Local Webgpu Llm Inference

local.ai runs language models locally without GPUs. Its Rust backend keeps the binary under 10 MB and performs CPU inference with GGML quantization. A single‑click interface streams responses to a UI, while a model manager tracks, verifies, and resumes downloads.

LM Studio runs open‑source large language models locally on Mac (M‑series), Windows, and Linux, enabling private, offline inference. It offers command‑line and headless deployment, server‑side API, SDKs, a model hub, and LM Link for remote model access.

LLMWare AI installs a lightweight client on PCs, providing instant access to 100+ AI models optimized for Intel and Qualcomm hardware. It supports RAG, auto‑tunes weights, runs locally without Wi‑Fi, and offers an admin console for monitoring, scaling, and audit logs.

General Compute is an OpenAI-compatible inference API using custom ASIC accelerators to deliver high throughput (e.g., 950 tokens/sec) and dramatically lower power consumption (≈17 kW vs. 120 kW per rack), enabling developers to switch providers by simply changing the base URL and API key. It suppor

Wafer AI is a serverless inference platform that lets you run open-source LLMs in production with OpenAI-compatible APIs. It offers dedicated endpoints with optimized performance, long-context support, and caching to reduce costs for coding, reasoning, and agent workloads.

fal.ai offers a unified API for generating images, videos, audio, and 3D models from a library of over 1,000 production‑ready assets. It provides serverless GPU inference, private deployment options, NVIDIA‑cluster fine‑tuning, SOC 2 compliance, and enterprise‑grade support.

Inception Labs' diffusion-based large language models (dLLMs) offer faster, more efficient, and cost-effective text generation than traditional autoregressive models. With built-in error correction, multimodal support, and structured output control, they excel in function calling and complex data ge

Ministral WebGPU optimizes machine learning applications by utilizing enhanced graphics processing power. It supports various app files, enabling efficient collaboration and development, with an intuitive interface suitable for both beginners and experienced practitioners.

LiteLLM is an open‑source gateway that unifies access to 100+ LLMs through a single OpenAI‑compatible API, enabling provider fallback, cost tracking, tag‑based budgeting, guardrails, observability, and on‑prem or cloud deployment with a lightweight SDK.

Foundry Local runs AI models on-device using ONNX Runtime (CPU/GPU/NPU) to keep data local, offering an OpenAI-compatible API, Python/JS/C#/Rust SDKs, a model hub, and CLI tools for edge and enterprise deployments.

GPU Mart provides dedicated GPU server hosting and VPS solutions optimized for demanding AI workloads, including LLM inference, image generation, and 3D rendering, offering guaranteed resources and transparent pricing.

Runpod supplies on‑demand GPUs in 31 regions, offering single‑node pods, multi‑node clusters, and serverless workloads. It delivers low‑latency inference, efficient fine‑tuning, instant scaling, S3‑compatible storage, real‑time logs, and sub‑200 ms cold starts.

canirun.ai is a searchable database mapping AI models to compatible hardware, listing CPUs/GPUs (including Apple M-series and NVIDIA cards), model requirements, VRAM/memory needs, filters and comparisons to plan local inference, fine-tuning, or deployment.

GPUX is a serverless inference platform that delivers 1‑second cold starts and GPU‑accelerated execution for models like Stable Diffusion XL, ESRGAN, and Whisper. It supports P2P and read‑write volume access for rapid, scalable deployment on NVIDIA RTX 4090 GPUs.

Browser‑based AI upscaler uses WebGPU and open‑source algorithms like Anime4K and RealESRGAN to enlarge video and image resolution. It processes each frame client‑side, preserving privacy, with drag‑and‑drop, side‑by‑side comparison, and selectable output sizes.

Lightning AI is a PyTorch Lightning‑based cloud platform for training, deploying, and serving models at scale. It offers GPU workspaces, managed clusters, fractional pay‑as‑you‑go GPU capacity, inference APIs, serverless deployment, security, and integration with LitServe, LitGPT, and LLMs.

