模型首次使用会从 Hugging Face 或 URL 下载并缓存,需联网;Godot 不支持 iOS 导出,Windows ARM64 和 Web 导出均不支持;本地服务器为实验性功能,默认监听 127.0.0.1:8888。
nobodywho
nobodywho-oooEUPL-1.2活跃维护跨平台本地大模型推理引擎,支持 Godot、Flutter、Expo 等客户端,让 LLM 在任意设备上高效离线运行。
NobodyWho is an inference engine that lets you run LLMs locally and efficiently on any device.
pip install nobodywho
from nobodywho import Chat
chat = Chat('hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M')
print(chat.ask('What is the capital of Denmark?').completed())桌面端需 64 位 Linux/macOS/Windows(Windows 仅 x86_64),macOS 走 Metal,Linux/Windows 需 Vulkan 驱动否则回退 CPU;空闲内存约为模型文件的 1.5 倍,8GB 起步。iOS 需 iPhone 11 及以上、4GB 内存;Android 需骁龙 855/Adreno 640/6GB 内存以上。显存不足时按可用 VRAM 卸载部分层,其余跑 CPU。
Rust 编写的本地 LLM 推理引擎,让手机、桌面和游戏引擎都能离线跑 GGUF 模型
跨平台本地大模型推理引擎,支持 Godot、Flutter、Expo 等客户端,让 LLM 在任意设备上高效离线运行。
核心能力
- 基于 llama.cpp 推理任意 GGUF 格式聊天模型
- 按函数签名自动生成结构化语法实现类型安全工具调用
- 支持图像音频多模态输入与 Whisper 语音转文字
- 内置 Kokoro 等后端本地合成 WAV 语音并做 VAD
- 提供 Kotlin Swift Flutter React Native Python Godot 绑定
容易踩的坑
- nobodywho-swift-v6.0.0最新正式版2026-10-29 · 2026-10-29 14:59 UTC
6.0.0
Added
-
Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.
-
Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.
In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.
Changed
-
Breaking: Several changes to how tool calls are read from a model's output:
- With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
- A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
- Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given
10received the number10instead of"10". - A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
- A block of tool calls that can't be read is now streamed as text, not only returned in the response.
-
ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.
Fixed
- Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
- A Hugging Face model path without a file name, such as
hf://owner/repo, now fails with an error that shows the expectedhf://owner/repo/filename.ggufformat instead of a raw parser error.
-
- nobodywho-react-native-v6.0.02026-10-29 · 2026-10-29 14:04 UTC
查看更新说明
6.0.0
Added
-
Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.
-
Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.
In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.
Changed
-
Breaking: Several changes to how tool calls are read from a model's output:
- With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
- A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
- Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given
10received the number10instead of"10". - A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
- A block of tool calls that can't be read is now streamed as text, not only returned in the response.
-
ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.
Fixed
- Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
- A Hugging Face model path without a file name, such as
hf://owner/repo, now fails with an error that shows the expectedhf://owner/repo/filename.ggufformat instead of a raw parser error. - Added missing proguard-rules.pro, which should allow enabling R8 on Android.
-
- nobodywho-kotlin-v6.0.02026-10-29 · 2026-10-29 13:16 UTC
查看更新说明
6.0.0
Added
-
Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.
-
Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.
In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.
Changed
-
Breaking: Several changes to how tool calls are read from a model's output:
- With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
- A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
- Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given
10received the number10instead of"10". - A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
- A block of tool calls that can't be read is now streamed as text, not only returned in the response.
-
ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.
Fixed
- Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
- A Hugging Face model path without a file name, such as
hf://owner/repo, now fails with an error that shows the expectedhf://owner/repo/filename.ggufformat instead of a raw parser error.
-
- nobodywho-godot-v13.0.02026-10-29 · 2026-10-29 12:34 UTC
查看更新说明
13.0.0
Added
-
Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.
-
Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.
In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.
Changed
-
Breaking: Several changes to how tool calls are read from a model's output:
- With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
- A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
- Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given
10received the number10instead of"10". - A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
- A block of tool calls that can't be read is now streamed as text, not only returned in the response.
-
ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.
Fixed
- Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
- A Hugging Face model path without a file name, such as
hf://owner/repo, now fails with an error that shows the expectedhf://owner/repo/filename.ggufformat instead of a raw parser error.
-
- nobodywho-python-v5.0.02026-10-29 · 2026-10-29 10:35 UTC
查看更新说明
5.0.0
Added
-
Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.
-
Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.
In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.
Changed
-
Breaking: Several changes to how tool calls are read from a model's output:
- With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
- A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
- Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given
10received the number10instead of"10". - A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
- A block of tool calls that can't be read is now streamed as text, not only returned in the response.
