Reflexor vs Continue.dev
Local AI power without the headache of editing JSON configs.
Continue.dev is a versatile framework, but requires setting up external servers, manually modifying config.json files, configuring ports, and troubleshooting endpoint timeouts. Reflexor ships an embedded native engine that works out of the box in 1 click.
Key Differences
- 1-Click Embedded Engine: No need to manually install Ollama or Docker first. Reflexor manages local inference automatically.
- Zero Config File Editing: No broken JSON syntax, no mismatched API endpoint URLs, and no CORS or localhost timeout issues.
- Instant Hybrid Compatibility: Already running Ollama or LM Studio? Reflexor detects and connects seamlessly without manual setup.
Comparison Table: Reflexor vs Continue.dev
| Feature | Reflexor | Continue.dev |
|---|---|---|
| Setup & Onboarding | 1-Click in UI | Manual (install server & config files) |
| Editing config.json files | None required | Mandatory |
| Embedded Native AI Engine | Yes | No (requires external backend) |
| Auto-detect running Ollama | Yes | Requires manual JSON entry |
| Inline code completion (Tab) | Yes | Yes |
| Built-in Semantic RAG | Yes (Zero setup) | Requires external embedding setup |
| Open Source & Zero Telemetry | Yes | Yes |
| Multilingual UI Support | 24 Locales | Predominantly English |
FAQ
If I already run Ollama, can I keep using my existing models?
Yes! Reflexor automatically discovers running Ollama and LM Studio instances, displaying your local models directly in the UI without manual port or URL mapping.
How does performance compare between Reflexor and Continue?
Reflexor's embedded native engine is tailored specifically for low-latency code completion on modern x64 and Apple Silicon systems, keeping RAM and CPU footprint minimal.
Does Reflexor work completely without internet access?
Yes. Once your engine and model are confirmed, Reflexor works 100% offline, without telemetry pingbacks, license checks, or remote dependencies.