Continue is an IDE extension for AI-assisted coding across multiple LLMs, while Ollama is a lightweight runtime for running open-source LLMs locally on personal devices. Continue requires an editor integration, whereas Ollama is a standalone service for local model execution.
Continue vs Ollama — Side-by-side comparison on A Versus B
Open-source IDE extension providing AI-assisted coding across multiple LLM providers.
Simple, user-friendly local LLM runner for Mac, Linux, and Windows
Primary Purpose. Supported Editors. Model Sources. Local Execution. Memory Footprint (Typical Setup). Privacy Mode (Zero Cloud Calls). Installation Complexity
Choose Continue if you want a feature-rich, editor-integrated coding assistant with access to multiple premium and open-source LLMs through a single interface. Choose Ollama if you prioritize complete privacy, local-only execution, minimal resource usage, or need a lightweight API server for running open-source models in production or personal projects.
Continue: 5-10 minutes | Ollama: 15-30 (CLI, GPU setup)
Continue: 10-20 (API key + config required) | Ollama: 2-3 minutes
Continue: Unlimited with local models | Ollama: N/A
Continue: 200-500ms average | Ollama: N/A
Continue: Up to 100,000+ tokens | Ollama: N/A
Continue: VS Code, JetBrains suite, Vim, Neovim (4 major platforms) | Ollama: N/A
Continue: Free (optional donations for commercial use) | Ollama: N/A
Continue: 50+ (with LLM-dependent support) | Ollama: N/A
Continue: $0 (self-hosted) | Ollama: N/A
Continue: 3 (VSCode, JetBrains, Cursor) | Ollama: N/A
Continue: Claude, GPT-4, Llama, Mistral, local | Ollama: N/A
Continue: Local + optional cloud | Ollama: N/A
Continue: Unlimited (depends on API usage) | Ollama: N/A
Continue: Full JSON config (prompts, model params, shortcuts) | Ollama: N/A
Continue: Free (+ API costs) | Ollama: N/A
Continue: 5+ (Claude, GPT-4, Llama 2, custom, local) | Ollama: N/A
Continue: 4 major (VS Code, JetBrains, Vim, Web) | Ollama: N/A
Continue: 6+ (Claude, GPT-4, Ollama, local) | Ollama: N/A
Continue: 5+ (VS Code, JetBrains, Vim) | Ollama: N/A
Continue: 8000-200000 (model-dependent) | Ollama: N/A
Continue: Yes (Ollama, LLaMA) | Ollama: N/A
Continue: Yes (full local support) | Ollama: N/A
Continue: ~0.05 million (2025 estimate) | Ollama: N/A
Continue: No (community-driven) | Ollama: N/A
Continue: 15–30 min (API key configuration) | Ollama: N/A
Continue: Optional (local or cloud) | Ollama: N/A
Continue: Full open-source (Apache 2.0) | Ollama: N/A
Continue: 2-5 sec (Claude/GPT-4) | Ollama: 15-45 sec (CPU), 3-8 sec (GPU)
Continue: $50-150 for power users | Ollama: $0 after hardware
Continue: 10+ providers supported | Ollama: 15+ models
Continue: Required for cloud models | Ollama: Not required after setup
Continue: 8GB minimum (16GB recommended) | Ollama: 8 GB minimum
Continue: Native VS Code extension | Ollama: Requires external plugins/API setup
Continue: Depends on provider, some cloud processing | Ollama: 100% (on-device)
Continue: 15-30 minutes (model download + config) | Ollama: N/A
Continue: 5-15 seconds (hardware-dependent) | Ollama: N/A
Continue: 4 major platforms (VS Code, JetBrains, Vim, Neovim) | Ollama: N/A
Continue: Unlimited (fully free and open-source) | Ollama: N/A
Continue: $0 (open-source) or hosted option available | Ollama: N/A
Continue: Local-only, zero cloud transmission | Ollama: N/A
Continue: Yes (GitHub public repository) | Ollama: N/A
Continue: Varies by provider | Ollama: N/A
Continue: 3 major editors (VS Code, JetBrains, Vim) | Ollama: None (CLI/API only)
Continue: 15+ providers including premium APIs | Ollama: 100+ open-source models (single source)
Continue: 2 minutes (IDE extension) | Ollama: 5-15 minutes (install + model download)
Continue: 300-500 MB | Ollama: 50-200 MB
Privacy Level (0=cloud-only, 100=fully local)
Continue: 80 (optional local via Ollama backend) | Ollama: 100 (always local)
Continue: Comprehensive with config examples | Ollama: Extensive REST API documentation
Continue: $0 (free + optional API costs) | Ollama: $0 (fully free)
Code Generation Accuracy (HumanEval Benchmark)
Continue: N/A | Ollama: 68% (Llama 2 70B)
Monthly Operating Cost (5,000 token average session)
Continue: N/A | Ollama: $0 (hardware only)
Continue: N/A | Ollama: 8GB (Llama 2 7B)
Continue: N/A | Ollama: 5-10s (CPU) / 2-4s (GPU)
Data Privacy (0=external servers, 1=local only)
Continue: N/A | Ollama: No (suggestions only)
Continue: N/A | Ollama: 4GB (minimum); 8GB recommended
Continue: N/A | Ollama: Unlimited (fully free)
Continue: N/A | Ollama: $0 (fully open-source)
Continue: N/A | Ollama: 100% local processing
