Free AI Hosting | Free.ai
Host AI models for free. GPU access, API hosting, and cloud deployment.
වලාකුළ සත්කාරක
Free.ai යටිතල පහසුකම් භාවිතා කරන්න. ශුන්ය ස්ථාපනය, ශුන්ය නඩත්තු. සියලුම ආකෘති පෙර-පූරණය සහ API හෝ වෙබ් UI හරහා භාවිතා කිරීමට සූදානම්.
දැනට භාවිතයේ ඇතDocker ස්වයං- සත්කාරක
ඔබේම දෘඩාංග මත අපගේ විවෘත මූලාශ්රය AI ආකෘති ධාවනය කරන්න. GPU සහාය සහිත Docker පින්තූර, නිගමනය සඳහා උපරිම කළ හැකිය.
ස්වයංක්රීය සේවාවකළමනාකරණය කළ පුද්ගලික
අප විසින් කළමනාකරණය කරන ලද කැපවූ GPU සේවාදායක, ඔබේ ප් රියතම වලාකුළු කලාපයේ යෙදවුම්. සම්පූර්ණ දත්ත හුදකලා කිරීම සහ අභිරුචි SLA.
එන්ටර්ප්රයිස්ස්වයං- සත්කාරක බෙදාහැරීම
අපගේ සියලු ආකෘති විවෘත මූලාශ්රය වේ (අපාචේ 2.0 / MIT). ඔබ ඔබේම GPU යටිතල පහසුකම් මත ඒවා ධාවනය කළ හැකිය:
# 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 awqඅවම අවශ්යතා
- 24GB + VRAM සහිත එන්වීඩියාවේ ග් රැෆික්ස් ප් රොසෙසරය (RTX 4090, A5000, A100)
- CUDA 12.0+ සහ NVIDIA බහාලුම් මෙවලම් කට්ටලය සමඟ Docker
- 16GB + පද්ධති RAM, ආකෘතියකට 100GB + ගබඩා
- 72B පරාමිතික ආකෘති සඳහා: 80GB VRAM (A100) හෝ බහු-GPU ස්ථාපනය
ඇයි ස්වයං-සත්කාරක?
- දත්ත පෞද්ගලිකත්වය — Your data never leaves your servers
- අනුපාත සීමා නැත — Unlimited inference on your hardware
- අනුකූලතාව — Meet data residency requirements
- රිසිකරණය — Fine-tune models on your data
- පිරිවැය පාලනය — Fixed hardware costs, no per-token fees
- වායු-අවහිර — Runs fully offline
නිතර අසන පැන
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.