-
ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.
Fixed
- Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
- A Hugging Face model path without a file name, such as
hf://owner/repo, now fails with an error that shows the expectedhf://owner/repo/filename.ggufformat instead of a raw parser error.
-
用户点评
登录用户的真实使用记录,可按版本和硬件筛选还没有人点评。第一个说出真实体验的人最有价值。
Features
- Run locally, offline — no API keys needed or hidden fees
- Run any chat LLM — Gemma, Qwen, Mistral and more
- Fast, type-safe tool calling — automatically generates structured grammars from your function signatures, no schema writing needed
- Multimodal input — provide image and audio information to your LLM
- Text-to-speech — synthesize local WAV audio with Kokoro, Pocket TTS and Supertonic backends
- Speech-to-text — transcribe audio into text with Whisper
- Voice Activity Detection — know when to stop listening and start transcribing with Silero
- Model downloading — load models directly from Hugging Face or any URL
Under the Hood
flowchart TD
FL["Flutter"]:::lang
PY["Python"]:::lang
GO["Godot"]:::lang
K["Kotlin"]:::lang
S["Swift"]:::lang
RN["React Native"]:::lang
FRB["flutter_rust_bridge"]:::glue
P3["PyO3"]:::glue
GX["gdext"]:::glue
U["UniFFI"]:::glue
FL --> FRB
PY --> P3
GO --> GX
K --> U
S --> U
RN --> U
CORE["NobodyWho · Rust<br/>chat · templates · grammars · sampling · context shifting"]:::core
FRB --> CORE
P3 --> CORE
GX --> CORE
U --> CORE
CORE --> LCPP["llama.cpp<br/>text · vision · embeddings · reranking"]:::engine
CORE --> ORT["ONNX Runtime<br/>speech-to-text · text-to-speech · VAD"]:::engine
LCPP --> HW["Hardware<br/>Vulkan · Metal · CUDA · GPU · CPU"]:::hw
ORT --> HW
classDef lang fill:#e8eefc,stroke:#5b7bd5,color:#11204a
classDef glue fill:#f3f0fb,stroke:#8b7bd5,color:#2a1f4a
classDef core fill:#eaf6ee,stroke:#4fa46a,color:#0f3b1f
classDef engine fill:#fdf0e3,stroke:#d58f3b,color:#4a2d0b
classDef hw fill:#f0eeea,stroke:#a09a90,color:#3a352e
- GPU-accelerated inference via Vulkan or Metal — runs fast on any OS
- Compatible with thousands of pre-trained LLMs — use any LLM in the GGUF format
- Powered by the wonderful llama.cpp
You can test our inference engine on iOS, Android, Vision Pro and Apple Watch.
Platforms
| Binding | Install | Runs on | Documentation |
|---|---|---|---|
| Kotlin | Maven Central | Desktop, Android | docs.nobodywho.ooo/kotlin |
| Swift | SPM | macOS, iOS, visionOS, watchOS | docs.nobodywho.ooo/swift |
| React Native / Expo | npm | Desktop, Android, iOS | docs.nobodywho.ooo/js |
| Flutter | pub.dev | Desktop, Android, iOS | docs.nobodywho.ooo/flutter |
| Python | PyPI | Desktop | docs.nobodywho.ooo/python |
| Godot | AssetLib | Desktop, Android | docs.nobodywho.ooo/godot |
Desktop means Linux, macOS and Windows throughout. Three gaps worth knowing before you start:
- Godot has no iOS export. Use the Flutter, React Native or Swift binding on iOS.
- Windows ARM64 is not supported yet.
- There is no web export. It is tracked in issue #111.
⭐ Useful to you? Star the repo, it's the easiest way to say thanks.
Requirements
Inference uses the GPU where available and CPU where not. The real constraint is memory.
Desktop
- Hardware — any 64-bit Linux, macOS or Windows machine. Windows is x86_64 only, there are no ARM64 Windows builds. macOS accelerates through Metal out of the box, Linux and Windows need a GPU driver with Vulkan support and fall back to CPU without one.
- Memory — roughly 1.5× the model file in free RAM, or 2× on a machine that's already busy. 8 GB is a comfortable floor for models up to ~2 GB; 16 GB or more above that.
- Discrete GPUs — NobodyWho offloads as many layers as fit in free VRAM and runs the rest on the CPU, so a model larger than your VRAM still works, just slower. If barely any of it fits, it skips the GPU and stays on CPU. It uses one GPU, the card with the most free memory.
Mobile
- iOS — iPhone 11 or newer, 4 GB RAM or more.
