Find which open-weight LLMs fit in your GPU or Mac and compare the speeds people report on setups like yours.
Pick your GPU or Mac, then read the speeds people reported on it, or estimate which models fit and how fast they run.
Free to use. No account needed. Memory estimates and community measurements are labelled separately.
Search for a model to see its reported speeds across GPUs and Macs.
These are individual setups, not a controlled benchmark. Compare GPU count, quantization, context and offloading before comparing speeds. How to read a report →
Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.
NVIDIA RTX A6000 48GB · 1,000,000 ctx
User reports DeepSeek-V4-Flash-0731 UD-Q8_K_XL at a steady 17.20 t/s on an RTX A6000 48GB. Setup is an AMD EPYC 74F3 24-core with 8 channel 3200 DDR4. Prompt processing is in the high 70 t/s, down to mid 30 t/s at 300k context. The user says 48GB VRAM is enough for the full 1mil context but prompt processing would be very slow.
NVIDIA RTX A6000 48GB · llama.cpp
User reports bf16 with no quantization at 10.25 GB VRAM and 61 ms TTFT. Source is dev.to Gaurav Vij.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking