Latest Content
Qwen3 14B icon

Qwen3 14B

NVIDIA
The Qwen3-14B is a large-scale Causal Language Model built on a 40-layer architecture with 13.2B non-embedding parameters, designed for workloads that require deeper reasoning capacity and higher generation fidelity across complex tasks. It supports a native 32,768-token context window and can be extended up to 131,072 tokens using YaRN, enabling effective processing of long-form documents, extended analytical prompts, and multi-stage conversational workflows. Leveraging Qwen3’s hybrid thinking design, the model transitions smoothly between deliberate, multi-step reasoning and efficient general-purpose generation.
TypeDense LLM
CapabilitiesText Generation, Instruction Following, Reasoning, Mathematical Reasoning+4 more
Group Release DateApril 28, 2025
Links
Paper|Blog|HF Model Card
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 -it --rm 
 --runtime=nvidia 
 --gpus all 
 --ipc=host 
 --shm-size=64g 
 -p 8000:8000 
 -v ~/.cache/huggingface:/root/.cache/huggingface 
 -e HF_TOKEN='YOUR_HF_TOKEN' 
 -e LD_LIBRARY_PATH='/usr/local/nvidia/lib64:/usr/local/nvidia/lib:/usr/lib/x86_64-linux-gnu' 
 vllm/vllm-openai:v0.15.0-cu130 
 Qwen/Qwen3-14B 
  --tensor-parallel-size 8 
  --max-model-len auto 
  --max-num-batched-tokens 65536 
  --gpu-memory-utilization 0.95 
  --max-num-seqs 1024 
  --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

Deploy NVIDIA B200 instancesContact Sales