A40 vLLM: google/gemma-3-4b-it aggregate output throughput, 100 concurrent

Database Mart hosted-GPU report, page footer dated 10/07/2026. Engine is vLLM built from github.com/vllm-project/vllm with no release tag or commit printed, so the engine version is unpinned. Weights are the Hugging Face checkpoint at the precision the table labels 'Quantization 16' (bf16/fp16 not distinguished); format_id is null because data/quantization/ has no fp16/bf16 record. Single GPU, tensor parallel 1. Input length fixed at 100 tokens, output length fixed at 600 tokens. The 'Output (tokens/s)' column is aggregate generated tokens across the concurrent requests divided by benchmark duration, NOT a per-request decode rate. Median TTFT is the median time to first token under that same concurrency. Third-party measurement by the GPU host; confidence capped because the harness and the vLLM commit are unpublished. Card: NVIDIA A40, Ampere, 48 GB GDDR6, 10,752 CUDA cores. 100 requests, input length 100, output length 600, benchmark duration 48.12 s, total input tokens 10000, total generated tokens 19307. AGGREGATE across the concurrent requests, not a per-request decode rate.

Output (tokens/s) column. These six model rows were not in the earlier A40 filing, which covered Llama 3.1 8B and Qwen2.5 7B/14B only.