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DATASHEET // OLLAMA

Ollama

One-command local LLM runtime.

OPEN SOURCECPU-CAPABLERuns locally
Actually FreeNo SignupOpen SourceWatermark-FreeHobbyist-OKAPI
Visit OllamaUPDATED 2026-05-15 · DIRECT LINK
ollama.com
Ollama — preview image

HARDWARE REQUIREMENTS //

Runs locally · Mid GPU (12 GB)

CPU-CAPABLE
Min VRAM
None
Rec. VRAM
16 GB
Min RAM
8 GB
Rec. RAM
32 GB
Disk
50 GB
GPU class
Mid GPU
CUDA optional (NVIDIA)Apple Silicon ✓CPU-CapableQuant: Q4_K_M, Q5_K_M, Q6_K +2

7B Q4 runs on 8 GB. 13B Q4 on 12 GB. 70B Q4 needs 48 GB unified or split GPU.

[ EDITORIAL PICK ]

Why we recommend Ollama

DERIVED FROM METADATA — NOT SPONSORED
  • Open source

    Source is public — you can audit it, fork it, and you'll never lose access to your workflows if Ollama the company changes direction.

  • CPU-capable

    Doesn't require a dedicated GPU — useful on laptops and headless servers.

  • Apple Silicon

    Native Metal / MPS support — runs on M-series Macs without CUDA gymnastics.

  • Top-tier pick

    Power-user score 94/100 — consistently rated highly by people who use this every day, not just benchmark chasers.

[ EVIDENCE NOTE ]

Documentation-led datasheet

This page summarizes upstream documentation, release information, and editorially reviewed catalogue fields. It is not presented as a hands-on benchmark. Verify changing requirements at the official project; report stale data through our corrections channel.

Memory guide →

AT-A-GLANCE SIGNALS //

DERIVED FROM THIS PAGE'S DATA
  • Install difficulty
    Easy

    Runs CPU-only — no CUDA / driver gymnastics required.

  • Hardware comfort
    Runs anywhere

    No dedicated GPU required.

  • Ecosystem
    Strong devkit

    Open-source AND ships an API — easy to integrate, possible to host yourself.

  • Verification
    Recent

    Catalogue entry last updated 62 days ago — re-verification due soon.

[ COMMUNITY GUIDES & WORKFLOWS ]

Tutorials & deep-dives for Ollama

Hand-picked from YouTube, Reddit, GitHub, and the wider web. Each link goes straight to the source — we don't intercept or rewrite anything.

[ MORE IN THIS NICHE ]

Other local llm runners tools we rate

Three picks across different tradeoffs — so you don't end up with three near-clones of Ollama.

LIGHTEST HARDWARE //

Transformers

The library every LLM ships against first.

OPEN SOURCE2–24 GB VRAM
BEST FREE OPTION //

llama.cpp

The C++ inference engine powering most local LLMs.

OPEN SOURCECPU-CAPABLE
TOP QUALITY //

vLLM

High-throughput LLM serving for GPUs.

OPEN SOURCE24–80 GB VRAM

What is Ollama?

Ollama wraps llama.cpp behind a clean CLI and HTTP API. Pull a model (`ollama run llama3.1`), get a chat or an OpenAI-compatible endpoint. Excellent default for hobbyists running quantized models.

Pros & cons

✓ PROS

  • Easiest local LLM onboarding
  • OpenAI-compatible API
  • Great Apple Silicon performance

– CONS

  • Opinionated model registry
  • Less control than raw llama.cpp
  • Single-user by default

What's actually free?

Fully free / OSS. You provide the hardware.

✓ Actually FreeNo SignupOpen SourceWatermark-Free

Alternatives

llama.cpp

The C++ inference engine powering most local LLMs.

OPEN SOURCECPU-CAPABLE

vLLM

High-throughput LLM serving for GPUs.

OPEN SOURCE24–80 GB VRAM
VRAM fit24–80 GB