Can RTX 4070 SUPER run Dolphin Mistral 24B (Venice Edition)?

Yes — runs locally

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

Your VRAM

12 GB

Model size

24B

Best quant

Q4_K_M

VRAM needed

14.9 GB

The verdict

The RTX 4070 SUPER (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 4070 SUPER

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

TL;DR

Run Dolphin Mistral 24B (Venice Edition) on an NVIDIA GeForce RTX 4070 SUPER with Q4_K_M quantization for 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, the latest NVIDIA drivers (version 525.60 or later), and CUDA 11.8 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 of VRAM means you should aim for a practical context window of around 16,000 tokens to avoid out-of-memory errors.

1. Install runtimeOllama

pip install ollama
ollama init

2. Download the model

Download the Q4_K_M quantized version of Dolphin Mistral 24B (Venice Edition), 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
ollama chat Dolphin-Mistral-24B-Venice-Edition-Q4_K_M

4. Optimize for RTX 4070 SUPER

For optimal performance on the NVIDIA GeForce RTX 4070 SUPER with 12GB VRAM, set --n-gpu-layers to 12 to utilize the available VRAM efficiently. Enable flash attention (--flash-attn) to speed up inference and reduce memory usage. Given the 14.9GB VRAM requirement, you will have approximately -2.9GB of VRAM headroom, which limits the maximum context window you can use effectively.

Troubleshooting

Out of memory error during inference

Reduce the context length or decrease the number of GPU layers using --n-gpu-layers <N> where N is less than 12.

Slow token generation rate

Ensure flash attention is enabled with --flash-attn. If still slow, try reducing the batch size or context length.

Model fails to load

Verify that the model file has been downloaded correctly and is not corrupted. Re-run the download command if necessary.

Alternative runtimes

Consider using LM Studio for a more user-friendly interface, llama.cpp for fine-grained control over optimizations, or Jan for a lightweight alternative. Use LM Studio if you prefer a GUI, llama.cpp for advanced tuning options, or Jan for minimal resource usage on this GPU.

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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