Alternatives to Zibra Labs

Managed Ray platform for distributed training, multimodal data curation, batch embedding, and post-training on your own GPUs

Parallax is a distributed model serving framework for building your own self-hosted AI cluster across scattered GPUs, Macs, and

Kalavai pools spare GPUs across your laptops, desktops and cloud VMs into one self-hosted AI compute cluster you control.

Run open-weight model inference on Together AI — serverless APIs, batch jobs, and GPU clusters.

Rent per-second GPU pods, autoscaling serverless inference endpoints and multi-node clusters on Runpod's AI developer cloud.

Cerebrium is a serverless GPU platform for real-time AI, with memory and GPU snapshotting that restores CUDA workloads in about 3.38

MAX Engine serves open models through one OpenAI-compatible endpoint across NVIDIA, AMD, Apple silicon, CPUs, and ASICs.

Serverless GPU compute with forkable microVMs and millisecond-billed sandboxes for AI agents.

Lilac turns idle GPU clusters into a white-labeled neocloud with spot H100 leases and serverless inference.

Axelera AI builds European edge inference accelerators — Metis and Europa AIPUs for vision, agentic and GenAI workloads from M.2 modules to

MatrixHub is a self-hosted AI model registry that gives vLLM and SGLang clusters a private Hugging Face replacement.

Mesh LLM splits large open-weight models into layer ranges across your own GPUs and serves them through one OpenAI-compatible endpoint at localhost:9337.

Nscale sells sovereign GPU cloud capacity — reserved compute, inference endpoints, and AI data centers it owns and powers.

Rent GPU instances and per-second GPU sandboxes for AI training, RL rollouts, and agent workloads from $0.35/hr.

Per-second-billed cloud GPUs (H100, A100, A6000, V100) with 1-click Jupyter notebooks, model deployment, and distributed training in beta.

Zettascale builds XPU accelerator chips that cut AI inference and training energy by keeping data close to compute.

Etched builds custom inference silicon and rack-scale frontier inference clusters for trillion-parameter MoE prefill and decode.

Run AI agents across a peer-to-peer mesh of the idle machines you already own

DistriFusion splits SDXL image generation across multiple GPUs for up to 6.1x lower latency at high resolution — no retraining required.

Serverless GPU cloud for production AI — declare Python functions and hardware in one file and pay per second.

Groq delivers fast LLM inference on its own LPU and LPX silicon through an OpenAI-compatible API.

Run and fine-tune image, video, speech and LLM models with one Replicate API call

Run fast, production-grade GPU inference on dedicated GPUs or token-priced Model APIs — with per-minute billing.

Runware is one inference API for 400K+ image, video, audio, LLM and 3D models on a single endpoint.

Serverless AI inference on 100+ open models via an OpenAI-compatible API, billed per token with no GPU overhead.

Cerebras inference cloud: frontier LLMs at up to 750 tokens/sec for real-time agents and voice AI.

Query image, video, speech, music and text generation through one multimodal API key

Fireworks AI runs open-model inference with per-token pricing, model routing, and fine-tuning on one platform.

Rent GPUs on Vast.ai's marketplace — 20,000+ cards, per-second billing, and API-native provisioning agents can drive.

Open-source LLM fine-tuning framework for MoE, LoRA, and GRPO runs on your own GPUs