Best Alternatives to Modal

Anyscale is the managed Ray platform from the original creators of Ray, providing production-scale infrastructure for distributed AI workloads — model training, batch inference, RAG pipelines, agent orchestration, and reinforcement learning — running on any cloud with autoscaling GPU and CPU clusters.

Arcade AI is an MCP runtime for production agents focused on secure tool authorization, hosted MCP servers, and authenticated SaaS actions.

Beam is a developer-first serverless platform purpose-built for AI workloads. The pitch is direct: import a Python function, decorate it, push to Beam, and it runs on a GPU somewhere with the right model weights cached, scales to thousands of concurrent invocations, and shrinks back to zero when traffic stops — with cold starts measured in single-digit seconds rather than the minutes most generic serverless platforms take to load model weights. The team built the platform from the ground up for

AI factory company providing renewable-powered GPU cloud for training and inference at hyperscale.

DeepInfra review 2026: serverless open-source LLM inference, OpenAI-compatible API, per-token pricing, dedicated endpoints, LoRA hosting, pros, cons.

Open-source tool that turns your Macs and workstations into a single distributed local LLM inference cluster.

Open-source simulation platform for general-purpose robotics and embodied AI — massively parallel, photoreal, and Python-native.

GPU cloud infrastructure with VMs built for AI agents — MCP-controlled, per-second billing, H100s and B200s from $1.70/hr.

Open-access AI cloud — GPU clusters and OpenAI-compatible serverless inference with transparent pricing.

Enterprise data product platform with high-performance MCP server for real-time, multi-source data delivery to LLMs and AI agents.

Open-source, embedded multimodal vector database designed to live next to your AI app rather than as a separate service.

From Free

Serverless platform for running and composing MCP servers (called 'servlets') in a portable WebAssembly sandbox, with a marketplace for installing tools into any MCP client.

Unified AI inference platform from Chris Lattner's team — MAX engine, Mojo language, and a kernel-to-cloud stack.

Specialised models for coding agents — Fast Apply edits, WarpGrep search, and Compact context — behind one OpenAI-compatible API.

Serverless Postgres with branching, autoscaling, and pgvector support for AI app retrieval workflows.

From Free

Reinforcement learning platform that turns agent traces into smaller, cheaper, faster fine-tuned models.

Unified API marketplace giving developers a single OpenAI-compatible endpoint and one bill for 300+ models from every major and minor LLM provider.

From Free

One-click launcher for open-source AI apps — install, run and manage local models, image and video tools without the terminal.

Open stack for self-improving agents — decentralized compute marketplace plus RL post-training environments and inference.

Managed Rust-based vector search engine with hybrid retrieval, multitenancy, and a Hybrid Cloud option for self-managed clusters.