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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools competes with
Ollama
vs
vLLM

Choose Ollama when…

  • •You want to run LLMs locally on your machine
  • •Privacy or offline use cases require local models
  • •You're testing open-source models without API costs

Choose vLLM when…

  • •You're serving LLMs at high throughput in production
  • •Continuous batching and PagedAttention are needed
  • •You're running your own GPU inference cluster
Field
Ollama
vLLM
Category
LLM Infrastructure
LLM Infrastructure
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
—
—
Stars
⭐ 90,000
⭐ 32,000
Health
●80 — Active
●75 — Active
Trajectory
— not enough data
— not enough data
Synced
today
today

Ollama

Dead-simple local LLM serving. Pull and run models like Docker images. Compatible with the OpenAI API format.

vLLM

Production-grade LLM inference server. PagedAttention enables high throughput and efficient KV cache memory management.

Ollama Website ↗GitHub ↗
vLLM Website ↗GitHub ↗

Shared Connections (2)

LlamaIndexLiteLLM

Only Ollama (5)

ContinuevLLMllama.cppLLaVAMoondream

Only vLLM (11)

OllamaTogether AIModalRunPodAxolotlUnslothLlamaFactoryTorchtune
See full comparison in Explore →