Cursor + DeepSeek + VS Code Guide
This guide answers a very practical question: How close can you get to a "free" coding setup with Cursor and DeepSeek, and what is the fallback if you want to stay in VS Code or self-host as much as possible?
1. The short answer​
Cursor​
Yes, Cursor has a free official Hobby plan, but it is limited. Cursor's pricing page currently lists:
- Hobby as Free
- no credit card required
- limited Agent requests
- limited Tab completions
So "Cursor for free" is real, but it is not unlimited free usage.
DeepSeek​
DeepSeek is more nuanced:
- the official DeepSeek API is paid
- DeepSeek publishes open-weight models that you can run yourself
- so DeepSeek can be "free" only in the sense of self-hosting your own inference
As of June 22, 2026, DeepSeek's API docs list paid token pricing for deepseek-v4-flash and deepseek-v4-pro, and also note that deepseek-chat and deepseek-reasoner are scheduled for deprecation on July 24, 2026.
My practical recommendation​
If you want the cheapest sensible stack:
- use Cursor Hobby until its free limits annoy you
- for "real free", run DeepSeek locally
- if you want to stay in VS Code, recreate the stack with Continue + Ollama or Continue + vLLM
2. What "free" really means here​
| Tool | Officially free? | Catch |
|---|---|---|
| Cursor | Yes, Hobby plan | Limited agent requests and limited completions |
| DeepSeek API | No | Token-billed API |
| DeepSeek local models | Yes, weights/runtime path can be free | You still pay with your own hardware and electricity |
That means the truly low-cost path is usually:
- Cursor free plan for occasional use
- VS Code + local DeepSeek for heavy use
3. Can you use DeepSeek inside Cursor?​
Publicly, Cursor clearly supports multiple model-backed features, but based on the official pages I checked, Cursor's main public surface emphasizes its own plans and cloud features rather than a "self-host Cursor" story.
Important reality check​
- Cursor is its own editor product, not a normal VS Code extension
- Cursor is historically VS Code-like, but you do not "install Cursor into VS Code"
- if you want maximum control, VS Code + a separate extension + local model endpoint is the more transparent route
My inference​
Based on Cursor's public pricing/docs surface, Cursor is best treated as a proprietary hosted editor experience with some local/editor characteristics, not as a fully self-hostable AI stack.
So if your real goal is:
- lowest cost
- local model control
- transparent infrastructure
then VS Code is the better long-term base, not Cursor.
4. The clean VS Code fallback​
The most straightforward documented fallback I found is:
- VS Code
- Continue
- DeepSeek running locally through Ollama or behind an OpenAI-compatible server
Continue documents that it is available as a VS Code extension and an open-source coding agent. It also notes that the original repo is now read-only, but the final 2.0.0 release is still available and usable.
DeepSeek gives you the model, Ollama or vLLM gives you the server, and Continue gives VS Code the agent UI.
5. Easiest self-hosting path: Ollama + DeepSeek Coder + VS Code​
This is the simplest setup for one machine.
5.1 Install Ollama​
Download/install Ollama from the official site, then pull a DeepSeek Coder model:
ollama run deepseek-coder
Ollama currently lists these DeepSeek Coder variants:
deepseek-coder:1.3bdeepseek-coder:6.7bdeepseek-coder:33b
5.2 Which size should you choose?​
This part is an inference from model size, not an Ollama hardware guarantee:
| Model | Good for |
|---|---|
| 1.3b | Testing, weak laptops, very low resource usage |
| 6.7b | The most realistic local coding baseline |
| 33b | Serious local inference with strong hardware |
If you are unsure, start with:
ollama run deepseek-coder:6.7b
5.3 Install Continue in VS Code​
Install the Continue extension from the VS Code Marketplace.
