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. Same Indian sovereignty — plus a licensable platform.

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Why ML teams pick PodStack over Cyfuture

GPU-native platform

Cyfuture is a generalist cloud with GPU added on. PodStack is built ground-up for GPU.

True fractional GPU

12.5%–100% of an A100 or H100. Stop overpaying for inference workloads.

ML templates out of the box

vLLM, Unsloth, ComfyUI, PyTorch — one-click launch, BYO Docker also supported.

Platform license available

Run the same stack inside your own DCs. Enterprise and government only.

PodStack vs Cyfuture Cloud — feature by feature

FeaturePodStackCyfuture Cloud
Platform stackProprietary, GPU-nativeGeneralist cloud, GPU as add-on
Platform licenseAvailable — license + run in your own DCNo — managed only
Fractional GPU12.5% – 100% via PodVirtFull GPU only
Developer toolingSDK, CLI, REST API, podstack.yamlPortal-led
ML templatesvLLM, Unsloth, ComfyUI, PyTorch one-clickBYO image
Per-second billingYesPer-hour
Data residencyIndia (Bengaluru DCs)India
ComplianceISO 27001, DPDP-readyISO 27001

Pricing side-by-side

Cyfuture Cloud GPU prices indicative — published rates vary by SKU and region.

GPUPodStackCyfuture Cloud
NVIDIA L40S 48GB₹100/hr (incl. taxes)~₹140/hr
NVIDIA A100 40GB₹208/hr~₹260/hr
NVIDIA A100 80GB₹292/hr~₹340/hr
NVIDIA H100 80GB₹333/hr~₹410/hr

Migrating from Cyfuture in under an hour

  1. Step 1
    Push your Docker image
    docker tag my-llm:latest registry.podstack.ai/<org>/my-llm:latest
    docker push registry.podstack.ai/<org>/my-llm:latest
  2. Step 2
    Sync model weights and datasets
    aws s3 sync ./weights/ s3://my-bucket/weights/ \
      --endpoint-url https://s3.podstack.ai
  3. Step 3
    Launch a Pod
    # podstack.yaml
    gpu: a100-80gb
    gpuFraction: 0.5
    image: registry.podstack.ai/<org>/my-llm:latest
    podstack pod create -f podstack.yaml

Frequently asked questions

Why look for a Cyfuture Cloud alternative?+

Cyfuture Cloud is a generalist Indian 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, government departments, 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 $/hr 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.

Is PodStack sovereign and DPDP-compliant?+

Yes. PodStack is operated from Indian data centres, ISO 27001 certified, and DPDP-compliant. Government-empanelment ready for defence and regulated workloads.

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. Sovereign. Licensable.

Launch a Pod in 60 seconds — or talk to us about licensing.

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