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Qwen3 0.6B

NVIDIA
Qwen3 0.6B is a highly efficient causal language model from the Qwen3 family, built on a 28-layer architecture with approximately 0.44B non-embedding parameters. It is designed to deliver strong instruction following, logical reasoning, and multilingual understanding relative to its compact size. The model supports hybrid thinking modes, allowing step-by-step reasoning for complex tasks or fast responses for simpler queries. The model supports a 32K token context window, enabling it to handle extended prompts and multi-step interactions.
TypeDense LLM
CapabilitiesText Generation, Instruction Following, Reasoning, Mathematical Reasoning+4 more
Release Date29 April, 2025
Links
Paper|Blog
LicenseApache 2.0

Inference Instructions

Deploy and run this model on NVIDIA B200 GPUs using the command below. Copy the command to get started with inference.

CONSOLE
docker run --gpus all 
 --shm-size 64g 
 -p 8000:8000 
 -v ~/.cache/huggingface:/root/.cache/huggingface 
 -e HF_TOKEN='YOUR_HF_TOKEN' 
 --ipc=host 
 lmsysorg/sglang:v0.5.8-cu130 
 python3 -m sglang.launch_server 
 --model-path Qwen/Qwen3-0.6B 
 --host 0.0.0.0 
 --port 8000 
 --max-prefill-tokens 32768 
 --max-running-requests 1024 
 --enable-piecewise-cuda-graph 
 --tp 8 
 --mem-fraction-static 0.95 
 --attention-backend flashinfer 
 --trust-remote-code

Model Benchmarks

Each model was tested with a fixed input size and total token volume while increasing concurrency to measure serving performance under load.

ITL vs Concurrency

Time to First Token

Throughput Scaling

Total Tokens/sec vs Avg TTFT

Vultr Cloud GPU

NVIDIA HGX B200

Deploy NVIDIA B200 on Vultr Cloud GPU

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