Cursor IDE vs Continue.dev vs Codeium: Local LLM Privacy Guide

Most AI coding tools send your code to someone else’s server. That single fact is reshaping how engineering teams choose their tooling in 2026.

The Cursor IDE vs Continue.dev vs Codeium privacy debate isn’t academic. It’s a procurement conversation happening right now in regulated industries — fintech, healthcare, defense contracting — where a single API call to a third-party model can violate compliance requirements. And it’s bleeding into general software teams who’ve started reading their vendor agreements more carefully.

Three tools dominate this conversation: Cursor IDE, Continue.dev, and Codeium (now rebranded as Windsurf). Each takes a fundamentally different position on where your code lives during inference. That architectural choice has downstream consequences for security posture, latency, cost, and team autonomy that most comparison posts gloss over.

This breakdown covers the trade-offs with specifics — not marketing copy.

Key Takeaways

• Cursor IDE offers the strongest developer experience but routes all inference through Anthropic/OpenAI APIs by default, with no true on-premise option as of Q1 2026.
• Continue.dev is the only tool in this comparison that runs entirely air-gapped when paired with a local model like Ollama or llama.cpp — making it the default choice for compliance-heavy teams.
• Codeium (Windsurf) offers a self-hosted enterprise tier, but minimum seat requirements and infrastructure complexity put it out of reach for teams under roughly 50 engineers.
• Local LLM inference via Ollama + DeepSeek Coder V2 now reaches ~85–90% of GPT-4o code quality benchmarks on HumanEval, according to community benchmarks published on the Ollama GitHub discussions board (March 2026).
• The decision ultimately splits along one axis: do you need zero data egress, or do you need the best autocomplete experience money can buy?

How We Got Here: The Privacy Reckoning in AI Tooling

Twelve months ago, the AI coding tool conversation was mostly about autocomplete quality. Teams were benchmarking tab completion speed and context window size. Privacy was a checkbox item.

That changed fast. Samsung’s widely-reported 2023 incident — engineers accidentally leaking proprietary source code through ChatGPT — became a cautionary case study that compliance and legal teams started citing in 2024 vendor reviews. By late 2025, GitHub’s own survey data (State of the Octoverse 2025) showed that 41% of enterprise respondents listed “data privacy and security” as their top concern when evaluating AI coding tools, up from 22% in 2023.

Regulatory pressure compounded this. The EU AI Act’s provisions around high-risk AI systems, which began enforcement in August 2025, created new documentation requirements for companies using AI in certain software categories. American defense contractors operating under CMMC 2.0 faced similar constraints — any code touching controlled unclassified information can’t leave a compliant environment.

So the market fragmented. Consumer-grade tools kept improving their cloud models. A parallel ecosystem built around local inference — Ollama, llama.cpp, LM Studio — matured enough to be production-viable. Three distinct categories emerged: pure cloud (Cursor), pure local-first (Continue.dev), and hybrid enterprise (Codeium/Windsurf).

Three Tools, Three Philosophies

Cursor IDE: Best-in-Class UX, Cloud-First Architecture

Cursor remains the benchmark for raw developer experience. The Tab completion model, the Composer multi-file editing interface, and the @codebase context retrieval are genuinely ahead of alternatives. The Cursor team has been transparent that their proprietary Tab model is trained specifically for code completion — it’s not just a wrapped GPT-4o call.

The architecture is cloud-first. Your code goes to Cursor’s servers, which route to Anthropic or OpenAI depending on the model selected. Cursor’s privacy policy (last updated February 2026) lets users opt out of telemetry and training data collection, and their “Privacy Mode” doesn’t store prompts. That’s meaningfully better than many competitors.

It’s not enough for teams with strict data egress policies. There’s no self-hosted Cursor option. The Cursor Business tier ($40/user/month as of April 2026) provides SOC 2 compliance documentation, but inference still happens in Cursor’s cloud infrastructure.

For teams without compliance constraints, Cursor is the productivity leader. Full stop.

This approach can fail when your codebase contains regulated data — PHI, CUI, PCI-scoped logic — and your legal team finally reads the vendor DPA. At that point, Cursor’s UX advantages become irrelevant. The tool is simply off the table.

Continue.dev: The Air-Gap Champion

Continue.dev is open-source (Apache 2.0 license), runs as a VS Code or JetBrains extension, and is model-agnostic by design. Point it at an Ollama instance running locally, and zero bytes of your code leave your machine during inference. That’s not a marketing claim — it’s the architecture.

