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Batch AI processing · Early accessUseful AI results.
Useful AI results.
Without managing the GPU.
IdleGPU is developing managed batch processing that connects suitable GPU capacity with customers who need completed, validated results.
Discuss a validation pilot →Start with a
repeatable workload.
Our proposed first use case is text embeddings: numerical representations that help search systems find related content. Model suitability and useful throughput must be measured for each task.
Product-catalogue processing
Explore semantic search over public product descriptions. Scope, input length and quality requirements determine the benchmark.
Repeatable experiments
Compare outputs on a fixed evaluation dataset before committing to a larger batch or recurring schedule.
What a pilot would involve.
- Define the outcome, model, permitted dataset and acceptable delivery window.
- Run a small controlled benchmark and compare output correctness against a trusted reference.
- Measure full processing cost, transfers, validation and retries before offering a quote.
- Agree acceptance criteria and return the processed output in a documented format.
These are proposed pilot steps. Uploading customer datasets, automated GPU dispatch and live checkout are not available through this page.
Why consider IdleGPU?
The proposed value is a simpler route to completed batch work: suitable capacity, coordinated processing and result validation through one service. Competitive pricing and turnaround are hypotheses to test, not guaranteed savings.
Early trials would use controlled workers with public or synthetic inputs. Distributed processing requires additional controls before confidential information can be accepted. Read our security approach →
Common questions
Do I choose a GPU?
In the proposed managed service, the customer specifies the outcome and constraints; IdleGPU selects compatible validated capacity. The current discovery marketplace supports introductions only.
Can this run an instant chatbot?
Our initial focus is queued batch work with flexible delivery windows. We do not currently offer an always-on real-time inference service.
What does it cost?
Published planning rates are illustrative. A usable pilot quote requires measured workload performance and acceptance criteria.
Can I send private documents?
Initial validation is limited to public or synthetic data. Do not put private documents, credentials or personal data into marketplace listings.
Bring us a real processing requirement.
Tell us the task, approximate volume, deadline, current method and whether the data can be used in a controlled test. Keep the initial description non-sensitive.