Open Source

Run powerful AI models locally with complete control over your data. Open-source tools like Ollama and LM Studio make it easy to deploy models rivaling proprietary services — no cloud dependency, no API costs, no data leaving your machine. The open-source ecosystem in 2026 has reached parity with commercial offerings for many tasks.

Popular Models to Run Locally:

• DeepSeek V3.2 — 671B total / 37B active parameters, comparable to GPT-5, MIT license
• Qwen3 — 700M+ downloads, models from 0.6B to 235B, Apache 2.0 license
• Llama 4 Scout/Maverick — Multimodal, up to 10M token context
• Mistral / Codestral — Strong for coding tasks
• Gemma, Phi, NVIDIA Nemotron — Smaller models for consumer hardware

Local Deployment Tools:

• Ollama — CLI-first, 20% faster inference, lower memory usage, ideal for developers and production
• LM Studio — GUI-focused with built-in chat, model discovery, and easy downloads
• LocalAI — OpenAI-compatible API for drop-in replacement
• vLLM — High-throughput serving for production deployments

Key Strengths:

• Complete privacy with local execution — no data leaves your machine
• Zero ongoing costs after hardware setup
• Works fully offline without internet
• Mix and match models for different tasks
• Unlimited usage with no rate limits or subscriptions
• Fine-tune and customize models for your domain

Best For: Privacy-critical workflows, air-gapped environments, unlimited AI experimentation, custom model fine-tuning, and developers who want full ownership of their AI stack.