Can RTX 3090 Ti run Mistral Nemo 12B?
Yes — runs locally
~42 tok/sec · Fast — smooth conversation. Responses feel real-time.
The verdict
The RTX 3090 Ti (24 GB VRAM) handles Mistral Nemo 12B comfortably using the Q8_0 quantization, which fits in 12.6 GB. Expected throughput is around 42 tokens/second, which feels Fast — smooth conversation. Responses feel real-time. in interactive use. Mistral's 12B model with excellent instruction following.
Setup tutorial: Mistral Nemo 12B on RTX 3090 Ti
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Mistral Nemo 12B on an NVIDIA GeForce RTX 3090 Ti with a Grade S performance of ~71 tok/sec using the Q8_0 quantization. This setup ensures smooth operation within the 24GB VRAM limit.
Prerequisites
Before starting, ensure you have at least 12.1GB of free disk space, a 64-bit version of Windows or Linux, the latest NVIDIA drivers (version 525.60.13 or later), and CUDA 11.8 installed.
Expected performance
With the Q8_0 quantization, you can expect a token generation rate of approximately 71 tok/sec, utilizing 12.6GB of VRAM. The remaining 11.4GB of VRAM will be available for context, allowing for a large practical context window of up to 131072 tokens.
1. Install runtimeOllama
pip install ollama
ollama config set device cuda2. Download the model
Download the Q8_0 quantized version of Mistral Nemo 12B, which is a 12.1GB file from the Hugging Face repository.
ollama pull bartowski/Mistral-Nemo-Instruct-2407-GGUF:Mistral-Nemo-Instruct-2407-Q8_0.gguf3. Run it
ollama run Mistral-Nemo-Instruct-2407-Q8_0.gguf
ollama chat --model Mistral-Nemo-Instruct-2407-Q8_0.gguf4. Optimize for RTX 3090 Ti
For optimal performance on the NVIDIA GeForce RTX 3090 Ti 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 (--flash-attn) to reduce memory consumption and improve inference speed. Given the 24GB VRAM, you can achieve a practical context window of up to 131072 tokens with 11.4GB of VRAM reserved for context.
Troubleshooting
Out of memory error during inference
Reduce the number of GPU layers by setting --n-gpu-layers to a lower value, such as 24 or 16.
Slow token generation rate
Ensure that flash attention is enabled with --flash-attn. If still slow, try increasing the batch size or reducing the sequence length.
Model fails to load
Verify that the model file is correctly downloaded and not corrupted. Try re-downloading the model file.
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio offers a user-friendly interface and is suitable for those who prefer a graphical environment. llama.cpp is highly optimized for performance and is ideal for users who need fine-grained control over the runtime settings. Jan is another lightweight option that can be used for quick prototyping. For the NVIDIA GeForce RTX 3090 Ti, Ollama is recommended due to its ease of use and good performance out-of-the-box.
Other models that run great on RTX 3090 Ti
FAQ (20)
What GPU do I need to run Mistral Nemo 12B?
To run Mistral Nemo 12B, you need a GPU with at least 7.5 GB of VRAM for the lowest quantization level, up to 12.6 GB for the highest. NVIDIA RTX 3060 or better is recommended.
Is Mistral Nemo 12B good for coding?
Mistral Nemo 12B is well-suited for coding tasks due to its strong instruction-following capabilities and large context length of 131,072 tokens.
Mistral Nemo 12B vs Llama 3.1 8B?
Mistral Nemo 12B has more parameters (12B vs 8B) and a longer context length (131,072 vs 4,096), making it generally more powerful but requiring more VRAM.
Can I run Mistral Nemo 12B on a Mac?
Yes, you can run Mistral Nemo 12B on a Mac with an M1 or M2 chip, but performance will be better on a machine with a dedicated GPU.
How much VRAM does Mistral Nemo 12B need?
The VRAM requirement for Mistral Nemo 12B ranges from 7.5 GB to 12.6 GB, depending on the quantization level used.
Is Mistral Nemo 12B censored?
Mistral Nemo 12B is not inherently censored, but it follows ethical guidelines and can be fine-tuned to avoid generating harmful content.
Is Mistral Nemo 12B commercial-use allowed?
Yes, Mistral Nemo 12B is licensed under Apache-2.0, which allows for commercial use without additional fees.
Mistral Nemo 12B context length?
Mistral Nemo 12B has a context length of 131,072 tokens, allowing it to process very long sequences of text.
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