NVIDIA Quadro M4000
1,664
CUDA Cores
8GB
VRAM
192
GB/s
Technical Specifications
1,664
CUDA Cores
773
Base MHz
1502
Boost MHz
8GB GDDR5
256-bit bus
Performance
4.2
FP32 TFLOPS
8.4
FP16 TFLOPS
120W
TDP
Cloud Availability
1
Available Instances
$0.45/hr
Starting Price
Detailed Specifications
| Architecture | Maxwell (Unknown) |
| Release Date | 2015-06-29 |
| Launch Price | $999.00 |
| Process | 28nm |
| Transistors | 5.2B |
AI Features
none
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
9.5in
Length
4.4in
Width
1-slot
Height
About Quadro M4000 GPU
The NVIDIA Quadro M4000 was introduced in 2015 on the Maxwell architecture. Its specification combines 1,664 CUDA cores with 8GB of GDDR5, which defines both the workloads it can run and the batch sizes it can hold.
Based on its 8GB memory capacity, the Quadro M4000 is best evaluated for compact inference, rendering, computer vision, and legacy CUDA workloads. Always size the model, optimizer state, KV cache, and framework overhead together rather than choosing a GPU from core count alone.
GPUvec currently tracks 1 cloud listing for the Quadro M4000, with the lowest observed hourly rate at $0.45. Prices and availability can change by provider, region, and instance configuration, so verify the final rate before starting a workload.
For software planning, the Quadro M4000 combines 192 GB/s of memory bandwidth, CUDA compute capability the latest, and a 28nm manufacturing process. Confirm the minimum CUDA, PyTorch, TensorFlow, or driver version required by your application before renting or purchasing hardware.
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External Resources
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
What You Need to Know About the Quadro M4000
Complete Specifications for the NVIDIA Quadro M4000
The NVIDIA Quadro M4000 uses the Maxwell architecture and combines 1,664 CUDA cores with 8GB of GDDR5. GPUvec records 192 GB/s memory bandwidth alongside architecture, release date, process node, accelerator features, and physical specifications so the page can be evaluated from source data instead of model-name assumptions.
Compare NVIDIA Quadro M4000 Cloud Rental Prices per Hour
GPUvec currently tracks 1 cloud listing, with an observed starting rate of $0.45 per hour. Provider rates can vary by region, host configuration, billing model, and availability. Use the provider directory and related-GPU links to compare an available alternative when this exact accelerator is not listed.
Is the NVIDIA Quadro M4000 the Right GPU for Your AI Workload?
Start with the 8GB memory limit, then evaluate 192 GB/s memory bandwidth, compute features, and software compatibility for your workload. Model weights, KV cache, activations, optimizer state, and framework overhead all consume memory. Compare this page with related accelerators rather than assuming that a higher core count alone guarantees a better training or inference result.
Top GPUs for Training and Inference
| Category | Rank 1 | Rank 2 | Rank 3 |
|---|---|---|---|
| Best for Training | NVIDIA H200 | NVIDIA H100 | NVIDIA B200 |
| Best for Inference | NVIDIA A40 | NVIDIA A100 | NVIDIA A10 |
Compare GPU specifications and cloud instances to find the best GPU for your workload.