnote features, pros, and cons

Deepnote is a cloud data notebook built for teams. You write Python and SQL side by side, connect to 60+ data sources through an API or MCP, and collaborate in real time the way you would in a Google Doc.

On top of the notebook, you get scheduled runs, deploy-as-API, interactive apps and dashboards, an AI agent that writes code and builds charts, and machines that scale up to GPUs.

It's also open source under an Apache 2.0 license, and it carries SOC 2, HIPAA, and GDPR compliance.

You can expect these pros and cons:

Pros

• Real-time collaboration: Commenting and live editing work well across a team.
• Strong native connections: Warehouses like BigQuery, Snowflake, and Redshift connect natively.
• Jupyter compatibility: Your existing notebooks come along.
• Generous free compute: AI tools are baked into the editor from the Free tier up.
• Open-source transparency: You can inspect the code or self-host it.

Cons

• Per-editor pricing: Costs scale fast for bigger teams.
• Metered AI and compute: Overage sneaks up on you.
• No free GPU: Unlike Colab, GPU access starts on paid plans.
• Code-first design: Non-technical teammates still lean on an analyst to get answers.

In my experience, Deepnote is a professional tool for data teams, and it handles that job well. A marketer or finance lead who just wants a quick answer will still be stuck waiting on an analyst.

Is Deepnote worth the cost?

Deepnote is worth the cost if your team collaborates on notebooks regularly, needs data warehouse connections, or wants to automate analysis with scheduled runs. The per-editor model makes it harder to justify for teams where only a few members need full editing access while others review.

Here's how to decide:

• It's worth it if: Your team writes Python or SQL together, connects to cloud data warehouses, and needs real-time collaboration with version history.
• It's best for: Data science teams, analytics groups, and researchers who want Jupyter compatibility with better collaboration than local notebooks.
• Skip it if: You only need quick insights from business data without writing code, or you're looking for natural-language analysis that non-technical users can run.

The collaboration features work well for technical teams. For non-technical users who want answers without SQL or Python, a tool designed for natural-language queries might be a better fit.

Deepnote alternatives and pricing comparison

Deepnote isn't the only option for collaborative notebooks and data analysis. I tested a few tools that take different approaches to teamwork, pricing, and technical requirements.

Here's how Deepnote alternatives compare:

Hex pairs collaborative notebooks with a drag-and-drop app builder, starting at $36 per editor on Professional and $75 on Team. If you're weighing it seriously, we broke down the numbers in our Hex pricing guide and covered the alternatives in our Hex competitor roundup.

Google Colab is the pick for cheap, GPU-heavy solo work. Julius goes the other direction, built for people who want charts and reports from plain-English questions, no code required.

💡 Tip: Read our Julius vs Deepnote comparison if you’d like to learn more.

Deepnote vs Google Colab: pricing compared

I've come to think of Deepnote as the team tool and Colab as the solo builder's tool, and once you frame it that way, the pricing on both sides starts to make sense:

As of September 2026, Colab also comes bundled into Google's AI subscription plans, so Plus, Pro, and Ultra subscribers get priority GPU access on top of any standalone Colab plan.

Colab's strength is cheap GPU access for solo ML work. Deepnote's strength is collaboration, warehouse connections, and AI-assisted analysis for teams.

Pick your billing model accordingly: compute units on Colab, editor seats plus metered compute on Deepnote.

Does Deepnote offer free GPUs, and can you run it locally?

No, Deepnote doesn't give you a free GPU. Its GPU machines (60 GB RAM, 12 GB K80) are pay-as-you-go on Team and Enterprise only, and the Free plan tops out at Basic CPU machines. If a free GPU is the whole reason you're shopping, I'd point you toward Colab instead.

Running Deepnote locally is possible, just not in the traditional sense. It's cloud-first by design, but the notebook itself is open source under an Apache 2.0 license, so you can self-host it if you want full control.

You can also start a notebook locally in VS Code or Cursor and pick up the same work in the cloud later. Full on-premise or single-tenant deployment exists too, but it's an Enterprise-only option.

There's no one-click desktop app here, so "local" really means self-hosting the open-source version or going the Enterprise route.

Julius vs Deepnote: Which should you choose?

Julius is built for business users who want fast insights from connected data without writing code. Deepnote focuses on technical users who need collaborative Python and SQL notebooks with version control and scheduling.

Use this quick guide to figure out which fits your needs:

• Julius is better for: Non-technical users who want charts, summaries, and reports from natural-language questions. It works well for marketers, finance teams, and managers who need quick answers without learning SQL or Python.
• Deepnote is better for: Data scientists and analysts who write code daily and need Jupyter-style notebooks with real-time collaboration. Deepnote pricing makes the most sense when your workflow involves Python, SQL, and team-based analysis.
• Use both if: Your data team uses Deepnote for deep technical work while business users run quick queries and scheduled reports in Julius. This setup lets technical and non-technical teams work independently without creating bottlenecks.

Ready to see how Julius handles your data questions? Try Julius for free today.

My bottom line on Deepnote pricing

Deepnote pricing makes sense for technical teams that need collaborative notebooks with scheduling and database connections, but the per-editor model gets expensive once you add more than a few collaborators. The jump from Free to Team forces an all-or-nothing decision when you hit the 3-editor cap.

The Team plan works well for data teams who spend their days in Python or SQL and need real-time collaboration with version history. It's built for code-first workflows, but I found the lack of natural-language querying means non-technical teammates still need to rely on analysts for answers.

If your focus is getting quick answers from data, sharing insights with stakeholders, or running analysis without writing SQL, I'd recommend trying Julius alongside or instead of Deepnote. It gives you fast results and clear visuals without the technical overhead of a full notebook environment.

Frequently asked questions

Does Deepnote offer a free trial?

Yes, Deepnote offers a 14-day free trial of the Team plan. You don't need a credit card to start the trial. At the end of 14 days, you can continue on a paid plan or drop back to the Free tier with its 3-editor and 5-project limits.

What happens when you downgrade from Deepnote Team to Free?

When you downgrade from Deepnote Team to Free, your workspace reverts to Free tier limits. Excess editors become viewer-only, and you can't create new projects above the 5-project cap. Scheduled notebooks stop running, revision history beyond 7 days becomes inaccessible, and premium integrations disconnect.

Can you use Deepnote for enterprise data warehouses?

Yes, you can use Deepnote for enterprise data warehouses like BigQuery, Snowflake, Redshift, and Databricks on the Team and Enterprise plans. The Free plan supports PostgreSQL, MySQL, ClickHouse, MariaDB, and MindsDB, and file uploads, but warehouse connections require a paid subscription.

Can you run Deepnote locally?

Sort of. Deepnote is cloud-first, but the notebook is open source under Apache 2.0, so you can self-host it. Enterprise customers can also get on-premise or single-tenant deployments, while everyone else works in the cloud.