Runcrate vs TensorWave: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Runcrate and TensorWave. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Runcrate is a GPU cloud founded in 2024 offering on-demand instances with per-second billing and no minimum commitment — the meter stops the moment you stop the instance. The platform aggregates GPU capacity across eight global regions spanning North America, Europe, and Asia, covering 14 GPU models from RTX A6000 and A100 through H100 and RTX PRO 6000. Full root access via SSH, Docker support, and custom images are included on every instance. An OpenAI-compatible inference API serves open-source models billed per token, and reserved or dedicated capacity is available for teams with monthly volume commitments.
- Per-second billing — no minimum commitment
- OpenAI-compatible inference API
- 14 GPU models including H100 and RTX PRO 6000
- 8 global regions across NA, EU, and Asia
- Full root SSH access with Docker and custom images
- Reserved and dedicated capacity available
- No enterprise SLAs or uptime guarantees
- Smaller provider — limited scale vs hyperscalers
- No managed platform or containers
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TensorWave specializes in AMD Instinct MI300X and MI325X GPU instances — the highest-memory GPU accelerators available in any cloud — offering a compelling NVIDIA alternative for large-model LLM inference and distributed AI training via the ROCm ecosystem. On-demand and reserved billing options are available from US-based data centers, with competitive pricing relative to equivalent NVIDIA H100 configurations. The go-to on-demand GPU cloud for teams exploring AMD ROCm or needing massive VRAM for large-context inference.
- AMD MI300X/MI325X — highest VRAM in any cloud
- NVIDIA alternative via ROCm ecosystem
- Competitive pricing vs equivalent H100 configs
- Large-context inference capability
- AMD ROCm ecosystem less mature than CUDA
- Smaller provider — limited scale vs hyperscalers
- Fewer regions — US-only
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Key differences
Runcrate
GPU cloud with per-second billing and an OpenAI-compatible inference API
TensorWave
AMD MI300X and MI325X GPU cloud — highest-VRAM accelerators for large-model inference