llama.
Everything we've published on llama across guides, agents, hardware reviews and glossary entries — 14 entries in total.
Guides (1)
- Local LLMs in 2026 — the complete benchmark report on portable hardwareAI Agents · 2026-04-30
Real-world benchmarks of Llama 3.3 70B, Qwen 2.5 72B, Mistral 7B, Llama 3 8B and Phi-3 mini across Raspberry Pi 5, Intel mini PCs, Apple Silicon Mac Mini, and Mac Studio. Tokens-per-second, agentic task pass rates, power and cost economics.
Agents (1)
- ZeroClaw
Privacy-first. Local LLMs only. Network egress denied at iptables. AGPL-3.0.
Hardware (7)
- Raspberry Pi 5
The default starting point for pocket AI in 2026. 4–8 GB of LPDDR4X, ARM Cortex-A76, sub-€100, runs Hermes Agent (no browser tool) or Nanobot comfortably.
- Intel NUC 13 / Mini PC
Mini PCs at €300–600 with i5/i7 + 16–32 GB RAM. The sweet spot for self-hosted AI agents that need browser automation and decent local model performance.
- Mac Mini M4 / M4 Pro
The single best small-form-factor host for local LLMs in 2026. Apple Silicon unified memory makes 70B-class models tractable on a desk-sized machine.
- Geekom IT13 / generic Intel mini PC
Sub-€500 mini PC with i7-13620H, 32 GB RAM, 1 TB SSD. The pragmatic alternative to the Intel NUC.
- Mac Studio M3 Ultra
192 GB unified memory ceiling. The local-LLM workstation. Llama 3.3 70B at 22 tok/s. €4,500+.
- MacBook Air M3 / M4
Fanless laptop with up to 24 GB unified memory. Runs Mistral 7B Q4 silently on the train. €1,299+.
- Minisforum UM790 Pro
Ryzen 9 7940HS mini PC. 32–64 GB RAM. The best Linux mini PC value at €700-900.
Glossary (5)
- Local LLM — Language model running on local hardware rather than via cloud API. Llama, Qwen, Mistral local variants.
- Ollama — Local LLM runtime that exposes an OpenAI-compatible API over local model weights.
- Llama — Meta's family of open-weight large language models. Llama 3.3 70B is the leading open frontier model in 2026.
- llama.cpp — C++ inference engine for LLMs. The runtime under most local-LLM setups, including Ollama.
- GGUF — File format for storing quantised LLM weights, used by llama.cpp and Ollama.