Create compelling investor pitch decks with proven structures from Y Combinator, Sequoia, and top VCs. 10-15 slide frameworks.
Open Source
Skills for self-hosted AI using Ollama, LM Studio, and open-source models like DeepSeek, Qwen, and Llama. Full privacy, zero API costs, unlimited usage.
1030 skills available
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.
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