Instructions to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Use Docker

docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

LM Studio
Jan

vLLM

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Ollama
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Ollama:
```
ollama run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
```
Unsloth Desktop

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Docker Model Runner:
```
docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
```

Lemonade

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Run and chat with the model

lemonade run user.Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF-BF16

List all available models

lemonade list

Hermes Agent

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF

File size: 1,777 Bytes

ae48755

Swift-Qwen3.8-Flash-Next
Copyright 2026 UkisAI

UkisAI's contribution (the "Swift Contribution") is licensed under the
Swift Open License v1.0. See LICENSE.

This model is a derivative work of Qwen3.8-Flash-Next
  https://huggingface.co/Qwen/Qwen3.8-Flash-Next
  Copyright (c) 2026 Qwen
  Licensed under the Qwen Community License 1.0. See LICENSE-QWEN.

Changes made by UkisAI:
  - model-*.safetensors: model weights were modified by UkisAI through fine-tuning.
  - tokenizer.json, tokenizer_config.json: re-serialized from UkisAI's training
    base. Vocabulary and merges are unchanged; the file format, some metadata
    fields and the pre-tokenizer pattern differ from the Base Model files.
  - README.md: replaced. LICENSE (Swift Open License v1.0), NOTICE,
    benchmarks/ and ukisai-banner.png added.
  - The Base Model's license text was moved from LICENSE to LICENSE-QWEN.
  - All other files (config.json, generation_config.json, chat_template.jinja,
    model.safetensors.index.json, vocab.json, merges.txt,
    preprocessor_config.json, video_preprocessor_config.json) are unmodified
    from Qwen3.8-Flash-Next and remain under the Qwen Community License 1.0.

Changes made by Baekpica:
  - Main GGUF files: converted Swift1.5 BF16 weights using the published
    Qwen MQ-Q5 SSD-PLE tensor recipe; no pruning or imatrix calibration.
  - PLE-FP8/: official Qwen FP8 PLE copied after full byte-exact verification
    that Swift BF16 PLE is unchanged from the Qwen BF16 source.
  - reproduction/: conversion and verification tools adapted for Swift.
  - README.md and artifact manifests: added conversion and provenance records.

This is an independent conversion, not an official UkisAI or Qwen release.
The ds4 quantizer sources are MIT licensed; see ds4/LICENSE.