SRG Bottom Line
One-Line Verdict: Continue is the right tool for freelance developers who want Cursor-caliber AI coding without the $20/month subscription and without surrendering control over which model runs, where code goes, and how the assistant behaves — but if you want something that works in five minutes flat without touching a config file, Cursor or Copilot will serve you better.
What is Continue?
Continue (continue.dev) is an open-source AI coding assistant built by Continue, Inc., a San Francisco-based company founded in 2023. It installs as an extension in VS Code and JetBrains IDEs and adds autocomplete, inline edits, chat, and agent-mode capabilities to your existing editor — without requiring you to switch to a new IDE or pay a subscription for core functionality.
The defining characteristic is model flexibility: Continue connects to any AI provider through your own API keys — OpenAI, Anthropic, Google, Mistral, DeepSeek — or to a fully local model running through Ollama, with no code ever leaving your machine. The extension has 2.5 million+ VS Code installs and 32,000+ GitHub stars as of April 2026, making it one of the most widely adopted open-source AI coding tools available.
Its product has also quietly pivoted beyond pure IDE assistance into CI/CD territory, with PR-level AI quality checks and agentic Mission Control workflows that run background agents on schedules and triggers.
At Smart Remote Gigs, I’ve been running Continue as a daily driver across two client projects — a TypeScript API service and a Python data pipeline — specifically testing it against Cline and Cursor to answer the question that matters to freelancers: is the setup overhead worth the cost savings and the control? The short answer is yes, with a specific caveat about what “free” actually means when you’re routing Claude Sonnet at $3 per million input tokens through a BYOK setup.
🚀 Key Features for Freelancers
Bring Your Own Model — Any Model
Continue connects to OpenAI, Anthropic, Google Gemini, Mistral, DeepSeek, Amazon Bedrock, Azure OpenAI, and xAI through your own API keys, with no markup or platform fee on top. You pay the model provider directly at their published API rates — Claude Sonnet 4.6 at $3/$15 per million tokens, GPT-5 at $10/$30, or run DeepSeek-Coder V2 locally via Ollama at $0/month. For a freelancer doing moderate AI coding work, routing through the cheapest capable model can reduce your effective monthly AI spend to under $15 — less than Copilot, with more model flexibility than Cursor.
Fully Local / Air-Gapped Mode with Ollama
Configure Continue with a local Ollama model and your code never touches an external server. Qwen2.5-Coder 32B and DeepSeek-Coder-V2 are both capable enough for production coding tasks and run entirely on-device. For freelancers handling confidential client codebases — legal, financial, healthcare — this is the cleanest possible answer to the “where does my client’s code go?” question: nowhere, it stays on your machine.
Multi-Model Task Routing
Continue lets you configure different models for different tasks in the same session — a fast, cheap model (DeepSeek-V3) for inline autocomplete, a reasoning-heavy model (Claude Opus 4.6 or o3) for complex refactoring chat, and a different model again for agent-mode tasks. No other IDE extension at this price point offers this level of routing granularity. In practice, I set autocomplete to a local Ollama model and chat to Claude Sonnet and shaved about $40/month off my API costs versus routing everything through Sonnet.
CI/CD PR Quality Checks (Mission Control)
Continue’s newer Mission Control platform runs AI agents as GitHub status checks on every pull request — enforcing code standards, catching security vulnerabilities, flagging documentation gaps — automatically, without a developer manually triggering anything. For freelancers delivering code to clients who have quality standards baked into their GitHub workflow, being able to propose Continue-powered automated quality gates is a genuine service differentiator that clients in regulated industries will pay for.
Fully Configurable Context and Prompts via YAML
Continue’s behavior is configured through a plain-text YAML file — which context sources to include, how prompts are structured, which tools agents can call, which MCP servers to connect to. For freelance developers who do the same types of projects repeatedly, building a project-specific Continue configuration that bakes in your client’s code style and context sources means every new engagement starts with a pre-tuned assistant rather than a blank slate.
🗣️ Voice of the Street: “I set autocomplete to a local Qwen model and chat to Claude Sonnet. My monthly AI spend dropped from $65 to about $18 with zero quality loss on the work I actually bill for.” – u/FreelanceDev_Tomas, Reddit
⚖️ Pros & Cons
✅ The Good:
- The extension is genuinely free — Apache 2.0, no feature gates, no watermarks, no trial expiry. 2.5 million developers use it at $0/month for core IDE functionality.