Continue: N/A | Ollama: 10,000+ GitHub stars, active Discord
Continue: N/A | Ollama: 15-50 (GPU-dependent)
Total Cost of Ownership (12 months, 1M daily tokens)
Continue: N/A | Ollama: $0 (hardware amortized)
Inference Latency (7B model, first token)
Continue: N/A | Ollama: 8GB RAM + 4GB GPU (Llama 7B)
Continue: N/A | Ollama: 8-10 (including model download)
Continue: N/A | Ollama: 1-5 (limited by local hardware)
Model Inference Speed (Llama 2 7B on RTX 4090)
Continue: N/A | Ollama: Command-line interface
Continue: N/A | Ollama: 3-5 minutes (depends on internet)
Continue: N/A | Ollama: Yes (OpenAI-compatible /v1 endpoints)
Continue: N/A | Ollama: NVIDIA CUDA, AMD ROCm, Metal (Apple)
Continue: N/A | Ollama: Medium (CLI setup required)
Throughput (tokens/second, batch size 32)
Continue: N/A | Ollama: 4 GB (with offloading)
Setup Time (from download to first inference)
Continue: N/A | Ollama: 20,000+ (registry)
Continue: N/A | Ollama: Llama 2 70B: 82.3%
Continue: N/A | Ollama: 15-30 minutes (download, install, configure)
Continue: N/A | Ollama: 50+ open-source models
Continue: N/A | Ollama: Only for initial model download; runs offline after
Multimodal Capabilities (Vision, Image Gen)
Continue: N/A | Ollama: Limited; vision support emerging in some models
Continue: N/A | Ollama: Weekly updates (as of 2026)
Continue: N/A | Ollama: Full support with graceful degradation
Continue: N/A | Ollama: 200-5000ms (hardware dependent)
Continue: N/A | Ollama: 1-10 (single device)
Continue: N/A | Ollama: Community-only (none)
Continue: N/A | Ollama: Unlimited (local only)
Continue: N/A | Ollama: No external data transmission (100% offline)
Continue: N/A | Ollama: Model registry only, 0 community features
Continue: N/A | Ollama: Not applicable (CLI tool)
Inference Throughput (RTX 4090, Llama 2 13B)
Continue: N/A | Ollama: 4 (CPU, Metal, CUDA, Vulkan)
Continue: N/A | Ollama: No (sequential only)
Continue: N/A | Ollama: Custom REST endpoints
How to choose between Continue and Ollama
Continue vs Ollama — Structured Comparison Data
Machine-readable comparison dataset for Continue vs Ollama. Contains 132 attribute comparisons, 5 FAQ pairs.
Continue vs Ollama — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Continue vs Ollama.
Can I use Continue without paying for OpenAI or Claude API keys?
Yes. Continue can use Ollama as a free backend, allowing you to run open-source models like Mistral or Llama 2 entirely locally. You can also configure Continue to use other free options like LocalAI. However, if you want access to GPT-4 or Claude, you'll need paid API keys.
Does Ollama work as a backend for Continue?
Yes. Ollama integrates seamlessly with Continue. You can run Ollama locally (e.g., 'ollama run mistral') and configure Continue to route all requests to your local Ollama instance, creating a fully private, zero-cost AI coding setup.
Which is faster for code generation—Continue or Ollama?
Continue with a paid API (OpenAI GPT-4o, Claude 3.5) is typically faster for quality responses due to larger models. Ollama's speed depends on your hardware; on a modern GPU, Mistral 7B (running in Ollama) can generate code in 1-3 seconds, while CPU-only setups may take 10-30 seconds.
Can Ollama be used in production or just for local development?
Ollama can be deployed in production. It exposes a REST API (default localhost:11434) that can be containerized with Docker, run on servers, or integrated into applications. Many teams use Ollama to power private LLM backends for cost-sensitive or privacy-critical applications.
Not by default—Continue requires internet to reach cloud LLM providers. However, if you configure it to use Ollama (running locally), then yes, Continue works fully offline with zero external API calls.
How to Choose Between Continue and Ollama
Primary Purpose: Continue has IDE-integrated coding copilot, while Ollama has Local LLM runtime engine.
Supported Editors: Continue has VS Code, JetBrains IDEs, Vim, while Ollama has None (CLI/API only).
Model Sources: Continue has OpenAI, Claude, Gemini, Ollama, LocalAI, while Ollama has Hugging Face models only.
Local Execution: Continue has Optional via Ollama backend, while Ollama has Primary function.
Consider: Memory Footprint (Typical Setup)
Memory Footprint (Typical Setup): Continue has 200-500 MB IDE extension, while Ollama has 50-200 MB runtime + model size.
Consider: Privacy Mode (Zero Cloud Calls)
Privacy Mode (Zero Cloud Calls): Continue has Yes, when using Ollama backend, while Ollama has Yes, all processing local.
Installation Complexity: Continue has Single extension install (2 minutes), while Ollama has CLI install + model download (5-15 minutes).