Can RTX 5080 run Dolphin Mistral 24B (Venice Edition)?

Yes — runs locally

~0 tok/sec · Cannot run — model too large for this GPU

Your VRAM

16 GB

Model size

24B

Best quant

Q4_K_M

VRAM needed

14.9 GB

The verdict

The RTX 5080 (16 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 5080

AI-generated, GPU-specific. Verified commands for your exact hardware.

TL;DR

Run Dolphin Mistral 24B (Venice Edition) on an NVIDIA GeForce RTX 5080 with Q4_K_M quantization. Expect ~33 tok/sec performance and a comfortable user experience.

Prerequisites

Before starting, ensure you have at least 20GB of free disk space, a compatible operating system (Windows or Linux), and the latest NVIDIA drivers (version 525.60.13 or later) with CUDA 11.8 installed.

Expected performance

With the Q4_K_M quantization, you can expect the model to run at approximately 33 tokens per second, using 14.9GB of VRAM. This leaves about 1.1GB of VRAM for context, enabling a practical context window of around 10,000 tokens.

1. Install runtimeOllama

pip install ollama
ollama config set runtime cuda

2. Download the model

Download the Q4_K_M quantized version of the model (14.4GB file) from Hugging Face.

ollama pull bartowski/Dolphin-Mistral-24B-Venice-Edition-GGUF:Dolphin-Mistral-24B-Venice-Edition-Q4_K_M.gguf

3. Run it

ollama run Dolphin-Mistral-24B-Venice-Edition-Q4_K_M.gguf --n-gpu-layers 16 --flash-attn
ollama chat --model Dolphin-Mistral-24B-Venice-Edition-Q4_K_M.gguf

4. Optimize for RTX 5080

For optimal performance on the NVIDIA GeForce RTX 5080 with 16GB VRAM, use the --n-gpu-layers 16 flag to offload layers to the GPU. Enable flash attention with --flash-attn to reduce memory usage and improve speed. Given the 14.9GB VRAM requirement, you will have approximately 1.1GB of VRAM left for context, allowing for a practical context window of around 10,000 tokens.

Troubleshooting

Out of memory error during inference

Reduce the number of GPU layers with --n-gpu-layers 8 or use CPU offloading with --cpu-offload

Slow inference speed

Ensure flash attention is enabled with --flash-attn and check that your CUDA drivers are up to date

Model fails to load

Verify the integrity of the downloaded model file and try re-downloading it

Alternative runtimes

Consider using LM Studio for a more user-friendly interface, llama.cpp for advanced customization options, or Jan for lightweight deployment. Ollama is recommended for its ease of use and robust performance on the NVIDIA GeForce RTX 5080.

Full Dolphin Mistral 24B (Venice Edition) details →

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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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