NVIDIA Quadro M4000

8 GB VRAM120 W TDP0 providers0 offerings0 regions

The NVIDIA Quadro M4000 is an enterprise-class GPU built on the Maxwell architecture, featuring 8 GB of memory with 192 GB/s of memory bandwidth and a 120 W TDP. It delivers 2.6 TFLOPS of FP32 performance.

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Hardware specifications

Same across all providers

Memory

8 GB

What LLMs fit? ↓

TDP

120 W

Memory bandwidth

192 GB/s

Architecture

Maxwell

FP32 performance

2.6 TFLOPS

Brand

NVIDIA

Series

Quadro

NVIDIA Quadro M4000 Price History

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Provider	Count	vCPU	RAM	Region	Per GPU hour	Total/hr	Action
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LLMs that fit on the NVIDIA Quadro M4000

Estimated VRAM for popular open-weight LLMs at 16-bit (FP16/BF16), 8-bit (FP8/INT8) and 4-bit (INT4/MXFP4) precision, against 8 GB per GPU.

Model	Parameters	16-bit	8-bit	4-bit
Gemma 3 12B Google	12.2B	29 GB Too large	16 GB Too large	9.4 GB Tight on 1× · 2% spare
Granite 4.1 8B IBM	8.8B	21 GB Too large	12 GB Too large	6.8 GB 1× · 1.2 GB free
Qwen3 8B Alibaba	8.2B	20 GB Too large	11 GB Too large	6.3 GB 1× · 1.7 GB free
Llama 3.1 8B Instruct Meta	8B	19 GB Too large	11 GB Too large	6.2 GB 1× · 1.8 GB free
Mistral 7B Instruct v0.3 Mistral AI	7.2B	17 GB Too large	9.6 GB Tight on 1× · 0% spare	5.6 GB 1× · 2.4 GB free
Qwen3 4B Alibaba	4B	9.7 GB Too large	5.3 GB 1× · 2.7 GB free	3.1 GB 1× · 4.9 GB free

Estimates: model weights plus 20% for KV cache and runtime overhead, at short context lengths. Long contexts and large batches need more. Rows marked “tight” hold the weights but not that full margin. A ×N figure is the total VRAM across N of these GPUs and makes no claim about interconnect throughput. How we estimate this

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Frequently asked questions

How much VRAM does the Quadro M4000 have?

The Quadro M4000 comes with 8 GB of VRAM, which determines the largest models and batch sizes it can hold in memory for training and inference.

Which LLMs can I run on the Quadro M4000?

With 8 GB of VRAM, a single Quadro M4000 can serve models such as Granite 4.1 8B, Qwen3 8B, Llama 3.1 8B Instruct, Mistral 7B Instruct v0.3. The table above lists the estimated VRAM for each model at 16-bit, 8-bit and 4-bit precision, including the multi-GPU configurations needed for larger models.