Cyfuture Cloud Alternative
The Cyfuture Cloud alternative
built around GPU - not bolted on.
GPU-native control plane. Fractional GPU from 12.5%. One-click vLLM, Unsloth, ComfyUI templates. Developer SDK and CLI. Per-minute billing - plus a licensable platform.
Why ML teams pick PodStack over Cyfuture
Cyfuture is a generalist cloud with GPU added on. PodStack is built ground-up for GPU.
12.5%-100% of an A100 or H100. Stop overpaying for inference workloads.
vLLM, Unsloth, ComfyUI, PyTorch - one-click launch, BYO Docker also supported.
Run the same stack inside your own DCs. Enterprise and government only.
PodStack vs Cyfuture Cloud - feature by feature
| Feature | PodStack | Cyfuture Cloud |
|---|---|---|
| Platform stack | Proprietary, GPU-native | Generalist cloud, GPU as add-on |
| Platform license | Available - license + run in your own DC | No - managed only |
| Fractional GPU | 12.5% - 100% via PodVirt | Full GPU only |
| Developer tooling | SDK, CLI, REST API, podstack.yaml | Portal-led |
| ML templates | vLLM, Unsloth, ComfyUI, PyTorch one-click | BYO image |
| Per-minute billing | Yes | Per-hour |
| Egress fees | Zero | Plan-dependent |
| Pricing | Custom - talk to sales | Public rate cards |
Pricing built around your workload
PodStack pricing is customised to your GPU mix, fraction sizes, and committed usage - with per-minute billing and zero egress fees, you only pay for what you actually use. Tell us your workload and get a quote the same day.
Migrating from Cyfuture in under an hour
- Step 1Push your Docker image
docker tag my-llm:latest registry.podstack.ai/<org>/my-llm:latest docker push registry.podstack.ai/<org>/my-llm:latest - Step 2Sync model weights and datasets
aws s3 sync ./weights/ s3://my-bucket/weights/ \ --endpoint-url https://s3.podstack.ai - Step 3Launch a Pod
# podstack.yaml gpu: a100-80gb gpuFraction: 0.5 image: registry.podstack.ai/<org>/my-llm:latestpodstack pod create -f podstack.yaml
Frequently asked questions
Why look for a Cyfuture Cloud alternative?+
Cyfuture Cloud is a generalist cloud that has added GPU instances as part of its broader offering. For teams whose primary workload is ML training, fine-tuning, and inference, a GPU-native platform with fractional GPU, ML templates, and a real SDK/CLI is usually faster to ship on. PodStack is built ground-up around GPU workloads, not bolted on.
Is PodStack built on open-source like OpenStack or Kubernetes?+
No. PodStack is a proprietary, purpose-built platform - our own control plane, scheduler, and virtualisation layer (PodVirt) designed specifically for fractional GPU sharing. This is why we can offer 12.5% fractional GPU allocation and sub-second scaling.
Can we license the PodStack platform to run our own GPU cloud?+
Yes. PodStack is sold both as a managed cloud and as a licensable platform. Enterprises and operators can license the full PodStack stack and deploy it inside their own data centres. Contact sales@podstack.ai for licensing terms.
Does PodStack support fractional GPU?+
Yes. PodStack supports true fractional GPU from 12.5% to 100% of a card via PodVirt. For inference and sub-utilised training, this typically reduces effective cost per hour by 3-5×.
Does PodStack have one-click ML templates?+
Yes. PodStack ships one-click templates for vLLM, Unsloth fine-tuning, ComfyUI, PyTorch, and TensorFlow. You can also bring any Docker image.
What security certifications does PodStack have?+
PodStack runs on operator-owned hardware in ISO 27001 certified data centres, with DPDP compliance covered for teams that need it.
How do I migrate from Cyfuture Cloud to PodStack?+
Three steps: (1) push your Docker image to PodStack's registry, (2) sync model weights and datasets to a PodStack S3-compatible bucket, (3) launch a Pod via the portal or with `podstack pod create -f podstack.yaml`. Most teams migrate in under an hour.
GPU-native. Fractional. Licensable.
Launch a Pod in 60 seconds - or talk to us about licensing.
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