Intel Arc Pro B60
0
CUDA Cores
24GB
VRAM
456
GB/s
Technical Specifications
0
CUDA Cores
2400
Base MHz
2400
Boost MHz
24GB GDDR6
192-bit bus
Performance
40
FP32 TFLOPS
80
FP16 TFLOPS
200W
TDP
Cloud Availability
0
Available Instances
$0.00/hr
Starting Price
Detailed Specifications
| Architecture | Alchemist (Unknown) |
| Release Date | 2025-04-01 |
| Launch Price | $599.00 |
| Process | 5nm |
| Transistors | 18.5 Billion |
AI Features
Gen 3
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
About Arc Pro B60 GPU
The Intel Arc Pro B60 was introduced in 2025 on the Alchemist architecture. Its specification combines its vendor-specific compute units with 24GB of GDDR6, which defines both the workloads it can run and the batch sizes it can hold.
Based on its 24GB memory capacity, the Arc Pro B60 is best evaluated for model fine-tuning, production inference, image generation, and multi-GPU development. Always size the model, optimizer state, KV cache, and framework overhead together rather than choosing a GPU from core count alone.
GPUvec does not currently have an active hourly cloud listing for the Arc Pro B60. This is not a zero-dollar offer: it means no comparable provider price is available in the present dataset. Check the provider directory for availability or compare a related GPU with an active listing.
For software planning, the Arc Pro B60 combines 456 GB/s of memory bandwidth, CUDA compute capability the latest, and a 5nm manufacturing process. Confirm the minimum CUDA, PyTorch, TensorFlow, or driver version required by your application before renting or purchasing hardware.
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 Arc Pro B60
Complete Specifications for the Intel Arc Pro B60
The Intel Arc Pro B60 uses the Alchemist architecture and combines vendor-specific compute units with 24GB of GDDR6. GPUvec records 456 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 Intel Arc Pro B60 Cloud Rental Prices per Hour
GPUvec currently has no comparable active hourly listing for this model; this means pricing is unavailable, not free. 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 Intel Arc Pro B60 the Right GPU for Your AI Workload?
Start with the 24GB memory limit, then evaluate 456 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.