Can RTX 3070 Ti run Dolphin Mistral 24B (Venice Edition)?

Yes — runs locally

~0 tok/sec · Cannot run — insufficient VRAM

Your VRAM

8 GB

Model size

24B

Best quant

Q4_K_M

VRAM needed

14.9 GB

The verdict

The RTX 3070 Ti (8 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 — insufficient VRAM 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 3070 Ti

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

TL;DR

Run Dolphin Mistral 24B (Venice Edition) on an NVIDIA GeForce RTX 3070 Ti with Q4_K_M quantization. Expect ~17 tok/sec, suitable for interactive use.

Prerequisites

Before starting, ensure you have at least 15GB of free disk space, a 64-bit version of Windows or Linux, NVIDIA driver version 470.82 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 17 tokens per second, using around 14.9GB of VRAM. Given the 8GB VRAM limit, the model will utilize CPU memory, leaving about -6.9GB of VRAM for context, allowing for a practical context window of around 8192 tokens.

1. Install runtimeOllama

curl -fsSL https://ollama.ai/install.sh | sh
ollama init

2. Download the model

Download the Q4_K_M quantized model, which is a 14.4GB file.

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 --n-gpu-layers 12 --flash-attn --context-length 8192

4. Optimize for RTX 3070 Ti

For optimal performance on the NVIDIA GeForce RTX 3070 Ti with 8GB VRAM, use --n-gpu-layers 12 to offload some layers to CPU memory, enabling flash attention and setting the context length to 8192 tokens. This configuration balances VRAM usage and inference speed, ensuring the model runs efficiently within the 8GB limit.

Troubleshooting

Out of memory errors during inference

Reduce the number of GPU layers with --n-gpu-layers 8 or lower, and decrease the context length to 4096 tokens.

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

Verify that the model file has been downloaded correctly and that there is sufficient disk space available.

Alternative runtimes

For users preferring different runtimes, consider LM Studio for a more user-friendly interface, llama.cpp for advanced customization, or Jan for lightweight deployment. Each runtime has its strengths, but Ollama provides a balanced approach for this GPU, especially for interactive use.

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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