EmpirioLabs AI is a platform for hosting, deploying, and scaling open-source and proprietary AI models via API or web playground. It supports multimodal, long-context models with optimized endpoints, creative templates, and high-throughput rate limits for production workloads.

ModelsLab offers API‑based generative AI for image, video, audio, and language tasks, including editing, generation, and voice synthesis. It supports GPU server deployment, custom workflows, fine‑tuning, and LoRA adaptation for creators and developers.

Unsloth Studio is a no-code web UI enabling local training, running, and exporting of open AI models like Qwen3.5 and NVIDIA Nemotron 3, simplifying experimentation for users without extensive technical expertise.

Vast.ai supplies on‑demand GPU instances, including NVIDIA RTX, H100, and Blackwell models, deployable in seconds. Developers can programmatically provision resources via CLI, SDK or API, and scale workloads with autoscaling, serverless inference, and dedicated InfiniBand clusters.

Atomic Chat is a fully offline, on-device AI chat app for macOS, Windows, Linux, iOS, and Android that runs 1,000+ LLMs locally with built-in agent support, persistent memory, and privacy-first design. It features TurboQuant optimizations for up to 8x faster attention and lower memory use, with one-

Inferless is a serverless platform for deploying machine learning models seamlessly. It offers automatic load balancing, custom runtime environments, and automated CI/CD workflows, minimizing infrastructure management while scaling efficiently from single to millions of requests.

Groq is an inference platform that uses custom LPU silicon for low‑latency, high‑throughput AI workloads. It supports large language and multimodal models via an OpenAI‑compatible API, with modular deployment and predictable performance for NLP, vision, and recommendation tasks.

SiliconFlow is an AI infrastructure platform enabling high-speed inference for LLMs and multimodal applications, supporting serverless, reserved, and private-cloud deployments. It offers low-latency processing, elastic compute, and built-in monitoring for scalable, cost-efficient AI workloads.

Llama.cpp is an open-source tool for efficient inference of large language models. Run open source LLM models locally everywhere.

Cerebras provides a wafer-scale AI accelerator and software stack that enables single-node training of very large LLMs, high-throughput low-latency inference (GLM-4.6 at 1,000 TPS), PyTorch SDK, deployment options, and MLOps tooling.

Float16.cloud delivers AI‑as‑a‑Service, platform, and infrastructure through instant, ready‑to‑use models accessed via a dashboard or API. It offers dedicated GPUs, 1‑second cold starts, Jupyter notebooks, credit‑based quotas, and dynamic scheduling for training, inference, and batch processing.

little-coder is a Pi-based coding agent for running 5–25 GB local LLMs via llama.cpp or Ollama, offering Python/Node CLIs and TypeScript extensions, reproducible benchmarks, build/serve guides, and tools for local code generation, on-device development, and evaluation.

Scale your AI projects affordably with Salad's GPU Cloud service. Access over 10,000 GPUs for generative AI tasks like generating 9 million+ images in just 24 hours at a starting price of $0.02/hr. Salad offers fully managed services like the Salad Container Engine, Salad Gateway Service, and Virtua

ClearML AI Infrastructure Platform unifies GPU management, model development, and generative‑AI deployment across on‑prem, cloud, and hybrid setups, offering secure multi‑tenant provisioning, priority scheduling, fractional GPU allocation, integrated IDE, CI/CD, and streamlined workflows for data sc

UBIAI fine‑tunes LLMs with classifiers, retrievers, and reasoning. It automates PDF/DOCX labeling, synthetic data, and quality filtering; offers 15‑minute prompt‑level tuning or 2‑4 hour weight training; exports to GGUF, safetensors, or Hugging Face for API or custom deployment.

LLM Arena enables users to compare multiple large language models side-by-side, analyzing features like accuracy and capabilities. It supports up to 10 models, facilitating informed decision-making for researchers and developers in selecting the right LLM for their needs.

exllama is a memory-efficient tool for executing Hugging Face transformers with the LLaMA models using quantized weights, enabling high-performance NLP tasks on modern GPUs while minimizing memory usage and supporting various hardware configurations.

