Free AI Hosting
Host AI models for free. GPU access, API hosting, and cloud deployment.
વાદળ યજમાન
Free.ai ઇન્ફ્રાસ્ટ્રક્ચર વાપરો. શૂન્ય સ્થાપન, શૂન્ય જાળવણી. બધા મોડેલો પહેલાથી જ લોડ થયેલ છે અને API અથવા વેબ UI મારફતે વાપરવા માટે તૈયાર છે.
હવે ઉપલબ્ધDocker સ્વયં-હોસ્ટ થયેલ
તમારા પોતાના હાર્ડવેરમાં અમારા ઓપન-સોર્સ AI મોડેલો ચલાવો. GPU આધાર સાથે Docker ઇમેજો, અનુમાન માટે શ્રેષ્ઠ.
સ્વયં સેવાસંચાલિત ખાનગી
અમારા દ્વારા સંચાલિત સમર્પિત GPU સર્વર, તમારા પસંદગીના વાદળ વિસ્તારમાં સ્થાપિત. સંપૂર્ણ માહિતી અલગ પાડવું અને વૈવિધ્યપૂર્ણ SLA.
એન્ટરપ્રાઇઝસ્વયં-હોસ્ટ થયેલ વિસ્તરણ
અમારા બધા મોડેલો ઓપન-સોર્સ છે (Apache 2.0 / MIT). તમે તેમને તમારા પોતાના GPU ઇન્ફ્રાસ્ટ્રક્ચર પર ચલાવી શકો છો:
# 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 awqન્યૂનતમ જરૂરિયાતો
- NVIDIA GPU 24GB+ VRAM સાથે (RTX 4090, A5000, A100)
- CUDA 12.0+ અને NVIDIA કન્ટેનર ટુલકિટ સાથે ડોકર
- 16GB+ સિસ્ટમ RAM, 100GB+ સંગ્રહ મોડેલ પ્રતિ
- 72B પરિમાણ મોડેલો માટે: 80GB VRAM (A100) અથવા મલ્ટી-GPU સુયોજન
શા માટે Self-Host?
- માહિતી ખાનગી — Your data never leaves your servers
- દર મર્યાદા નથી — Unlimited inference on your hardware
- અનુરૂપતા — Meet data residency requirements
- વૈવિધ્યીકરણ — Fine-tune models on your data
- ખર્ચ નિયંત્રણ — Fixed hardware costs, no per-token fees
- એર-ગેપ થયેલ — Runs fully offline
વારંવાર પૂછાતા પ્રશ્નો
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.