The setup looks like this in practice:

ollama pull deepseek-coder-v2:16b
# configure Continue to use http://localhost:11434 as the provider

That’s genuinely the core of it. The Continue.dev team maintains documentation for connecting to Ollama, llama.cpp, LM Studio, and remote self-hosted endpoints (vLLM, Hugging Face TGI). The flexibility is real.

The trade-off is quality and polish. Autocomplete with local models runs noticeably behind Cursor’s Tab model, especially for multi-line completions. The UI is functional, not delightful. And you’re responsible for model selection, hardware provisioning, and tracking new model releases — real engineering overhead.

According to Walter Deane’s benchmark write-up on Medium (2025), running DeepSeek Coder V2 16B locally on an M2 MacBook Pro achieved ~12 tokens/second. Usable for chat-style interactions, but noticeably slower for real-time autocomplete than cloud-based tools.

Codeium / Windsurf: The Enterprise Middle Ground

Codeium rebranded to Windsurf in late 2024 and has been pushing aggressively into enterprise. Their self-hosted deployment option (Windsurf Enterprise) lets organizations run the full stack on their own infrastructure — inference included.

The catch: it’s not lightweight. Windsurf Enterprise requires Kubernetes, a dedicated GPU cluster, and a minimum contract that Codeium’s sales team quotes in the $50k+/year range for smaller organizations. According to DEV Community coverage of AI coding tools (2025), this puts Windsurf’s self-hosted option firmly in the large-enterprise tier.

For mid-market teams — 10 to 100 engineers — who want self-hosting without the infrastructure complexity, Windsurf’s tier is often harder to justify than a Continue.dev + Ollama stack.

Side-by-Side: Which Tool Fits Which Team?

The autocomplete quality gap between Cursor and Continue.dev is real but narrowing. DeepSeek Coder V2 and Qwen2.5-Coder (released Q4 2025) have pushed local model HumanEval scores into the 75–80% range, versus GPT-4o’s ~90%. That gap was 30+ points two years ago.

Matching Tool to Team Reality

For teams with zero compliance requirements — early-stage startups, solo developers, open-source projects — Cursor is the correct choice today. The productivity gains from Tab completion and Composer are measurable. GitHub’s internal research (cited in the 2025 Octoverse report) found AI coding tools reduced time-to-first-PR by 26% on average. Cursor’s UX maximizes that effect.

For teams with strict data handling requirements — healthcare SaaS with PHI in codebases, defense contractors under CMMC, fintech with PCI-scoped code — Continue.dev plus a local Ollama stack is the only option that doesn’t require a legal review of a vendor’s data processing agreement. Budget 2–4 hours of engineering time to configure correctly, plus ongoing model management. That overhead is worth it when the alternative is a compliance violation.

For large engineering organizations (50+ developers) in regulated industries who need enterprise support and SLAs, Windsurf Enterprise is worth evaluating. Get the infrastructure requirements in writing before signing — GPU cluster management is not trivial, and that surprise lands hard mid-deployment.

What to watch next: The local model quality curve is the key signal. If Qwen2.5-Coder or a successor closes the gap with GPT-4o to within 5% on standard benchmarks by end of 2026, the case for cloud-based tools weakens significantly even for non-regulated teams. The HumanEval and SWE-bench leaderboards on Papers with Code tell the real story — those numbers move faster than any vendor roadmap.

Where This Goes Next

The decision comes down to three realities:

• Cursor wins on experience, but cloud inference is the price of admission.
• Continue.dev wins on privacy, with genuine air-gap capability that no other free tool matches.
• Windsurf wins on enterprise support, but the infrastructure bar is high.

Over the next 6–12 months, two things will shift this landscape. Local model quality will keep improving — the gap between Ollama-hosted models and GPT-4o is closing faster than most cloud-tool vendors want to admit. And Cursor may face real pressure to offer a self-hosted option as enterprise demand grows; their current architecture makes this non-trivial, but the market signal is difficult to ignore.

The question isn’t “which tool is best.” It’s “where does your code need to stay?” Answer that first. The tool selection follows directly.

What’s your team’s current data egress policy for AI tooling — and does your vendor contract actually reflect it?

References

1. Top Cursor Alternatives (2025): 10 Best Picks - Openxcell
2. Running a Local LLM for Code Assistance | by Walter Deane | Medium
3. Top 10 Open Source Cursor Alternatives for Developers in 2025 - DEV Community

Photo by BoliviaInteligente on Unsplash