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.
M2 Max 64GB · Transformers
User reports Qwen3.5 4B at 70.4 t/s on an M2 Max using native GGUF support in transformers. Setup is the Q4_K_M GGUF from unsloth, reusing ggml kernels on Apple Silicon. llama.cpp reached 71.8 t/s on the same model. Two other models were also tested: Qwen3.8 27B UD-Q4_K_M at 15.9 t/s (vs 13.4 t/s with llama.cpp) and Qwen3.5 35B-A3B UD-IQ4_XS at 60.2 t/s (vs 61.3 t/s).
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking