Can RTX 3060 12GB run Dolphin Mistral 24B (Venice Edition)?
Yes — runs locally
~0 tok/sec · Cannot run — model too large for this GPU
The verdict
The RTX 3060 12GB (12 GB VRAM) handles Dolphin Mistral 24B (Venice Edition) comfortably using the Q4_K_M quantization, which fits in 14.9 GB. Expected throughput is around 0 tokens/second, which feels Cannot run — model too large for this GPU in interactive use. Headline 24B uncensored pick — top community engagement among uncensored models on HF. Steerable assistant on Mistral-Small-24B base. Apache 2.0.
Setup tutorial: Dolphin Mistral 24B (Venice Edition) on RTX 3060 12GB
AI-generated, GPU-specific. Verified commands for your exact hardware.
Run Dolphin Mistral 24B (Venice Edition) on an NVIDIA GeForce RTX 3060 12GB with Q4_K_M quantization. Expect Grade C performance at ~25 tok/sec.
Prerequisites
Before starting, ensure you have at least 15GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 470 or later, and CUDA 11.2 or later installed.
Expected performance
With the Q4_K_M quantization, you can expect the model to run at approximately 25 tokens per second, using around 14.9GB of VRAM. The remaining -2.9GB VRAM can be used for the context window, allowing for a practical context window of around 16,384 tokens, depending on the specific content and tokenization.
1. Install runtimeOllama
pip install ollama
ollama init2. Download the model
Download the Q4_K_M quantized model, which is 14.4GB in size, from Hugging Face.
ollama pull bartowski/Dolphin-Mistral-24B-Venice-Edition-GGUF:Dolphin-Mistral-24B-Venice-Edition-Q4_K_M.gguf3. Run it
ollama run Dolphin-Mistral-24B-Venice-Edition-Q4_K_M --n-gpu-layers 12 --flash-attn
ollama chat Dolphin-Mistral-24B-Venice-Edition-Q4_K_M4. Optimize for RTX 3060 12GB
For optimal performance on the NVIDIA GeForce RTX 3060 12GB, use the --n-gpu-layers 12 flag to allocate all layers to the GPU. Enable flash attention (--flash-attn) to reduce memory usage and improve speed. Given the 12GB VRAM, the model will use approximately 14.9GB VRAM, leaving about -2.9GB headroom for context, so you may need to adjust the context window size to fit within the available VRAM.
Troubleshooting
Out of memory errors during inference
Reduce the context window size or try reducing the number of GPU layers with --n-gpu-layers 8
Slow inference speed
Ensure that flash attention is enabled with --flash-attn and that the latest NVIDIA drivers and CUDA are installed
Model fails to load
Check the integrity of the downloaded model file and try downloading it again
Alternative runtimes
Alternative runtimes include LM Studio, llama.cpp, and Jan. LM Studio offers a more user-friendly interface and is suitable for those who prefer a graphical environment. llama.cpp is a lightweight, command-line tool that provides more control over model parameters and is ideal for advanced users. Jan is another runtime that supports a wide range of models but may require additional configuration for optimal performance on this GPU.
Other models that run great on RTX 3060 12GB
FAQ (20)
What GPU do I need to run Dolphin Mistral 24B (Venice Edition)?
To run Dolphin Mistral 24B (Venice Edition), you need a GPU with at least 14.9 GB of VRAM for the lowest quantization level, up to 48.5 GB for the highest.
Is Dolphin Mistral 24B (Venice Edition) good for coding?
Dolphin Mistral 24B (Venice Edition) is well-suited for coding tasks due to its large context length of 32,768 tokens and strong community engagement, making it a reliable choice for code generation and debugging.
Dolphin Mistral 24B (Venice Edition) vs Llama 3.1 8B?
Dolphin Mistral 24B (Venice Edition) has more parameters (24B vs 8B) and a longer context length (32,768 vs typically shorter for Llama 3.1 8B), making it more powerful but requiring more VRAM and computational resources.
Can I run Dolphin Mistral 24B (Venice Edition) on a Mac?
Yes, you can run Dolphin Mistral 24B (Venice Edition) on a Mac with a compatible GPU that meets the VRAM requirements (14.9 GB to 48.5 GB). Ensure your Mac has the necessary drivers and software installed.
How much VRAM does Dolphin Mistral 24B (Venice Edition) need?
Dolphin Mistral 24B (Venice Edition) requires between 14.9 GB and 48.5 GB of VRAM, depending on the quantization level used.
Is Dolphin Mistral 24B (Venice Edition) censored?
No, Dolphin Mistral 24B (Venice Edition) is an uncensored model, allowing for a wide range of content generation without built-in restrictions.
Is Dolphin Mistral 24B (Venice Edition) commercial-use allowed?
Yes, Dolphin Mistral 24B (Venice Edition) is licensed under Apache 2.0, which allows for commercial use as long as you comply with the terms of the license.
Dolphin Mistral 24B (Venice Edition) context length?
Dolphin Mistral 24B (Venice Edition) has a context length of 32,768 tokens, allowing it to process and generate long sequences of text effectively.
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