Hostnot GPU vs Wirkung
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Hostnot GPU compared with Wirkung
| Detail |
Hostnot GPU |
Wirkung |
| What it does | On-demand GPU cloud compute for AI, LLM inference and development
| Everything has an algorithm
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| Stage | Not given
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| Founded | Not given
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| Based in | AE
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| Pricing model | Paid
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| Pricing | Not given
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| Key features | - Live GPU marketplace with real-time capacity and pricing
- Wallet-first authorization with fund reservation before compute request
- SSH-ready GPU instances with public key access
- Serverless inference with supported model catalog and API
- Deploy templates for repeatable environments
- Scoped developer API for capacity, usage, and inference automation
- Support for open-source AI models on GPU instances
- Multiple compute regions with dynamic availability
- 39 available GPU offerings with 7 GPU types
- 50 serverless models in model catalog
| - Constant-state attention: models serve any context length from the same memory per request
- HCGM: models run from disk storage instead of memory
- M-Rail: context processed by a model can be reused instantly in future requests
- CPUDA/sGPU: run unmodified CUDA programs on CPUs with bit-identical results
- Organ grafting: transfer capabilities between models without training
- Personal instruction set (ISA) compiled on device from phone signals
- Population ISA: compile laws from many people without personal records
- Digital twins of customers, fleets, cities or markets
- Results identical across all machines and architectures
- Computation cost follows novelty not data size
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| What makes it different | - Server-side pricing calculation with transparent customer rates shown before authorization
- Wallet-first deployment model prevents surprise charges
- Clear operational state and control without opaque claims or sales processes
- Flexible deployment options with persistent instances or serverless workflows
- Developer-first API with scoped credentials and idempotency keys
| - Constant memory cost regardless of context length or data size
- Exact reuse: every computed result is kept and reused instantly
- Portable execution with bit-identical results across all hardware
- Models run from storage without retraining or fitting in memory
- Privacy-preserving: raw data never leaves the device
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| Community votes | 0 | 0 |
| DR (Domain Rating by Ahrefs) | 16 ▲ +1 (up) since last check | Not checked yet ● no change since last check |
| Trust Flow (Majestic) | 8 | 0 |
| Citation Flow (Majestic) | 26 | 0 |
| Referring domains (Majestic) | 36 | 0 |
3 details filled in for both companies.
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