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 4090 · LM Studio · 120,000 ctx
User reports 3000 tokens in about 2 minutes, or 25 t/s, and is seeking faster performance. Setup is Q4_0 with 120k context and both caches quantized to 4_0. A reply adds a vLLM benchmark on an RTX 3090: a 27B INT4 quant at 125K context with a TurboQuant 3-bit NC KV cache and MTP speculative decoding, reaching 82 tok/s generation and 0.3-0.6s TTFT.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking