How to use from the
Use from the
MLX library
# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("OsaurusAI/VibeThinker-3B-MXFP4")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Osaurus

VibeThinker-3B · MXFP4

Official OsaurusAI MXFP4 microscaling (4.25 bpw) build of WeiboAI/VibeThinker-3B (MIT) — a 3B dense reasoning model (Qwen2). Quantized by Osaurus; runs on Apple Silicon via Osaurus / mlx_lm. Emits <think> reasoning blocks.

Usage

python -m mlx_lm generate --model OsaurusAI/VibeThinker-3B-MXFP4 --prompt "What is 17 + 28?"

Or load in Osaurus.

Provenance

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Safetensors
Model size
0.6B params
Tensor type
U8
·
U32
·
BF16
·
MLX
Hardware compatibility
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4-bit

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