Tools
LocalAI vs vLLM
LocalAI or vLLM? Their plans monthly and yearly, the capabilities their makers state, security and latest updates, side by side — read from the makers' own pages.
In short
- Both: Choice of models, Self-hosted, API, Runs models for you
- Only LocalAI states: Runs commands, VS Code, Command line, Builds agents and workflows, Search over your data
LocalAI
LocalAI runs AI models on your own hardware through an OpenAI-compatible local server and web interface.
Plans
Not read from the maker’s page yet.
Prices checked 2026-09-25 on the maker’s page.
Capabilities
- Runs commands — “It runs shell commands behind an approval gate you control, delegates to sub-agents, and loads MCP servers, plugins and skills.” source
- VS Code — “Install on openSUSE and drive it from VS Code” source
- Command line — “Run local-ai chat and you are talking to an agent that already knows where your models are.” source
- Choice of models — “Every tier of every model we quantize, ranked against the hardware you actually have and installed with one click.” source
- Self-hosted — “keep your data on your hardware, and scale to a room full of GPUs when you need more capacity.” source
- API — “One binary with an OpenAI-compatible API in front of it.” source
- Runs models for you — “Point an existing client at it and the calls keep working, except now the model is on your machine.” source
- Builds agents and workflows — “Run local-ai chat and you are talking to an agent that already knows where your models are.” source
- Search over your data — “Agents, MCP, skills, RAG, interactive tools” source
Latest updates
- v4.10.0 (v4.10.0)
Added a fleet operations dashboard, credentials.yaml authentication, and CLI end-to-end latency and throughput benchmarking.
- v4.9.0 (v4.9.0)
Authentication now defaults to deny; chat supports context compression, canonical model/backend pages, and video serving in vllm-cpp.
- v4.8.0 (v4.8.0)
Added the vllm-cpp backend, 3D generation, a multi-family audio.cpp engine, hardware-matched gallery builds, and distributed-mode fixes.
vLLM
Open-source engine for serving large language models with batching, caching, quantization, and distributed inference.
Plans
Free
Free
- Unlimited public/private repositories
- Dependabot security and version updates
- 2,000 CI/CD minutes/month
- 500MB of Packages storage
- Issues & Projects
- Community support
Team
- $4 USD per user/month
- Access to GitHub Codespaces
- Repository rules
- Multiple reviewers in pull requests
- Draft pull requests
- Code owners
- 3,000 CI/CD minutes/month
Enterprise
- Starting at $21 USD per user/month
- Data residency
- Enterprise Managed Users
- User provisioning through SCIM
- Enterprise Account to centrally manage multiple organizations
- Environment protection rules
- Audit Log API
Prices checked 2026-09-25 on the maker’s page.
Capabilities
- Choice of models — “vLLM seamlessly supports 200+ model architectures on Hugging Face, including:” source
- Self-hosted — “A high-throughput and memory-efficient inference and serving engine for LLMs” source
- API — “OpenAI-compatible API server, plus Anthropic Messages API and gRPC support” source
- Runs models for you — “A high-throughput and memory-efficient inference and serving engine for LLMs” source
Latest updates
- v0.30.0 (v0.30.0)
Added support for DeepSeek-V4.1-Flash, DeepSeek-V4-Flash-Vision-Exp, GLM-5.3-Flash, K2-Horizon, and other models.
- v0.30.0rc2 (v0.30.0rc2)
Fixed NIXL receive reports for notification-only requests.
- v0.30.0rc1: [Bugfix] Isolate supplemental FlashInfer BF16 autotuning (#57285) (v0.30.0rc1)
Isolated supplemental FlashInfer BF16 autotuning.