Gemma 3 1B

User reports 294.1 t/s generation. Source evidence (verbatim): Source: https://dev.to/sikamikanikobg/vllm-vs-llamacpp-vs-ollama-what-happens-when-your-model-doesnt-fit-in-24gb-vram-56eb # vLLM vs llama.cpp vs Ollama: What Happens When Your Model Doesn't Fit in 24GB VRAM Hardware: NVIDIA RTX 3090 24GB, 128GB system RAM. Concurrency 1 decode tok/s (llama.cpp / vLLM): Gemma 3 1B 294.1 / 235.5. Qwen3-Coder 30B-A3B 157.2 / 172.0 (vLLM AWQ). Gemma 4 26B-A4B 118.8 / 133.8. Ollama at concurrency 1: 125.6, 129.3, 84.5. Single-stream steady-state decode on the longest prompt tier with models that exceed VRAM (llama.cpp -ngl 12 for gpt-oss-120b): GPT-OSS-120B 7.65 tok/s llama.cpp, 7.6 Ollama. GLM-4.5-Air 4.58 llama.cpp, 4.59 Ollama. vLLM ran out of memory on both. Engine versions and context length not stated.