Ollama vs Groq
Both are alternatives to OpenAI API (ChatGPT). Here's how they stack up — verified facts, no spin.
Also searched as Groq vs Ollama — same comparison, one verdict.
Ollama
TOP PICKRun Llama, Mistral, Qwen and more with one command.
Ollama is the simplest way to pull and run open models locally with an OpenAI-compatible API. It handles model management and GPU acceleration out of the box, so a workstation with a modern GPU becomes a private inference server.
Groq
The speed king — open models at 500+ tokens/second on custom LPU chips.
Groq runs open models (Llama and friends) on its custom LPU hardware and is, as of mid-2026, the fastest mainstream inference API available — 500+ tokens per second, at prices mostly under $1 per million tokens (Llama 3.3 70B at $0.59/$0.79). If your product's bottleneck is latency — voice agents, live UX, rapid tool loops — Groq is the honest answer. It's a proprietary hosted platform, but like Together, the models themselves are open, so you're renting speed, not locking in your stack.
Side by side
| Ollama | Groq | |
|---|---|---|
| Sovereignty Score | 92 | 42 |
| Open source | Yes | No |
| Self-hostable | Yes | No |
| Local-first | Yes | No |
| License | MIT | Proprietary (platform); serves open-weight models |
| Pricing | Free / self-host (you pay only for your own hardware + power) | Most models under $1 per 1M tokens; Llama 3.3 70B $0.59/$0.79; batch −50% |
Ollama is Macrostack's recommended OpenAI API (ChatGPT) alternative, so it's our pick here.
Ollama
Strengths
- +One-command model install
- +OpenAI-compatible endpoint for drop-in swaps
- +Fully offline and private
Trade-offs
- −Quality depends on the model + your VRAM
- −You manage your own hardware
Groq
Strengths
- +Fastest inference on the market (500+ tok/s)
- +Very low prices on open models
- +OpenAI-compatible API — near drop-in
Trade-offs
- −Hosted-only; custom hardware means no self-host path for the speed
- −Model catalog is narrower than Together's
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Facts verified 2026-07-04. Licenses and pricing change — spotted something out of date? That's a correction we want.