Hardware-isolate,

Hardware GPU Slicing

The Fractional GPU Cloud

Slice full physical GPUs into dedicated, hardware-isolated compute instances. Pay up to 8x less for your AI inference and fine-tuning workloads with zero noisy neighbors.

MIG Partition Configurator

Select Your Hardware Slice

Choose a dedicated hardware profile scaled exactly to your model VRAM footprint.

Selected Architecture
2G.20GB SliceRecommended
Cost Savings
71% vs Full H100
NVIDIA H100 Physical VRAM (80GB Total)20 GB Allocated
Dedicated VRAM
20 GB HBM3
CUDA Compute
29,184 Cores
HBM3 Bandwidth
850 GB/s
Optimized Target Workload:13B - 14B Models (Mistral NeMo 12B, Qwen 2.5 14B, DeepSeek 14B)
On-Demand Rate
$0.80/ hour
  • Zero setup fees or minimum commit
  • NVIDIA MIG Hardware Memory Isolation
  • Sub-3 second container boot time
Deploy 2G.20GB Slice Now
Hardware Isolation

True physical partitioning, not software emulation

Every MIG slice operates as an independent GPU instance with dedicated crossbar interconnects and execution engines.

Hardware Partitioning

Dedicated Memory & L2 Cache

Each slice controls dedicated physical HBM3 memory controllers and L2 cache lines. Neighbor workloads can never observe or throttle your VRAM bandwidth.

Native Acceleration

NVIDIA MIG & AMD Architecture

Built directly on NVIDIA Multi-Instance GPU (MIG) and AMD hardware partitioning protocols for deterministic quality-of-service (QoS).

Micro Billing

Up to 8x Cost Savings

Never rent an entire 80GB card for small 7B or 14B model inference. Rent a 10GB slice for $0.40/hr with identical execution latency.

Partition Matrix

Available H100 Slices & Rates

MIG ProfileDedicated VRAMCUDA CoresTarget AI ModelsRateStatus
1g.10gb10 GB HBM314,592 Cores7B Models (Llama 3, Qwen 2.5, DeepSeek 7B)$0.40/hrInstant Access
2g.20gb20 GB HBM329,184 Cores13B - 14B Models (Mistral NeMo 12B)$0.80/hrMost Popular
3g.40gb40 GB HBM343,776 Cores32B - 34B Models (DeepSeek R1 Slices)$1.60/hrAvailable
7g.80gb (Full)80 GB HBM3114,688 Cores70B+ Models & Multi-GPU Clusters$2.80/hrDedicated