Jinfer
Jinfer is an open, modular AI stack for the JVM from Quixotic AI: a Java-native inference engine and related components providing chat, vision, embeddings, and text-to-speech on the JVM with Spring AI and LangChain4j integrations.
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Best for: Audio
What it does
Audio software for decision-makers comparing workflow fit and alternatives.
Best fit
Audio
Pricing snapshot
Pricing available on request
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Jinfer
Jinfer is the Java-native AI inference engine in Quixotic AI's modular stack, built to run end-to-end on the JVM without external sidecars or glue code. It provides chat, vision, embeddings and text-to-speech capabilities and integrates with Spring AI and LangChain4j. The project includes supporting components (jam for quantized matrix multiplications, Tok'n'Roll tokenizers, gguf and safetensors Java support) and runnable jbang examples that demonstrate LLM inference, TTS, transcription, vision prompts and embeddings. The stack emphasizes local execution and JVM-first design, and can be packaged as a GraalVM native image for small footprint and fast startup.
Run LLMs, vision, embeddings, and text-to-speech on the JVM at native speed. No Python runtime, ONNX bridges, or Docker sidecars.
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Jinfer AI inference engine
A JVM-native inference engine offering chat, vision, embeddings and text-to-speech capabilities with example model classes (e.g., JinferChatModel, JinferSpeechModel).
jam (quantized matrix-multiplication)
Fast quantized matrix-multiplication routines intended to accelerate inference on the JVM.
Tok'n'Roll tokenizers
TikToken-compatible and customizable tokenizers for popular LLM models.
jota (multi-backend tensor engine)
A write-once, accelerate-everywhere tensor API with planned backends for Java, C, CUDA, HIP, Metal, OpenCL, and Mojo (noted as 'in the works').
gguf and safetensors support
Pure Java read/write support for llama.cpp's GGUF and HuggingFace's Safetensors model formats.
GraalVM Native Image
Can ship as a single self-contained binary with millisecond startup and no JVM at runtime.
Jbang runnable examples
Multiple runnable snippets (Chat.java, TextToSpeech.java, Audio.java, Vision.java, Embed.java) showing typical workflows.
Spring AI and LangChain4j integration
Integration points for Spring AI and LangChain4j to use jinfer models within existing Java AI ecosystems.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
On-device and local JVM inference
Run LLM inference locally on the JVM without external services or sidecars, suitable for environments requiring AI sovereignty.
Chat and conversational agents
Create chatbots and conversational interfaces using JinferChatModel and provided examples.
Text-to-speech on the JVM
Generate audio from text using JinferSpeechModel (example: Kokoro TTS producing kokoro.wav).
Audio transcription
Transcribe audio recordings (example demonstrates transcription of an audio file via a model like Gemma 4 E2B).
Vision and multimodal prompts
Send images to models and receive descriptive responses (example uses a windmills image and a vision-capable model).
Embeddings for RAG and similarity search
Generate vector embeddings for retrieval-augmented generation and similarity computations (Embed.java example).
Integrations
Spring AI
Integration examples and dependency usage with Spring AI (org.springframework.ai) for chat prompts and client usage.
LangChain4j
Listed as an integration option for using jinfer within LangChain4j-based workflows.
Jbang
Runnable example snippets are provided using jbang to quickly run and test models and demos.
GraalVM Native Image
Support for shipping a native image binary for deployments without a JVM runtime.
Benefits
Limitations
Frequently Asked Questions
No verified FAQs are available.
Getting Started
- 1 Obtain the jbang examples from the project and use them as runnable templates (examples shown: Chat.java, TextToSpeech.java, Audio.java, Vision.java, Embed.java).
- 2 Add the jinfer BOM and required modules as dependencies (examples use coordinates like com.qxotic:jinfer-bom:0.2.0@pom and modules such as com.qxotic:jinfer-spring-ai).
- 3 Run the jbang scripts (the page shows how to run each example with $ jbang Chat.java, $ jbang TextToSpeech.java, etc.) to validate model inference and workflows.
Support
code / repository
View on GitHub (page displays 'View on GitHub' for source, examples and code).
examples
Runnable jbang examples embedded in the project page serve as usage references and quickstarts.
API
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