Olmo 3 7B Instruct — Hardware Requirements & GPU Compatibility
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OLMo 3 7B Instruct is an instruction-tuned language model from the Allen Institute for AI, built as part of their Open Language Model initiative. Like all OLMo releases, it comes with fully open training data, code, and intermediate checkpoints, setting a high standard for reproducibility and scientific transparency in the LLM space. At roughly 7 billion parameters, this model delivers competitive performance on instruction following, reasoning, and general knowledge tasks while remaining runnable on consumer GPUs with 8 GB or more of VRAM. It is an excellent choice for users who value open science and want a capable, well-documented model for local chat and assistant applications.
105.4K downloads
122 likesSpecifications
- Publisher
- Allen AI
- Parameters
- 528384
- Architecture
- Olmo3ForCausalLM
- Context Length
- 65,536 tokens
- Vocabulary Size
- 100,278
- Release Date
- 2026-01-05
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Olmo 3 7B Instruct Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 1.4 GB | 34.7 GB | 0.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Olmo 3 7B Instruct?
BF16 · 1.4 GBOlmo 3 7B Instruct (BF16) requires 1.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. Using the full 66K context window can add up to 33.3 GB, bringing total usage to 34.7 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Olmo 3 7B Instruct?
BF16 · 1.4 GB33 devices with unified memory can run Olmo 3 7B Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (1)
Frequently Asked Questions
- How much VRAM does Olmo 3 7B Instruct need?
Olmo 3 7B Instruct requires 1.4 GB of VRAM at BF16. Full 66K context adds up to 33.3 GB (34.7 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 528384 × 16 bits ÷ 8 = 0 GB
KV Cache + Overhead ≈ 1.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 34.7 GB (at full 66K context)
VRAM usage by quantization
BF161.4 GBBF16 + full context34.7 GB- Can I run Olmo 3 7B Instruct on a Mac?
Olmo 3 7B Instruct requires at least 1.4 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Olmo 3 7B Instruct locally?
Yes — Olmo 3 7B Instruct can run locally on consumer hardware. At BF16 quantization it needs 1.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Olmo 3 7B Instruct?
At BF16, Olmo 3 7B Instruct can reach ~2128 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~478 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 1.4 × 0.55 = ~2128 tok/s
Estimated speed at BF16 (1.4 GB)
AMD Instinct MI300X~2128 tok/sNVIDIA GeForce RTX 4090~478 tok/sNVIDIA H100 SXM~1590 tok/sAMD Instinct MI250X~1316 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Olmo 3 7B Instruct?
At BF16, the download is about 0.00 GB.