- Full model flexibility including 100% local, air-gapped operation via Ollama — the strongest privacy posture of any IDE extension in this comparison, and it costs nothing beyond compute.
- Multi-model routing lets you assign the cheapest capable model to each task type, which meaningfully reduces BYOK API costs versus routing everything through a frontier model.
- Works in both VS Code and JetBrains natively — unlike Cline (VS Code only) and unlike Cursor (its own IDE fork), Continue installs in the editor you already use.
- Apache 2.0 license means you can audit exactly what the extension does, fork it, and in regulated environments, demonstrate to client security teams that the codebase is fully inspectable.
❌ The Bad (The Catch):
- “Free” is conditional. The extension costs nothing, but heavy users routing through Claude Sonnet or GPT-5 pay $50–200/month in raw API costs — more than a Cursor or Copilot subscription in some usage patterns. You need to budget API spend carefully or use local models to keep costs predictable.
- Setup is not plug-and-play. Connecting your first model requires editing a YAML config file, obtaining and entering API keys, and understanding the difference between your chat model and your autocomplete model. Cursor takes 5 minutes from download to first suggestion. Continue can take 30–90 minutes to configure well for a first-time user.
- Continue has pivoted product focus toward CI/CD and Mission Control in 2025–2026 — some users on Reddit report feeling like the IDE extension is no longer the primary development focus, with agentic features getting more attention than inline autocomplete polish.
- No inline tab autocomplete as strong as Copilot or Cursor out of the box — Continue’s autocomplete is configurable and works well once tuned, but the default experience trails Cursor’s Composer and Copilot’s native suggestions in side-by-side testing.
- The Team plan at $20/seat/month includes $10 in monthly model credits per seat — but the Solo (free) tier requires you to bring your own API keys for every model access, with no included credits.
💰 Pricing Breakdown (Is it worth it?)
The core Continue extension is free with no time limit, no feature lock, and no credit card required — that’s real, not a demo trap. The actual cost question is your API spend. A light user doing 50–100 chat queries and moderate autocomplete per day on Claude Sonnet will spend roughly $15–25/month in API costs. A heavy user doing complex agent-mode sessions on frontier models can hit $100–200/month.
Switching to a local Ollama model for autocomplete and a cheaper provider for routine chat can bring that down to under $10/month for most solo freelancers. The Team plan at $20/seat/month adds $10 in model credits, team agent management, and shared API key governance — worth it for a small agency running Continue across multiple contractors, not worth it for a solo developer who can manage their own keys.
Plan
Price
Limits/Credits
Best For
Solo (Free)
$0
Full extension, full agent access, no model credits included — BYOK required for all model access, unlimited usage once configured
Solo freelance developers who are comfortable configuring API keys and want full model control at zero subscription cost
Team
$20/seat/mo
Everything in Solo + $10/mo model credits per seat, shared private agents, API key management, team agent governance
Small dev agencies or freelance teams who want centralized Continue configuration and shared model credits without each developer managing their own keys
Company (Enterprise)
Custom — contact sales
Everything in Team + SSO (SAML/OIDC), BYOK at org level, on-premises data plane, custom SLA
Freelancers embedded in enterprise client teams that need SSO, data residency controls, and a formal SLA for AI tooling
Local Ollama Setup (BYOM)
$0/mo (compute only)
Run Qwen2.5-Coder 32B, DeepSeek-Coder-V2, or Code Llama locally — fully air-gapped, no API costs, performance depends on local hardware
Privacy-focused freelancers handling confidential client code who need a provably local-only AI coding setup with no external API calls
⚔️ The Kill-Matrix: Continue vs Competitors
Continue wins on price, privacy, and configurability — but Cursor is still ahead on out-of-the-box polish, and Cline is ahead on autonomous agentic task execution for developers who don’t need inline completions.
