7 Best LlamaDeploy Alternatives in 2026 (Open Source)
LlamaDeploy — Deploy your agentic worfklows to production. vs Ray Serve / BentoML: LlamaIndex-native deployment framework with llamactl CLI — zero-code-change transition from notebook workflows to production multi-service systems
Short answer
- Closest match to LlamaDeploy: BentoML.
- Most actively developed: Ray (1,028 commits in the last 90 days).
- Fastest growing: AgentScope (+1,833 GitHub stars in the last 30 days).
- No commit in 6+ months: Jina-Serve, FastAgency and Eidolon.
These 7 open-source tools do the same job. They are ordered by how closely they match LlamaDeploy, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| LlamaDeploy(original) | 454 | -257 | 2026-09-25 |
| BentoML | 8.9k | +52 | 2026-09-07 |
| Jina-Serve | 21.9k | +2 | 2025-03-24 |
| Ray | 44.0k | +330 | 2026-10-02 |
| Agno | 42.5k | +558 | 2026-10-02 |
| AgentScope | 32.7k | +1,833 | 2026-09-30 |
| FastAgency | 548 | +3 | 2025-12-09 |
| Eidolon | 492 | +1 | 2024-12-19 |
1. BentoML
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
What sets it apart: Unified model serving framework with Bento packaging — turn any model into a production API with automatic Docker, adaptive batching, and multi-model orchestration
Best for: Teams deploying ML/AI models as production APIs; Applications needing dynamic batching and GPU optimization; Multi-model inference pipelines (LLM + embedding + reranker)
2. Jina-Serve
☁️ Build multimodal AI applications with cloud-native stack
What sets it apart: vs FastAPI/Flask: built-in containerization, gRPC-first architecture, dynamic batching, and one-command Kubernetes/cloud deployment specifically designed for ML serving
Best for: Deploying ML models as scalable microservices; LLM inference with streaming and dynamic batching requirements
3. Ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
What sets it apart: vs Spark: Python-native with actor model and ML-specific libraries (Train/Tune/Serve); vs Dask: broader AI/ML ecosystem with RLlib, serving, and managed Anyscale platform
Best for: Scaling ML training and serving across clusters; Distributed hyperparameter tuning; Building scalable AI inference pipelines
4. Agno
Build, run, manage agentic software at scale.
What sets it apart: Production-first agent runtime with built-in session isolation, approval workflows, and scalable FastAPI serving — unlike LangChain which is framework-first
Best for: Production multi-agent systems with session isolation; Enterprise agentic applications needing approval workflows and audit trails
5. AgentScope
Build and run agents you can see, understand and trust.
What sets it apart: Unlike LangGraph (stateful graph orchestration) and CrewAI (role-based crews), AgentScope uniquely combines realtime voice agents, A2A protocol, agentic RL fine-tuning, and Kubernetes-native deployment — designed for the rising capability of agentic LLMs
Best for: Teams building production multi-agent systems with realtime voice and A2A interoperability; Chinese-market developers wanting first-class DashScope/Qwen integration
6. FastAgency
The fastest way to bring multi-agent workflows to production.
What sets it apart: vs raw AutoGen/AG2: production deployment framework with unified interface, built-in testing, and FastAPI/NATS.io adapters for scaling agent workflows
Best for: Teams deploying AG2/AutoGen workflows to production; Projects needing unified console + web interfaces for agent workflows
7. Eidolon
The first AI Agent Server, Eidolon is a pluggable Agent SDK and enterprise ready, deployment server for Agentic applications
What sets it apart: vs LangChain/CrewAI: agents are deployed as HTTP services with built-in server, enabling true microservice agent architectures with dynamic inter-agent tool discovery
Best for: Deploying agents as production HTTP services; Multi-agent systems needing inter-agent communication
FAQ
- What are the best alternatives to LlamaDeploy?
- The closest open-source alternatives to LlamaDeploy are BentoML, Jina-Serve and Ray, followed by Agno, AgentScope and FastAgency. They are ranked by how closely they match what LlamaDeploy does.
- Which LlamaDeploy alternative is the most popular?
- Ray has the most GitHub stars among LlamaDeploy alternatives, with 43,963 stars.
- Which LlamaDeploy alternative is the most actively maintained?
- By recent activity, Ray (1,028 commits in the last 90 days) is the most actively developed alternative.