The Best Triton Inference Server Alternatives in 2026

Jina Serve helps developers build multimodal AI applications with cloud-native tools.

Sonar provides large-scale inference for language models through the project hosted in this repository.

GPUStack manages GPU clusters for serving AI models and provides on demand GPU instances accessible through SSH.

Deploy generative and predictive AI models on Kubernetes with KServe’s distributed inference platform.

FedML supports distributed model training, model serving, and federated learning, with a scheduler for AI jobs across cloud and local clusters.

A Rust inference engine for GGUF models, Shimmy uses WebGPU and supports the OpenAI API.

KServe provides distributed inference for generative and predictive AI models on Kubernetes.

A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

Run image model inference with FLUX through the official repository from Black Forest Labs.

bitsandbytes enables large language models in PyTorch using k-bit quantization.

OpenLLM runs open-source language models as cloud API endpoints compatible with OpenAI clients.

ANEE wraps pretrained transformer inference with an energy budget and early exits inside model execution.

NobodyWho runs language models locally through an inference engine designed for efficient operation across devices.

CTranslate2 provides a C++ and Python inference engine for transformer models.

PrivateGPT provides an API layer for local model based AI applications, including RAG, tools, MCP, and text to SQL.

GraphPipe provides a protocol and software for deploying machine learning models separately from their frameworks.

Rapid-MLX is an open-source LLM inference server for Apple Silicon, built on MLX, compatible with OpenAI and Anthropic APIs, focused on reliable tool calling for coding agents.

MindSpore provides a deep learning framework for training and inference across mobile, edge, and cloud scenarios.

LLMKube runs self hosted LLM inference across heterogeneous GPU fleets using Kubernetes and several model runtimes.

PowerInfer supports serving large language models for local deployment and inference.

BitNet provides an inference framework for one-bit large language models.

Uniform deep learning inference framework for mobile, desktop and server.

This Kimi API guide explains model inference billing, including token charges and cache discounts.