Free AI Hosting | Free.ai
Host AI models for free. GPU access, API hosting, and cloud deployment.
ମେଘ ଆଧାରିତ
Free.ai ଭିତ୍ତିଭୂମି ବ୍ୟବହାର କରନ୍ତୁ । ଶୂନ୍ୟ ସେଟଅପ, ଶୂନ୍ୟ ରକ୍ଷଣାବେକ୍ଷଣ । ସମସ୍ତ ନମୁନାଗୁଡ଼ିକ ପୂର୍ବ-ଧାରଣ କରାଯାଇଥାଏ ଏବଂ API କିମ୍ବା ୱେବ UI ମାଧ୍ୟମରେ ବ୍ୟବହାର ପାଇଁ ପ୍ରସ୍ତୁତ ହୋଇଥାଏ ।
ବର୍ତ୍ତମାନ ଉପଲବ୍ଧDocker ସ୍ୱୟଂ-ହୋଷ୍ଟିତ
ଆପଣଙ୍କର ନିଜ ହାର୍ଡୱେରରେ ଆମର ମୁକ୍ତ ଉତ୍ସ AI ନମୂନାକୁ ଚଲାନ୍ତୁ। GPU ସମର୍ଥନ ସହିତ Docker ପ୍ରତିଛବିଗୁଡ଼ିକୁ, ଅନୁମାନ ପାଇଁ ଅନୁକୂଳ କରନ୍ତୁ।
ସ୍ୱୟଂ-ସର୍ଭିସପରିଚାଳିତ ବ୍ୟକ୍ତିଗତ
ଆମ ଦ୍ୱାରା ପରିଚାଳିତ ସମର୍ପିତ GPU ସର୍ଭର, ଆପଣଙ୍କ ପସନ୍ଦର କ୍ଳାଉଡ ଅଂଚଳରେ ବିସ୍ତାରିତ। ସମ୍ପୂର୍ଣ୍ଣ ତଥ୍ୟ ଭିନ୍ନକ୍ଷମ ଏବଂ ଇଚ୍ଛାରୂପୀ SLA।
ଉଦ୍ୟୋଗସ୍ୱୟଂ-ହୋଷ୍ଟିତ ବିସ୍ତାର
ଆମର ସମସ୍ତ ନମୂନାଗୁଡ଼ିକ ମୁକ୍ତ ଉତ୍ସ (Apache 2.0 / MIT)। ଆପଣ ସେମାନଙ୍କୁ ଆପଣଙ୍କର ନିଜ GPU ଭିତ୍ତିଭୂମିରେ ଚଲାଇ ପାରିବେ:
# 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 awqସର୍ବନିମ୍ନ ଆବଶ୍ୟକତା
- NVIDIA GPU 24GB+ VRAM ସହିତ (RTX 4090, A5000, A100)
- CUDA 12.0+ ଏବଂ NVIDIA ଧାରକ ଉପକରଣଗୁଡ଼ିକ ସହିତ Docker
- 16GB+ ତନ୍ତ୍ର RAM, 100GB+ ଭଣ୍ଡାର ପ୍ରତି ମଡେଲ
- 72B ପରିମାପକ ମଡେଲଗୁଡ଼ିକ ପାଇଁ: 80GB VRAM (A100) କିମ୍ବା ବହୁ-GPU ବିନ୍ୟାସ
କାହିଁକି Self-Host?
- ତଥ୍ୟ ଗୋପନୀୟତା — Your data never leaves your servers
- କୌଣସି ହାର ସୀମା ନାହିଁ — Unlimited inference on your hardware
- ଅନୁରୂପତା — Meet data residency requirements
- ଇଚ୍ଛାରୂପଣ — Fine-tune models on your data
- ଖର୍ଚ୍ଚ ନିୟନ୍ତ୍ରଣ — Fixed hardware costs, no per-token fees
- ବାୟୁ-ଗ୍ୟାପ — 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.