dphn·Mistral·MistralForCausalLM

Dolphin Mistral 24B Venice Edition — Hardware Requirements & GPU Compatibility

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7.3K downloads 449 likes33K context

Specifications

Publisher
dphn
Family
Mistral
Parameters
23.6B
Architecture
MistralForCausalLM
Context Length
32,768 tokens
Vocabulary Size
131,072
Release Date
2025-09-08
License
Apache 2.0

Get Started

How Much VRAM Does Dolphin Mistral 24B Venice Edition Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_K3.4010.7 GB
Q3_K_S3.5011.0 GB
Q3_K_M3.9012.2 GB
Q4_04.0012.5 GB
Q4_K_M4.8014.9 GB
Q5_K_M5.7017.5 GB
Q6_K6.6020.2 GB
Q8_08.0024.3 GB

Which GPUs Can Run Dolphin Mistral 24B Venice Edition?

Q4_K_M · 14.9 GB

Dolphin Mistral 24B Venice Edition (Q4_K_M) requires 14.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 20+ GB is recommended. Using the full 33K context window can add up to 6.3 GB, bringing total usage to 21.1 GB. 17 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.

Which Devices Can Run Dolphin Mistral 24B Venice Edition?

Q4_K_M · 14.9 GB

27 devices with unified memory can run Dolphin Mistral 24B Venice Edition, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).

Related Models

Frequently Asked Questions

How much VRAM does Dolphin Mistral 24B Venice Edition need?

Dolphin Mistral 24B Venice Edition requires 14.9 GB of VRAM at Q4_K_M, or 24.3 GB at Q8_0. Full 33K context adds up to 6.3 GB (21.1 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 23.6B × 4.8 bits ÷ 8 = 14.1 GB

KV Cache + Overhead 0.8 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 7 GB (at full 33K context)

VRAM usage by quantization

14.9 GB
21.1 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 4090 run Dolphin Mistral 24B Venice Edition?

Yes, at Q6_K (20.2 GB) or lower. Higher quantizations like Q8_0 (24.3 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.

What's the best quantization for Dolphin Mistral 24B Venice Edition?

For Dolphin Mistral 24B Venice Edition, Q4_K_M (14.9 GB) offers the best balance of quality and VRAM usage. Q4_K_L (15.2 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 7.2 GB.

VRAM requirement by quantization

IQ2_XXS
7.2 GB
Q2_K
10.7 GB
Q3_K_L
12.8 GB
Q4_K_M
14.9 GB
Q4_K_L
15.2 GB
Q8_0
24.3 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Dolphin Mistral 24B Venice Edition on a Mac?

Dolphin Mistral 24B Venice Edition requires at least 7.2 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.

Can I run Dolphin Mistral 24B Venice Edition locally?

Yes — Dolphin Mistral 24B Venice Edition can run locally on consumer hardware. At Q4_K_M quantization it needs 14.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Dolphin Mistral 24B Venice Edition?

At Q4_K_M, Dolphin Mistral 24B Venice Edition can reach ~196 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~44 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: AMD Instinct MI300X5300 ÷ 14.9 × 0.55 = ~196 tok/s

Estimated speed at Q4_K_M (14.9 GB)

~196 tok/s
~44 tok/s
~147 tok/s
~121 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Dolphin Mistral 24B Venice Edition?

At Q4_K_M, the download is about 14.14 GB. The full-precision Q8_0 version is 23.57 GB. The smallest option (IQ2_XXS) is 6.48 GB.

Which GPUs can run Dolphin Mistral 24B Venice Edition?

17 consumer GPUs can run Dolphin Mistral 24B Venice Edition at Q4_K_M (14.9 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 5 GPUs have plenty of headroom for comfortable inference.

Which devices can run Dolphin Mistral 24B Venice Edition?

27 devices with unified memory can run Dolphin Mistral 24B Venice Edition at Q4_K_M (14.9 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.