Open-source desktop app for running local LLMs on Windows/macOS/Linux, supporting text and multimodal inputs, file attachments, multiple model backends with hot-switching, chat/instruction modes, prompt-engineering tools, API/tool-calling, extensibility, and conversation branching.

RunningHub is a cloud IDE for ComfyUI workflows, enabling in‑browser design, editing, and GPU‑accelerated execution. It offers pre‑installed nodes, access to major diffusion and video models, training tools, API integration, and real‑time collaboration.

Vocareum delivers labs with IDEs, notebooks, and GPU/CPU clusters in isolated containers or accounts. It offers tutoring, code grading, and a unified gateway to AWS, Azure, GCP, Databricks, and foundation models. LMS integration and SOC 2 compliance enable scalable training.

Trooper.AI provides private EU-hosted bare-metal GPU servers for model training, fine-tuning, and inference, with one-click AI environment templates, full root SSH and NVMe storage, tested CUDA on Ubuntu 22.04, scalable hardware and pause/upgrade controls.

Llama is a local AI tool that enables users to create customizable and efficient language models without relying on cloud-based platforms, available for download on MacOS, Windows, and Linux.

ComfyOnline lets users run ComfyUI workflows online, automatically installing dependencies and models. It auto‑generates APIs for image, video, audio, and text generation, supports advanced services, LLMs, custom nodes, and scales with traffic.

VibeClaw.dev is a browser-based OpenClaw runtime for running AI coding agents in sandboxed, in-browser Node.js containers. It features a complete virtual filesystem, multi-agent orchestration, and flexible model support from local WebGPU LLMs to cloud APIs, all exportable for private, reproducible w

The Full Stack offers a complete AI lifecycle curriculum, covering prompt engineering, LLMOps, deep learning, GPU selection, model monitoring, ethics, and MLOps. It trains developers, product managers, and researchers to design, build, and deploy AI applications.

Awan LLM offers unlimited token generation with Meta Llama 3.1 8B and 70B models, no censorship or caps, supporting persistent AI assistance, autonomous agents, roleplay, data processing, and code completion, hosted on owned GPUs for continuous use.

Massed Compute delivers on‑demand GPU/CPU resources via API and desktop interface, supporting NVIDIA A100/H100/L40/A6000 GPUs and custom clusters. Bare‑metal servers provide direct physical access, while an Inventory API streamlines instance management in a Tier III data‑center with expert support.

Fireworks AI is a cloud‑hosted inference platform supporting code, conversational, agentic, and search workflows across text, vision, audio, and image modalities. It delivers scalable, low‑latency inference with secure RAG and serverless GPU options.

Cloud GPU rental platform offering on-demand VMs and bare-metal servers with A100/H100/RTX4090 and other GPUs, configurable vRAM/vCPU, persistent volumes, spot instances, and API-driven provisioning for training, inference, rendering, and HPC workloads.

Fluidstack offers dedicated GPU clusters on bare‑metal Atlas OS, delivering rapid provisioning and full resource control. Continuous monitoring via Lighthouse ensures isolated, compliant infrastructure (GDPR, SOC 2, ISO 27001) with a 15‑minute support SLA for AI labs, enterprises, and government use

Thunder Compute is a cloud-based platform that provides easy access to network-attached GPUs for AI and machine learning projects. It enables swift model deployment, efficient scaling, and minimizes idle GPU costs through streamlined infrastructure management.

MLflow is an open‑source AI engineering platform that tracks LLM and agent execution, monitors performance, cost, and safety, manages prompts, and supports experiment tracking, tuning, and deployment across multiple clouds or on‑premises.

LLM Pulse tracks brand visibility and search presence across LLMs (ChatGPT, Perplexity, Google AI), offering prompt tracking and suggestions, citation analysis, visibility scoring and competitor benchmarking, sentiment and response inspection, plus API and reporting exports.

Open‑Chat is a self‑hostable, decentralized chat platform that supports both proprietary and open‑source AI models. It provides a full chat API, runs LLMs on local GPUs, lowers latency, enhances privacy, and deploys easily on personal or cloud servers.