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.
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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.
M4 Pro 48GB · MLX · 4,096 ctx
User reports Qwen 3.6 27B at 18.3 tok/s decode on an Apple M4 Pro with 48 GB unified memory. Setup is MLX with 4-bit weights, 4096 context, and native MTP speculative decoding at depth 3. Without MTP the model decodes at about 7 tok/s; served over WiFi it reaches 14.3 tok/s, and llama.cpp with MTP gives 10.5 tok/s.
M4 Pro 48GB · MLX
User reports speculative decoding with mlx-dspark on an 8-bit target at a 2.45x mean speedup, 8.3 to 20.3 tok/s. Setup is mlx-dspark with a 4-bit target at 1.74x and 25.3 tok/s. The 8-bit target with drafter beats plain 4-bit at 14.6 tok/s.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking