The Reviosa Blog
GPU benchmarks, infrastructure deep dives, and product news from the team running the Reviosa fleet across four regions.
Introducing per-second billing for every instance type
Starting today, every Reviosa instance type bills by the second with a 60-second minimum. A nine-minute smoke test on an 8×H100 node now costs $2.75, not $18.32.
Maya Reyes
CEO
Jul 14, 2026
5 min read
From notebook to production: vLLM endpoints on Reviosa
The distance between a working notebook and a production endpoint is smaller than it looks. Launch, serve, monitor, and load-test an OpenAI-compatible vLLM endpoint on Reviosa in an afternoon.
Why VRAM, not FLOPS, limits your batch size
Two H100 numbers matter more than TFLOPS ever will: 80 GB and 3.35 TB/s. A tour of where the bytes actually go in training and inference, and why memory hits the wall first.
On-demand vs reserved: choosing a GPU pricing model
Reserved capacity is meaningfully cheaper per hour, and on-demand is 100% cheaper when idle. The only question that matters is utilization — here's the break-even math.
Fine-tuning Llama 3 70B on a single 8×H100 node
You don't need a cluster to fine-tune a 70B model. A complete LoRA recipe for one 8×H100 node — memory budget, config, throughput, and the $64 bill at the end.
Multi-node training over InfiniBand: a practical NCCL tuning guide
Multi-node throughput is won or lost in NCCL configuration before your training script runs a single step. The baseline-first workflow we use to get 90%+ scaling efficiency on InfiniBand clusters.
Cutting inference costs 60%: quantization, batching, right-sizing
Most inference bills are 2-3× larger than they need to be. A practical walkthrough of quantization, continuous batching, and right-sizing that took a production Llama 3 8B deployment from $3,635 to under $1,300 a month.
H200 vs H100: real-world LLM training benchmarks
We ran identical FSDP fine-tuning jobs on 8×H100 and 8×H200 nodes and measured tokens per second, not marketing slides. Bandwidth buys more than you'd guess at long context — and less than the price delta everywhere else.
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