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Yotta Labs

Yotta Labs provides on-demand, elastic GPU compute built for AI at scale. Products include GPU Pods (Compute), Serverless auto-scaling inference, AI Gateway (unified multi-model API for 50+ models across 15+ providers), and cloud-native Model Quantization. Yotta Labs serves 50,000+ developers across 20+ global regions with SOC 2 Type I certified infrastructure.

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# Yotta Labs

> Yotta Labs provides on-demand, elastic GPU compute built for AI at scale. Products include GPU Pods (Compute), Serverless auto-scaling inference, AI Gateway (unified multi-model API for 50+ models across 15+ providers), and cloud-native Model Quantization. Yotta Labs serves 50,000+ developers across 20+ global regions with SOC 2 Type I certified infrastructure.

## Products

- [GPU Compute](https://www.yottalabs.ai/compute.md): On-demand GPU pods and virtual machines including H100, H200, B200, B300, A100, RTX 4090, RTX 5090, RTX A6000, RTX 6000 Ada, and RTX PRO 6000. Per-second billing, no commitments, from $0.38/hr.
- [Serverless](https://www.yottalabs.ai/serverless.md): Auto-scaling GPU inference and training with zero infrastructure management. Best for production inference services, batch workloads, and large-scale training pipelines.
- [AI Gateway](https://www.yottalabs.ai/ai-gateway.md): Single OpenAI-compatible API endpoint (`https://gateway.yottalabs.ai/v1`) for 50+ LLM, image, and video generation models. Intelligent cost/latency/quality routing, automatic fallback, 99.9% uptime SLA.
- [Inference](https://www.yottalabs.ai/inference.md): Multi-silicon inference optimization across NVIDIA, AMD, and AWS Trainium. Kernel-level SGLang integration, NeuronMM matmul kernels, and distributed inference kernels — backed by published research, open-source tools, and production deployments.
- [Quantization](https://www.yottalabs.ai/quantization.md): Cloud-native LLM quantization service supporting INT4 and NVFP4 precision. Cuts inference costs by up to 60% and reduces VRAM usage by up to 75%. No local setup required.
- [Launch Templates](https://www.yottalabs.ai/launch-templates.md): Preconfigured GPU deployment templates (PyTorch 2.9, ComfyUI, Unsloth, SkyRL). Bundles Docker image, CUDA drivers, and framework config for one-click GPU Pod deployment.

## Pricing & Resources

- [Pricing](https://www.yottalabs.ai/pricing.md): GPU and storage pricing. Per-second billing, no commitments. GPU on-demand rates from $0.38/hr (RTX 4090) to $7.64/hr (B300). Storage from $0.036/GB/mo.

## Research

- [Our Research](https://www.yottalabs.ai/our-research.md): Peer-reviewed publications on efficient ML, distributed GPU orchestration, and inference optimization. Papers published at SIGMOD, SC, USENIX ATC, HPCA, ASPLOS, EuroSys, IPDPS, and MICRO.
- [Research Credit Program](https://www.yottalabs.ai/research-credit.md): Academic GPU credit program offering $1,000 in free compute credits and 6 months of discounted usage for approved researchers, faculty, and graduate students.

## Blog Posts

- [Topaz Labs Starlight Precise 2.6 vs Starlight Fast 3: Which Video Upscaler to Use](https://www.yottalabs.ai/post/topaz-labs-starlight-precise-2-6-vs-fast-3-video-upscale-api.md): Topaz Labs’ two Starlight video upscalers are live on the Yotta AI Gateway at the same price. Here is what separates Precise 2.6 from Fast 3, what a clip costs at each resolution, and
…

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