01What it can do
- Explicit step-by-step reasoning (chain of thought)
- Dense 7B: fits on an 8 GB GPU in Q4 (~4.2 GB)
- 100% open OLMo base (weights + data + code)
- Permissive Apache 2.0 license
- —Community fine-tune, unofficial Allen AI model
- —Modest 16k context compared with recent 128k models
- —No official Ollama tag (deployment via Hugging Face)
04Install
Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.
02Required memory
Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.
What hardware do you need for OLMo 3 7B Think (SFT)?
To run OLMo 3 7B Think (SFT) locally with Q4 quantization, you need about 4.2 GB of VRAM. An option to compare: RTX 5060 Ti 16GB (ASUS Prime) — leave some headroom for the system and context; check engine compatibility with the GPU.
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On the go: OLMo 3 7B Think (SFT) also runs on a RTX laptop PC (16 GB of VRAM) →
Your private ChatGPT, free, on your own machine in an hour — LM Studio, Ollama, Open WebUI, your documents, no cloud.
- Lifetime online access
- PDF + files
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03Expected speed
Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.