| Type | Dense LLM |
| Capabilities | Text Generation, Instruction Following, Text Classification, Multilingual |
| Release Date | 17 February, 2026 |
| Links | |
| License | CC-BY-NC-4.0 |
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=128g -p 8000:8000 -v ~/.cache/huggingface:/root/.cache/huggingface -e HF_TOKEN='YOUR_HF_TOKEN' vllm/vllm-openai:v0.18.0 CohereLabs/tiny-aya-water --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
Note
Serving CohereLabs/tiny-aya-water requires gated model access via Hugging Face.
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
