OpenRouter

Open-weight inference, fine-tuning, and GPU-cloud platform

Together AI is a cloud platform for running, fine-tuning, batching, and training open-weight AI models. It supports serverless inference, dedicated endpoints, LoRA and full fine-tuning, GPU clusters, code-execution sandboxes, and async batch jobs up to 30B tokens per model. Current docs list fast-moving families such as Qwen, Kimi, GLM, GPT-OSS, DeepSeek, Llama, MiniMax, and Mistral.

Production-grade inference with serverless and on-demand GPUs

High-performance inference platform serving open-source and custom AI models at global scale, processing 13+ trillion tokens daily at ~180K requests per second. Fireworks AI delivers 1,000+ tokens per second on large models through quantization-aware tuning and adaptive speculation, with serverless, fine-tuning, and dedicated GPU options across text, image, and audio modalities.

Managed foundation models on AWS

Fully managed AWS service providing enterprise access to 100+ foundation models from Anthropic, Meta, Mistral, Cohere, and Amazon's Nova family through a single API. Bedrock includes AgentCore for agent runtime, Knowledge Bases for RAG, Guardrails blocking 88% of harmful content, plus Model Distillation, Prompt Caching, and Intelligent Prompt Routing for cost optimization.

Open-source LLM gateway with built-in optimization and A/B testing

TensorZero is an open-source LLMOps platform in Rust that unifies an LLM gateway, observability, prompt optimization, and A/B experimentation in a single binary. It routes requests across providers with sub-millisecond P99 latency at 10K+ QPS while capturing structured data for continuous improvement. Supports dynamic in-context learning, fine-tuning workflows, and production feedback loops. Backed by $7.3M seed funding, 11K+ GitHub stars.

Smart LLM router that cuts inference costs up to 70%

Manifest is an open-source smart model router that intelligently routes LLM requests to the cheapest capable model, reducing inference costs by up to 70% without sacrificing output quality. It uses a 23-dimension scoring algorithm to evaluate 300+ models across providers including OpenAI, Anthropic, Google, and DeepSeek, with automatic fallbacks and budget controls. Manifest can be deployed as a cloud service, local plugin, or self-hosted Docker container with transparent routing logic.