Olmo 3 7B — VRAM, Speed & Local Setup

Written by Jakub Rusinowski · Last updated September 19, 2026

Model libraryOlmo 3 → Olmo 3 7B

The small Olmo 3, in Base, Instruct and Think builds. Runs on an 8 GB card at Q4. Its value is provenance: every token it was trained on is published.

Olmo 3 7B needs about 5 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters7 Billion
Context window65,536
ArchitectureDense
ProviderAi2 (Allen Institute for AI)
LicenceApache 2.0
Specified atQ4_K_M
System RAM16 GB
Record updated2026-09-19

Corroborated — Two or more independent sources agree on these figures, but the model card itself was not retrieved. Treat the numbers as good rather than confirmed. Still unconfirmed: context.

Licence

Apache-2.0commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB). Weights plus framework overhead only — this model publishes no architecture we can read, so no KV cache is included. A real session needs more; the figure is a floor, not a target. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantBits/weightWeightsVRAM neededEst. speedFit on 24 GB
Q2_K2.632.3 GB3.1 GB~166 tok/s (est.)Fits comfortably
Q3_K_M3.413 GB3.8 GB~144 tok/s (est.)Fits comfortably
Q4_K_M4.834.2 GB5 GB~117 tok/s (est.)Fits comfortably
Q5_K_M5.675 GB5.8 GB~105 tok/s (est.)Fits comfortably
Q6_K6.565.7 GB6.5 GB~95 tok/s (est.)Fits comfortably
Q8_08.507.4 GB8.2 GB~78 tok/s (est.)Fits comfortably
F1616.0014 GB14.8 GB~47 tok/s (est.)Fits comfortably

Want to set your own context length and KV-cache quantization? Use the interactive VRAM calculator.

Buy This HardwareIntel Arc B570 10GB — 10 GB VRAM · 150 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Olmo 3 7B is the Intel Arc B570 (10 GB).

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Intel Arc B570 10GB
10 GB VRAM · 150 W board power
2026 prices are volatile — check the current listing.
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How to Run Olmo 3 7B

Install Ollama, then run:

ollama run olmo-3

Weights on Hugging Face: allenai/Olmo-3-1025-7B.

Best for: research, reproducibility, chat, fine tuning.

Other Olmo 3 Sizes

Olmo 3 7B — Frequently Asked Questions

How much VRAM does Olmo 3 7B need?
About 5 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Olmo 3 7B run on an RTX 4090 (24 GB)?
Yes. Olmo 3 7B needs about 5 GB at Q4_K_M, inside a 24 GB card, at an estimated 117 tokens/sec.
How do I run Olmo 3 7B locally?
Install Ollama and run `ollama run olmo-3`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Olmo 3 come in?
Olmo 3 7B (5 GB), Olmo 3 32B (20 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

← All Olmo 3 models | VRAM calculator | Check your own hardware