llamaperf

Qwen3.8 27B

on 2× NVIDIA RTX 5070 Ti · llama.cpp

Tone: mixedNVIDIA hardware
Sep 16, 2026
Throughput
95.1 t/s gen · 1729.5 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
Q4_K_XL (GGUF)

Use cases

codingagenticvisionlong-context

Summary

User reports Qwen3.8 27B peaking at 95.1 t/s generation and 1729.5 t/s prompt processing on an RTX 5070 Ti plus RTX 4070 Super, with means of 73.8 t/s and 845.1 t/s. Setup is llama.cpp with the Unsloth UD-Q4_K_XL GGUF and speculative decoding via draft-dflash plus ngram-mod; Dflash2 with ngram ran 20% faster than MTP with ngram. MTP acceptance was 0.48108 (674 accepted of 1401 generated). User praises the model for coding and vision tasks but notes reasoning makes it slow and token-hungry, with up to 50% of context consumed by reasoning and poisoned tool calls looping at 100k+ context. Caching was finicky and default settings did not work.