Free AI Hosting | Free.ai
Host AI models for free. GPU access, API hosting, and cloud deployment.
बंद करें (C)
Free.ai इन्फाइन्फस्ब का इस्तेमाल करें. शून्य सेटअप, शून्य देख सकते हैं. सभी मॉडलों को एपीआई या वेब यूआई के उपयोग के लिए पहले से लोड कर रहे हैं.
उपलब्धडॉकनेवाला स्व-Hod
अपने खुद के हार्डवेयर पर हमारे खुले स्रोत एआई मॉडल चलाएँ. GuPCP समर्थन के साथ डॉकर छवियों, PPERIPEPERIPEPERIPENDIPENDIPE.
स्व- सर्विसनिजी प्रबंधन
हमारे द्वारा प्रबंधित, अपने पसंदीदा बादल क्षेत्र में तैनात. पूरा डेटा पृथक और पसंदीदा सएलए.
छोटे - छोटे रंगस्व-शोषण कमी
हमारे सभी मॉडल खुले हैं (एप्रेत 2. 0 / एमआई). आप इन्हें अपने स्वयं के जीपीपीपी इन पर चला सकते हैं:
# Pull and run a model with Docker
docker pull ghcr.io/free-ai/inference:latest
docker run --gpus all -p 8000:8000 ghcr.io/free-ai/inference:latest \
--model qwen2.5-72b --quantization awqन्यूनतम आवश्यकताएँ
- NVIDia गापिजी के साथ 24GB+ वोथ (RX90, A5000, A100)
- CUD 12. 0+ तथा डॉक करें NIA अतिरिक्त कंटेनर के साथ
- 16GB+ सिस्टम रैम, 100GB+ भंडारण प्रति मॉडल
- 72B पैरामीटर मॉडल के लिए: 80GB वीरैम (ए100) या बहु-जीपी सेटअप
क्यों स्व-धन?
- डाटा गोपनीयता — Your data never leaves your servers
- कोई दर सीमा नहीं — Unlimited inference on your hardware
- कम्पलीशन — Meet data residency requirements
- मनपसंद सूचना — Fine-tune models on your data
- लागत नियंत्रण — Fixed hardware costs, no per-token fees
- एयर- फानितcolor — Runs fully offline
FAQ
Three options: Cloud Hosted (use our infrastructure, zero setup), Docker Self-Hosted (run models on your own GPU hardware), and Managed Private (dedicated GPU servers managed by us in your preferred region).
You need an NVIDIA GPU with 24GB+ VRAM (RTX 4090, A5000, A100), CUDA 12.0+, Docker with NVIDIA Container Toolkit, 16GB+ system RAM, and 100GB+ storage per model. For 72B parameter models, you need 80GB VRAM or a multi-GPU setup.
Yes. Self-hosted deployments run fully offline once the Docker images and model weights are downloaded. This is ideal for air-gapped environments and sensitive data processing.
Pull our Docker image and run it with GPU support. The command is: docker run --gpus all -p 8000:8000 ghcr.io/free-ai/inference:latest --model qwen2.5-72b --quantization awq. The container handles model loading and serves an API endpoint.
All self-hosted models use permissive open-source licenses -- Apache 2.0, MIT, or BSD. You can use them commercially without restrictions. We deliberately exclude models with restrictive licenses like Meta's Llama license.
Managed private hosting gives you dedicated GPU servers in your preferred cloud region, fully managed by our team. We handle setup, patching, model updates, and monitoring. You get full data isolation with an enterprise SLA.
Yes. Since all models are open-source, you can fine-tune them on your own data using standard training frameworks like Hugging Face Transformers. Our Docker images are compatible with popular fine-tuning tools.
Contact our sales team to discuss a trial period. We typically offer a short evaluation period for enterprise prospects to test managed private hosting before committing to a long-term plan.
Cloud hosting uses the standard token-based pricing. Self-hosted is free -- you only pay for your own hardware and electricity. Managed private hosting is priced based on GPU allocation, region, and SLA level.
Yes. You can self-host specific models for high-volume or sensitive workloads while using the Free.ai cloud for everything else. The API format is identical, making it easy to route requests between your infrastructure and ours.
We provide documentation, Docker images, and community support for self-hosted deployments. Managed private hosting includes full technical support, monitoring, and a dedicated account manager.
Cloud hosted is best for teams that want zero maintenance. Self-hosted is ideal for data privacy, compliance, or unlimited usage on your own hardware. Managed private is the best of both worlds -- full data isolation with no operational burden.