- Android — Snapdragon 855 / Adreno 640 / 6 GB RAM or better.
- Rule of thumb — the device needs roughly twice the model file size in available RAM. iOS reserves around 2 GB, Android 2 to 4 GB depending on vendor. Models under 1 GB run smoothly on any phone.
Models
Any model in the GGUF format works. Pass a hf:owner/repo:QUANT reference, an HTTPS URL, or a local path anywhere a model path is expected; remote models are downloaded and cached on first use. Pass "auto" to fit one to available memory.
Start with Qwen3 0.6B: it is small enough for any phone and good enough to tell whether the integration works.
Quick Start
pip install nobodywho
from nobodywho import Chat
chat = Chat('hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M')
response = chat.ask('What is the capital of Denmark?')
print(response.completed()) # The capital of Denmark is Copenhagen.
// Android
implementation("ai.nobodywho:nobodywho-android:<version>")
// Desktop JVM (Linux, macOS, Windows)
implementation("ai.nobodywho:nobodywho:<version>")
Use the version from the Maven Central badge above.
import ai.nobodywho.Chat
val chat = Chat.fromPath(
modelPath = "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M"
)
val response = chat.ask("What is the capital of Denmark?").completed()
println(response) // The capital of Denmark is Copenhagen.
Add via Swift Package Manager:
https://github.com/nobodywho-ooo/nobodywho-swift.git
import NobodyWho
let chat = try await Chat.fromPath(
modelPath: "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M"
)
let response = try await chat.ask("What is the capital of Denmark?").completed()
print(response) // The capital of Denmark is Copenhagen.
Swift documentation · GitHub · starter app
# React Native
npm install react-native-nobodywho
# Expo
npx expo install react-native-nobodywho
import { Chat } from "react-native-nobodywho";
const chat = await Chat.fromPath({
modelPath: "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M",
});
const msg = await chat.ask("What is the capital of Denmark?").completed();
console.log(msg); // The capital of Denmark is Copenhagen.
RN / Expo documentation · NPM · RN starter app · Expo starter app
flutter pub add nobodywho
import 'package:nobodywho/nobodywho.dart' as nobodywho;
void main() async {
await nobodywho.NobodyWho.init();
final chat = await nobodywho.Chat.fromPath(
modelPath: 'hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M',
);
final msg = await chat.ask('What is the capital of Denmark?').completed();
print(msg); // The capital of Denmark is Copenhagen.
}
Flutter documentation · pub.dev · starter app
Install NobodyWho from inside the editor:
- In Godot 4.5+, open the AssetLib tab and search for NobodyWho.
- Download and import it, making sure Ignore asset root is ticked in the import dialogue.
- Reload the project.
You can also grab a specific version from the releases page and import the zip the same way.
NobodyWho provides an experimental local server that implements the OpenAI Chat Completions API.
Start the server :
uvx --from 'git+https://github.com/nobodywho-ooo/nobodywho.git#subdirectory=nobodywho/server' nobodywho-server --model hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M --name qwen
It listens on http://127.0.0.1:8888 and serves /v1/models and /v1/chat/completions.
See the docs for more info.
Documentation
The documentation has everything you might want to know: https://docs.nobodywho.ooo/
Working with a coding agent? Point it at llms.txt or llms-full.txt, or install the NobodyWho skill so your agent can look up the current APIs and documentation:
npx skills add https://github.com/nobodywho-ooo/nobodywho --skill nobodywho
Community
- Discord & Matrix — ask us anything
- Issues and Discussions — bugs and feature requests
- CONTRIBUTING.md — set up the repo and send a PR
- CHANGELOG.md · SECURITY.md · CODE_OF_CONDUCT.md
⭐ Star the repo if NobodyWho is useful to you. It is how people find us.
License
NobodyWho is licensed under the EUPL-1.2. You may use it in proprietary and commercial projects, free of charge. There has been some confusion about this, so to be precise:
Linking two programs or linking an existing software with your own work does not – at least under European law – produce a derivative or extend the coverage of the linked software licence to your own work. [1]
If you distribute modified versions of the code in this repo, you must open source those changes.
Feel free to make proprietary projects using NobodyWho, but don't make a proprietary fork of NobodyWho.
The Kokoro text-to-speech backend converts text to phonemes with
espeak-ng, which is licensed under GPL-3.0-or-later. It is
compiled in through the kokoro Cargo feature, which is on by default, so the prebuilt packages
include it. If you don't need Kokoro, you can build without it, for example with
cargo build -p nobodywho-godot --release --no-default-features in the nobodywho/ directory.
Supertonic and Pocket TTS work either way.