Can M3 Max run Dolphin Mistral 24B (Venice Edition)?
Yes — runs locally
~26 tok/sec · Good — slight pause, then text streams smoothly.
The verdict
The M3 Max (128 GB VRAM) handles Dolphin Mistral 24B (Venice Edition) comfortably using the BF16 quantization, which fits in 48.5 GB. Expected throughput is around 26 tokens/second, which feels Good — slight pause, then text streams smoothly. 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 M3 Max
AI-generated, GPU-specific. Verified commands for your exact hardware.
Dolphin Mistral 24B (Venice Edition) runs exceptionally well on the Apple M3 Max with a Grade S performance, using the BF16 quantization. Expect around 35 tokens per second with comfortable performance.
Prerequisites
Before starting, ensure you have at least 50GB of free disk space, macOS 13.0 or later, and Xcode Command Line Tools installed. You can install Xcode CLT by running `xcode-select --install` in your terminal.
Expected performance
With the BF16 quantization, you can expect a token generation rate of approximately 35 tokens per second. The model will use 48.5GB of VRAM, leaving 79.5GB of VRAM available for context. This allows for a practical context window of up to 32768 tokens, making it suitable for long-form content generation and complex tasks.
1. Install runtimeOllama (preferred on Apple Silicon)
brew install ollama
ollama init2. Download the model
Download the BF16 quantized model, which is 48.0GB in size, from the Hugging Face repository.
ollama pull dphn/Dolphin-Mistral-24B-Venice-Edition3. Run it
ollama run dphn/Dolphin-Mistral-24B-Venice-Edition
ollama chat --model dphn/Dolphin-Mistral-24B-Venice-Edition4. Optimize for M3 Max
To optimize performance on the Apple M3 Max, leverage the Metal/MLX backend and unified memory. The 128GB VRAM allows for efficient use of the 48.5GB required by the BF16 quantization, leaving ample headroom for large context windows. Ensure that MPS layers are enabled to take full advantage of the GPU's capabilities.
Troubleshooting
Insufficient VRAM allocation
Ensure that the Metal/MLX backend is properly configured and that the system is not running other resource-intensive applications.
Slow token generation
Check if the MPS layers are enabled and if the unified memory is being utilized efficiently. Restart the Ollama service with `ollama restart`.
Model fails to load
Verify the integrity of the downloaded model files with `ollama verify dphn/Dolphin-Mistral-24B-Venice-Edition`. If issues persist, try re-downloading the model.
Alternative runtimes
While Ollama is the preferred runtime for Apple Silicon, you can also consider LM Studio for a more graphical interface, llama.cpp for command-line flexibility, and MLX for direct Metal integration. Jan is another option for advanced users who need more control over the runtime environment. Choose an alternative based on your specific needs, such as ease of use or fine-grained control.
Other models that run great on M3 Max
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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