Find which open-weight LLMs fit in your GPU or Mac and compare the speeds people report on setups like yours.
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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 Max 36GB · Inco Splash · 256,000 ctx
User reports Qwen3.8 27B at 15 t/s generation and about 100 t/s prefill on an M4 Max 36GB MacBook, running a 256K-token prompt. Setup is Inco Splash; no quant or KV cache format stated. User questions how the run fits in 36GB of RAM without significant swap.
M4 Max 36GB · Ollama · 128,000 ctx
User reports Qwen3.8 27B at 48 tok/s decode and 198 tok/s prompt processing at 4K context on an M4 Max with 36GB unified memory. Setup is Ollama 0.34.4 with NVFP4/MLX weights, q8_0 KV cache, flash attention enabled, and a 128K configured context. The GGUF Q4_K_M version of the same model reached only about 10.7 tok/s decode. Decode falls to 44 tok/s at 8K, 25 tok/s at 16K and 32K, and 14 tok/s at 115K, where time to first token reaches 21 minutes. The user notes that maximum context is not the same as comfortable interactive context and that memory pressure and swap grew during the stress runs.
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking