NVIDIA A2 GPU — Datasheet
Cost-efficient entry GPU for light inference, classic CV, and small GenAI pilots. Popular with startups moving from CPU to GPU in India without over-spending.
GPU Datasheets
Concise specs + real-world guidance from the inhosted.ai team to help you pick the right accelerator for India-scale workloads.
NVIDIA L4 GPU — Datasheet
Balanced price/perf for AI video analytics, diffusion, and high-QPS inference. Great for media, e-commerce, and surveillance workloads across Indian metros.
NVIDIA A30 GPU — Datasheet
Mid-range workhorse for mixed training/inference with strong FP16. A favourite for Indian SaaS teams scaling beyond POCs into revenue workloads.
NVIDIA L40S GPU — Datasheet
AI + graphics convergence for diffusion, real-time rendering, and enterprise visualization. Ideal for studios and digital twins with 48 GB GDDR6.
NVIDIA A100 GPU — Datasheet
Proven, versatile accelerator with MIG for multi-tenant fleets. India’s most widely adopted GPU for balanced TCO, training stability, and steady inference.
NVIDIA H100 GPU — Datasheet
Transformer Engine + NVLink for state-of-the-art LLMs, RAG, and agentic workflows. Our India PoP network keeps latencies predictable for production apps.
NVIDIA H200 GPU — Datasheet
HBM3e memory boosts long-context LLMs, vector DB throughput, and streaming inference. Designed for India-scale data and multilingual deployments.
NVIDIA RTX 8000 GPU — Datasheet
Studio-grade ray tracing and AI denoise for VFX and design review. Popular with Indian post-production houses modernising render pipelines.
NVIDIA RTX A6000 GPU — Datasheet
48 GB pro-viz muscle for CAD/BIM, broadcast, and AI-assisted content. Reliable, quiet, and predictable for global design teams operating from India.
NVIDIA RTX 6000 Ada GPU — Datasheet
Ada-generation Tensor + RT cores for GenAI and real-time viz. Loved by Indian automakers and architects building immersive digital twins.
NVIDIA RTX Pro 6000 GPU — Datasheet
Enterprise-class RTX for secure visualization stacks. Backed by inhosted.ai’s ISO/SOC-aligned DCs in India for predictable uptime and support.
Whitepapers
Deep dives authored with inhosted.ai’s field data from Indian enterprises — architectures, tuning, and cost playbooks that cut weeks of trial-and-error.
Designing High-QPS RAG on H100
A practical blueprint for tokenizer-aware batching, KV-cache placement, and vector DB design — benchmarked on India networks to keep tail-latency under control.
Scaling Context: H200 & Long-Sequence LLMs
How HBM3e helps long-context training and instruction-tuning at Indian data scales. Includes ZeRO variants, optimizer sharding, and I/O patterns that actually hold up.
FinOps for A100 Clusters
Instance right-sizing, MIG vs full-GPU trade-offs, preemption strategies, and real TCO patterns from Indian fleets — to keep spend predictable as traffic spikes.
From CPU to GPU: A2 Inference Playbook
A hands-on migration guide for teams moving classic ML and light GenAI from CPU to A2. Tuning tips that fit Indian bandwidth realities and edge deployments.