Another qwen 3.8 27b showcase - gta style prompt - also a remainder to use ngram in your configs.

https://preview.redd.it/ewxbqcpuakkh1.png?width=2559&format=png&auto=webp&s=e20b67d1c1444f5ba19cc0d6ccd10db84dc544bf Here is the link : https://cobalt-scheduler-2hj0.pagedrop.io/ fully playable small gta vice city style game, all made with qwen 3.8 27b with 128k context. fully used the context so you can also check the summary. Performance Summary (Real Data from Log) Setup Model: Qwen3.8-27B-Q6_K Hardware: 2x RTX 5060 Ti (32 GB) Context: 131,072 tokens Prompt Processing (Prefill) 25k tokens: ~850–890 tokens/s (e.g., 9.41 s for 25,177 tokens) 62 tokens: ~47 tokens/s (31.51 s log) Token Generation (Decoding) Best sustained speed: 197 tokens/s (task 16515, 15,787 tokens generated) - Yes it is 197 t/s because I use ngram and it just uses the same tokens. it skyrockets when you use it to write the same thing while debugging. Typical sustained speed: 50–55 tokens/s (task 0, 25,173 tokens) Short unique prompts: 35–40 tokens/s (task 27449, 530 tokens) Speculative Efficiency Peak acceptance rate: 89.46% (task 16515) Mean draft length at peak: 18.28 tokens Typical acceptance: 63–66% with draft length ~2.3–3.7 Total Output Evidence Longest run: 31,468 tokens generated at 55.46 t/s (task 18497) Fastest run: 15,787 tokens at 197.77 t/s (task 16515) Here is the detailed summary Token Usage and Performance Stability (Real Data) Task Tokens Generated Generation Speed (tokens/s) 0 25,173 58.80 10794 20,765 71.83 16515 15,787 197.77 -n gram kicked in yo 17412 15,960 165.81 18497 31,468 55.46 27449 530 39.44 27659 3,564 39.80 29015 1,276 36.77 29568 3,056 37.35 30825 2,075 37.50 Speed Decrease and Stability Baseline speed (short or unique prompts): 36–40 t/s (tasks 27449–30825) – highly stable. Typical long-run speed (moderate cache hits): 55–72 t/s (tasks 0, 10794, 18497). Peak speed (high cache hits): 166–198 t/s (tasks 16515, 17412). Maximum observed decrease: from 197.77 t/s (task 16515) down to 36.77 t/s (task 29015) – a drop of 81% when speculative cache is ineffective. Longest generation run: 31,468 tokens at a stable 55.46 t/s (task 18497), indicating no performance degradation over extended output. Here is my config for the curious i am sure that it will help someone "C:\Users\dsdt\llama\llama-server.exe" ^ -m "C:\Users\dsdt\Modeller\Qwen3.8-27B-UD-Q6_K.gguf" ^ --mmproj "C:\Users\dsdt\Modeller\mmproj-BF16.gguf" ^ --jinja ^ --chat-template-kwargs "{\"reasoning_effort\":\"medium\"}" ^ --chat-template-file "C:\Users\dsdt\Modeller\chat_template.jinja" ^ --reasoning on ^ --reasoning-preserve ^ -c 131072 ^ --split-mode tensor ^ --flash-attn on ^ --cache-type-k q8_0 ^ --cache-type-v q8_0 ^ --spec-type draft-mtp,ngram-mod ^ --spec-draft-n-max 2 ^ --spec-ngram-mod-n-match 24 ^ --spec-ngram-mod-n-min 24 ^ --spec-ngram-mod-n-max 86 ^ -t 8 ^ --batch-size 8869 ^ --ubatch-size 531 ^ -ngl 105 ^ -np 1 ^ --fit off ^ --temp 1.0 ^ --top-p 0.95 ^ --top-k 20 ^ --min-p 0.00 ^ --presence-penalty 0.0 ^ --host 127.0.0.1 ^ --port 8080"