Can RTX 4090 run OLMoE 1B-7B?
Yes — runs locally
~96 tok/sec · Instant — feels like typing. No noticeable delay.
The verdict
The RTX 4090 (24 GB VRAM) handles OLMoE 1B-7B comfortably using the Q8_0 quantization, which fits in 7.3 GB. Expected throughput is around 96 tokens/second, which feels Instant — feels like typing. No noticeable delay. in interactive use. Fully open MoE — 7 B total, only 1.3 B active per token. Tiny footprint, surprisingly capable.
Setup tutorial: OLMoE 1B-7B on RTX 4090
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run OLMoE 1B-7B on an NVIDIA GeForce RTX 4090 with Grade S performance at ~138 tok/sec using the Q8_0 quantization. Requires 7.3GB VRAM.
Prerequisites
Before starting, ensure you have at least 10GB of free disk space, a compatible operating system (Windows or Linux), the latest NVIDIA drivers (version 525.60.12 or later), and CUDA 11.8 installed.
Expected performance
With the Q8_0 quantization, you can expect ~138 tok/sec performance, utilizing 7.3GB of VRAM. This leaves 16.6GB of VRAM headroom, allowing for a full context window of 4096 tokens without performance degradation.
1. Install runtimeOllama
pip install ollama
ollama config set device cuda2. Download the model
Download the Q8_0 quantized version of OLMoE 1B-7B (6.9GB file) from Hugging Face.
ollama pull bartowski/OLMoE-1B-7B-0924-Instruct-GGUF:OLMoE-1B-7B-0924-Instruct-Q8_0.gguf3. Run it
ollama run OLMoE-1B-7B-0924-Instruct-Q8_0 --context-length 4096
ollama chat OLMoE-1B-7B-0924-Instruct-Q8_04. Optimize for RTX 4090
For optimal performance on the NVIDIA GeForce RTX 4090 with 24GB VRAM, use the --n-gpu-layers parameter to offload layers to the GPU. Set --n-gpu-layers to 32 to balance between speed and memory usage. Enable flash attention with --flash-attn to reduce memory consumption and improve speed. With 24GB VRAM, you can achieve a practical context window of up to 4096 tokens while maintaining high performance.
Troubleshooting
Out of memory errors during inference
Reduce the --n-gpu-layers value to 16 or lower to free up more VRAM.
Slow inference speed
Ensure that flash attention is enabled with --flash-attn and that the CUDA backend is correctly configured.
Model not loading
Verify that the model file has been downloaded correctly and that the Ollama runtime is properly installed and configured.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio offers a graphical interface and is suitable for users who prefer a GUI. llama.cpp is highly optimized for low-memory systems but may require more manual configuration. Jan is another lightweight option that supports a wide range of models but may not offer the same level of performance as Ollama on the RTX 4090.
Other models that run great on RTX 4090
FAQ (20)
What GPU do I need to run OLMoE 1B-7B?
To run OLMoE 1B-7B, you need a GPU with at least 4.4 GB of VRAM for the smallest quantized version, up to 7.3 GB for the full model.
Is OLMoE 1B-7B good for coding?
OLMoE 1B-7B is versatile and can handle coding tasks well, though it may not be as specialized as models specifically trained for code generation.
OLMoE 1B-7B vs Llama 3.1 8B?
OLMoE 1B-7B has fewer parameters (6.9B) compared to Llama 3.1 8B, but it uses a more efficient MoE architecture, making it lighter and potentially faster in certain tasks.
Can I run OLMoE 1B-7B on a Mac?
Yes, you can run OLMoE 1B-7B on a Mac with an M1 or M2 chip, provided you have the necessary VRAM and system resources.
How much VRAM does OLMoE 1B-7B need?
The VRAM requirement for OLMoE 1B-7B ranges from 4.4 GB to 7.3 GB, depending on the quantization level used.
Is OLMoE 1B-7B censored?
OLMoE 1B-7B is not inherently censored, but its responses can be filtered or moderated using external tools to ensure appropriate content.
Is OLMoE 1B-7B commercial-use allowed?
Yes, OLMoE 1B-7B is licensed under Apache-2.0, which allows for commercial use without additional fees.
OLMoE 1B-7B context length?
OLMoE 1B-7B supports a context length of 4096 tokens, which is suitable for handling longer conversations and documents.
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