Olmo 3.1 32B Instruct
Ai2 Olmo 3.1 32B Instruct, a fully open model, 4-bit GGUF. Chat in your browser, plus an OpenAI-compatible API.
- Engine
- llama.cpp · Q4_K_M
- Size
- 19 GB
- GPU memory
- 22 GiB or more
- Runs on
Pick a machine
Picked Apple M4 Pro (20-core GPU): the lowest price that fits. No speed data for these GPUs yet.
Deploying accepts the rental terms. Unused budget comes back to your balance.
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Hardware that can run this
- M4 Pro · 24 GB unifiedDeployable now · $0.12/h
10 more devices could run it, none online
| Hardware | Fits | Est. speed |
|---|---|---|
| RTX 3090 · 24 GB | Q4_K_M | 28–41 tok/s |
| RTX 4090 · 24 GB | Q4_K_M | 31–44 tok/s |
| RX 7900 XTX · 24 GB | Q4_K_M | Evidence unavailable: no cited memory bandwidth for this hardware |
| M1 Max · 32 GB unified | Q4_K_M | 12–18 tok/s |
| M2 Max · 32 GB unified | Q4_K_M | 12–18 tok/s |
| M3 Max · 48 GB unified | Q4_K_M, Q8 | 9–14 tok/s |
| M4 Max · 48 GB unified | Q4_K_M, Q8 | 12–18 tok/s |
| M4 Pro · 48 GB unified | Q4_K_M, Q8 | 8–12 tok/s |
| Instinct MI210 · 64 GB | Q4_K_M, Q8 | Evidence unavailable: no cited memory bandwidth for this hardware |
| M4 Max · 64 GB unified | Q4_K_M, Q8 | 12–18 tok/s |
Speeds are estimates from memory bandwidth and weight size, not measured benchmarks. A price is the cheapest listed offer for that hardware.
Template details
- Rating
- No ratings yet
- Runs
- 0
- Min VRAM
- 24 GB
- Backend
- Metal on Apple silicon
- Weights
- 19 GB
- Version
- llamacpp-olmo-3-1-32b-instruct-v1.0.0
- Image digest
- 1f4b9cf58982…
- Health check
- SSH probe on the leased endpoint
We match GPUs on their measured runtime and dedicated VRAM. A hardware report doesn't qualify another vendor's backend.
#llm #chat #openai-api #gguf
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