5.4 Point Continue at your local endpoint​
The exact UI can evolve, but the architecture is:
- model provider: OpenAI-compatible or local API
- endpoint: your Ollama local server
- model:
deepseek-coderordeepseek-coder:6.7b
A typical local endpoint is:
http://localhost:11434
5.5 Result​
You now have:
- VS Code as the editor
- Continue as the agent/chat layer
- DeepSeek Coder as the local coding model
- no per-token cloud bill
6. Stronger self-hosting path: vLLM server​
If you want something more server-like than Ollama, use vLLM.
vLLM's docs explicitly expose an OpenAI-compatible server and also list integrations for both Claude Code and Codex.
That matters because it means one local model server can become a backend for:
- VS Code tools
- Codex-like workflows
- Claude Code-like workflows
- your own apps
6.1 Basic idea​
Run a model behind vLLM and expose an OpenAI-style API:
vllm serve <your-model>
Then connect your tool to that local endpoint as if it were an OpenAI-compatible API.
6.2 When to choose vLLM over Ollama​
Choose Ollama when:
- you want the fastest local setup
- you are on one developer machine
- you want almost no infrastructure ceremony
Choose vLLM when:
- you want a more serious local or team server
- you want OpenAI-compatible routing for many tools
- you plan to run larger models on stronger GPU hardware
7. VS Code implementation blueprint​
If you want a repeatable setup, do it like this:
Option A - simplest​
- VS Code
- Continue extension
- Ollama
deepseek-coder:6.7b
Option B - more scalable​
- VS Code
- Continue extension
- vLLM OpenAI-compatible server
- a stronger DeepSeek model you host yourself
Option C - hybrid​
- Cursor Hobby for occasional premium UX
- VS Code + local DeepSeek for heavy or cheap work
That hybrid setup is often the most rational one.
8. Can you self-host Cursor?​
Short answer​
Not in the way people usually mean "self-host."
What I could verify​
Cursor's public pricing and product pages clearly describe:
- hosted plans
- cloud agents
- team billing
- admin/privacy controls
What I did not find in the public official material I checked was a clean "run Cursor fully on-prem/self-hosted" product story.
Practical conclusion​
Treat Cursor as:
- a proprietary editor product
- with a free entry tier
- but not as your self-hosted foundation
If self-hosting is the real goal, build around:
- VS Code
- Ollama or vLLM
- DeepSeek open-weight models
9. Can you self-host DeepSeek?​
Yes, with an important distinction​
You can self-host DeepSeek models, not the full commercial DeepSeek SaaS experience.
The three realistic modes​
| Mode | What it means |
|---|---|
| DeepSeek API | Official hosted API, paid |
| Ollama | Easy local runtime for smaller local DeepSeek models |
| vLLM | More advanced self-hosted inference server |
Good self-hosting choices​
Local laptop/workstation​
ollama run deepseek-coder:6.7b
Home lab / GPU server​
- host a model with vLLM
- expose an OpenAI-compatible endpoint
- connect VS Code, Codex-style tools, or your own apps
Compliance note​
If you care about data residency or privacy, local/self-hosted DeepSeek is usually more attractive than the official hosted API. But you still need to make your own decisions about:
- model provenance
- internal policy
- network isolation
- prompt and code retention
10. Minimal setup recipes​
10.1 Cheapest practical setup​
Cursor Hobby + DeepSeek only when needed
Good for:
- trying things
- light usage
- no infrastructure
10.2 Real free daily setup​
VS Code + Continue + Ollama + deepseek-coder:6.7b
Good for:
- daily coding
- no token bills
- local-first workflow
10.3 Strong self-hosted setup​
VS Code + Continue + vLLM + self-hosted DeepSeek model
Good for:
- team use
- internal API routing
- more serious infrastructure
11. Bottom line​
If someone told you "Cursor and DeepSeek are free," the accurate version is:
- Cursor: free tier exists, but limited
- DeepSeek API: not free
- DeepSeek local/self-hosted: yes, effectively free except hardware cost
If you want the best pragmatic path:
- start with Cursor Hobby
- move heavy work to VS Code + local DeepSeek
- if local usage becomes serious, upgrade from Ollama to vLLM
That gives you a workflow that is cheap, controllable, and not locked to one hosted editor.