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# 与 Qwen3 对话
nexa infer ggml-org/Qwen3-1.7B-GGUF

# 多模态：在 CLI 中拖入图片
nexa infer NexaAI/Qwen3-VL-4B-Instruct-GGUF

# NPU（Windows arm64，Snapdragon X Elite）
nexa infer NexaAI/OmniNeural-4B

pip install nexaai

from nexaai import LLM, GenerationConfig, ModelConfig, LlmChatMessage

llm = LLM.from_(model="NexaAI/Qwen3-0.6B-GGUF", config=ModelConfig())

conversation = [
		LlmChatMessage(role="user", content="Hello, tell me a joke")
]
prompt = llm.apply_chat_template(conversation)
for token in llm.generate_stream(prompt, GenerationConfig(max_tokens=100)):
		print(token, end="", flush=True)

<application android:extractNativeLibs="true">

dependencies {
		implementation("ai.nexa:core:0.0.19")
}

// 初始化 SDK
NexaSdk.getInstance().init(this)

// 加载并运行模型
VlmWrapper.builder()
		.vlmCreateInput(VlmCreateInput(
				model_name = "omni-neural",
				model_path = "/data/data/your.app/files/models/OmniNeural-4B/files-1-1.nexa",
				plugin_id = "npu",
				config = ModelConfig()
		))
		.build()
		.onSuccess { vlm ->
				vlm.generateStreamFlow("Hello!", GenerationConfig()).collect { print(it) }
		}

docker pull nexa4ai/nexasdk:latest

export NEXA_TOKEN="your_token_here"
docker run --rm -it --privileged \
	-e NEXA_TOKEN \
	nexa4ai/nexasdk:latest infer NexaAI/Granite-4.0-h-350M-NPU

import NexaSdk

// 示例：语音识别
let asr = try Asr(plugin: .ane)
try await asr.load(from: modelURL)

let result = try await asr.transcribe(options: .init(audioPath: "audio.wav"))
print(result.asrResult.transcript)