Feature
Continue
Cursor
Cline
Price (Core Tool)
Free — Apache 2.0, no subscription
$20/mo Pro (proprietary IDE)
Free — Apache 2.0, no subscription
Effective Monthly Cost
$0–200 depending on model usage
$20/mo flat (models included up to limits)
$0–200 depending on model usage
Model Flexibility
Any — OpenAI, Anthropic, Gemini, local, custom endpoints
OpenAI, Anthropic, some BYOK at Pro tier
Any — BYOK, OpenRouter, local
Local / Air-Gapped Mode
Yes — full Ollama support, zero external calls
No — cloud-dependent
Yes — Ollama support
IDE Support
VS Code + JetBrains (native extension)
VS Code fork only — no JetBrains
VS Code only
Inline Tab Autocomplete
Yes — configurable, requires tuning
Best in class — works great out of the box
No — agentic only, no inline completions
Autonomous Agent Mode
Yes — Mission Control + CLI agents
Yes — Composer and Agent mode, well-polished
Best in class — Plan/Act modes, 5M+ installs
CI/CD PR Quality Checks
Yes — unique Mission Control feature
No
No (CLI 2.0 has headless mode for CI)
Setup Time
30–90 minutes for full config
5 minutes
10–20 minutes
Best For
Control-focused devs, privacy-sensitive projects, mixed VS Code / JetBrains teams
Developers who want the best polish and don’t mind the subscription
Autonomous coding tasks, VS Code-only teams
SRG Verdict
Continue earns its spot in the Smart Remote Gigs recommended stack for a specific type of freelance developer: technically confident, privacy-conscious, working across VS Code and JetBrains, and motivated to invest 60–90 minutes of setup time in exchange for never paying a platform subscription again.
If that’s you, the multi-model routing alone — pairing a free local Ollama model for autocomplete with a cloud model for heavy chat — can bring your real monthly AI coding spend below $20 while giving you more model flexibility than Cursor at $20/month flat.
The Mission Control CI/CD agents are a genuine differentiator for freelancers working on client projects with PR-based quality workflows. But I’d be doing you a disservice if I didn’t name the tradeoffs clearly: if you want something that works immediately without touching a config file, Cursor is still the more polished experience and the $20/month is arguably worth it for the time you save on setup.
And if your primary need is autonomous multi-file agent tasks without inline completions, Cline is the better tool in that specific lane. Continue is the right call when control and cost efficiency matter more than convenience — and for the right freelancer, that’s a strong enough reason to make it your primary coding assistant in 2026.
Continue Reviews
Reviews
The open-source model and Apache 2.0 license are genuinely good — I respect what the project is trying to do.
Since Continue pivoted toward CI/CD and Mission Control, the IDE extension itself feels like it's getting less development attention.
The free price is correct and the extension installs without issues.
As a less-experienced developer I found the configuration requirements overwhelming — I spent more time troubleshooting than coding in my first week.
The configurability is genuinely impressive once you understand it — I've built project-specific assistants that no subscription tool could replicate.
That same configurability means it takes significant upfront time investment that a new client project doesn't always allow.
Free with full features — the zero-subscription core is a meaningful financial advantage for a solo freelancer.
The API cost unpredictability makes budgeting harder than a flat subscription — I had one month where I hit $90 without realizing it.
The Team plan's shared API key management is the one feature that makes Continue make sense for a small agency.
$20/seat/month on top of API costs means the Team plan isn't actually cheaper than Cursor for most teams.
The JetBrains integration actually works well — something I can't say about most AI coding tools that claim JetBrains support but clearly built for VS Code first.
Agent mode in JetBrains is noticeably less mature than in VS Code — some features lag by a version or two.
Apache 2.0 license means I can actually audit what the extension does — important when a client asks about my toolchain.
The Mission Control CI/CD features are promising but the documentation is thin and setup took longer than expected.
Works in both VS Code and JetBrains — finally a tool that covers my whole dev environment without me switching IDEs.
Autocomplete requires more tuning than Copilot to feel natural — the defaults aren't as polished.
Fully local with Ollama — my client's code never leaves my machine and I can prove it to their security team.
Local model quality on complex reasoning tasks is a step below Claude Sonnet — acceptable trade-off for me, might not be for everyone.
Multi-model routing let me cut my AI API spend by more than half without losing quality on billable work.
The initial YAML config took me a full afternoon to get right — not beginner-friendly.
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