DigitalOcean vs Novita: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for DigitalOcean and Novita. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
DigitalOcean GPU Droplets offer NVIDIA HGX B300, HGX H200, HGX H100, AMD Instinct MI325X, MI350X, MI355X, RTX 6000 Ada, RTX 4000 Ada, and L40S instances with simple per-second billing (5-minute minimum). On-demand, 12-month reserved, and spot options available. Managed Agents Runtime Services (Private Preview). Inference Engine, Model Library, Evaluations. Paperspace (Gradient) integrated.
- HGX B300 (12-mo reserved) — competitive Blackwell pricing
- AMD MI325X and MI300X — high-VRAM AMD options
- Spot GPU Droplets: B300 and MI355X available
- Full cloud ecosystem — Kubernetes, storage, databases, Inference Engine
- Developer-friendly UX and simple per-second billing
- Managed Agents Runtime Services (Private Preview)
- On-demand B300 not yet available (reserved/spot only)
- Less ML-focused than specialist providers like CoreWeave
- GPU catalog narrower than hyperscalers
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Novita has grown into a dual-product platform: a GPU cloud for training and fine-tuning (H100 SXM, A100, RTX 4090) and a high-volume LLM inference API serving 100+ open-source models at some of the lowest per-token rates in the market. In 2025–2026 Novita expanded its model catalog to include Llama 3.1/3.2, Qwen 2.5, DeepSeek V3/R1, and Mistral variants, and introduced batch inference pricing for high-volume workloads at up to 50% discount. The GPU cloud side offers fast provisioning (typically under 3 minutes), pre-built Docker environments for PyTorch and JAX, and persistent storage volumes. A practical choice for cost-conscious teams that want both raw GPU access and a cheap inference API from one provider.
- Among the lowest per-token LLM inference pricing in the market
- Batch inference API at up to 50% discount for high-volume workloads
- 100+ open-source models including Llama 3.2, Qwen 2.5, DeepSeek R1
- Fast GPU provisioning — typically under 3 minutes
- Pre-built PyTorch and JAX environments reduce setup time
- Smaller provider — cluster scale limited vs CoreWeave or Lambda for very large jobs
- Inference API latency trails Fireworks and Cerebras on speed benchmarks
- Less mature enterprise support and SLA options
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Key differences
DigitalOcean
HGX B300, H200, AMD MI325X, Spot B300
Novita
GPU cloud and LLM inference API — H100, A100, and 100+ open-source models