Qwen3.8-27B をとりあえず動かす- Q4: 70t/s, Q2: 100t/s
所感
良い感じ。Unsloth は、本家と同時に MTP 対応で GGUF を公開してくれた。
『RTX5070Ti + RTX5070』と『RTX5070Ti』の 2 パターンで動かす。
ただ、ワンショットは凄いが、エージェンティックな挙動は 3.6 の方が良い、チャットテンプレートが良くないとか、言われている。まー、初期不具合（かどうかは分からない）的なやつは良くあること。
のんびり遊びながら、動向をチェックしていく。
今回は、動かすだけ。
UD-Q4_K_XL (VRAM: 28 GB)
RTX5070Ti + RTX5070 / Context Length: 128K
llama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q4_K_XL \
-ngl 99 -fa on \
--temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 \
--presence-penalty 0.0 --repeat-penalty 1.0 \
--jinja --chat-template-kwargs '{"reasoning_effort": "low"}' \
-cb -np 1 \
--spec-type draft-mtp --spec-draft-n-max 2 \
-ts 18,12 -c 131072 -ctk q8_0 -ctv q8_0nvidia-smi
Sat Aug 15 10:56:44 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 610.43.02 KMD Version: 610.43.02 CUDA UMD Version: 13.3 |
+-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GeForce RTX 5070 Ti On | 00000000:01:00.0 Off | N/A |
| 0% 44C P8 11W / 300W | 15043MiB / 16303MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA GeForce RTX 5070 On | 00000000:04:00.0 Off | N/A |
| 0% 40C P8 3W / 250W | 11361MiB / 12227MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 3449 G /usr/lib/xorg/Xorg 4MiB |
| 0 N/A N/A 22038 C llama-server 15018MiB |
| 1 N/A N/A 3449 G /usr/lib/xorg/Xorg 4MiB |
| 1 N/A N/A 22038 C llama-server 11336MiB |
+-----------------------------------------------------------------------------------------+設計
Prompt: 494.53 tokens per second
Generate: 60.79 tokens per second
1.31.346.000 I slot print_timing: id 0 | task 0 | prompt eval time = 333.65 ms / 165 tokens ( 2.02 ms per token, 494.53 tokens per second)
1.31.346.002 I slot print_timing: id 0 | task 0 | eval time = 34906.21 ms / 2123 tokens ( 16.45 ms per token, 60.79 tokens per second)
1.31.346.003 I slot print_timing: id 0 | task 0 | total time = 35239.86 ms / 2288 tokens
1.31.346.013 I slot print_timing: id 0 | task 0 | graphs reused = 969
1.31.346.015 I slot print_timing: id 0 | task 0 | draft acceptance = 0.58598 ( 1145 accepted / 1954 generated), mean len = 2.17
1.31.346.075 I slot release: id 0 | task 0 | stop processing: n_tokens = 2287, truncated = 0実装
Prompt: 1619.46 tokens per second
Generate: 71.33 tokens per second
9.50.416.527 I slot print_timing: id 0 | task 981 | prompt eval time = 1335.02 ms / 2162 tokens ( 0.62 ms per token, 1619.46 tokens per second)
9.50.416.530 I slot print_timing: id 0 | task 981 | eval time = 333850.58 ms / 23815 tokens ( 14.02 ms per token, 71.33 tokens per second)
9.50.416.531 I slot print_timing: id 0 | task 981 | total time = 335185.59 ms / 25977 tokens
9.50.416.532 I slot print_timing: id 0 | task 981 | graphs reused = 9539
9.50.416.534 I slot print_timing: id 0 | task 981 | draft acceptance = 0.87431 (15150 accepted / 17328 generated), mean len = 2.75
9.50.416.653 I slot release: id 0 | task 981 | stop processing: n_tokens = 26137, truncated = 0生成の雰囲気
生成されたもの
UD-Q5_K_XL (VRAM: 28 GB)
RTX5070Ti + RTX5070 / Context Length: 96K
llama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q5_K_XL \
-ngl 99 -fa on \
--temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 \
--presence-penalty 0.0 --repeat-penalty 1.0 \
--jinja --chat-template-kwargs '{"reasoning_effort": "low"}' \
-cb -np 1 \
--spec-type draft-mtp --spec-draft-n-max 2 \
-ts 18,12 -c 98304 -ctk q8_0 -ctv q8_0設計
Prompt: 457.36 tokens per second
Generate: 53.35 tokens per second
2.19.131.193 I slot print_timing: id 0 | task 0 | prompt eval time = 360.77 ms / 165 tokens ( 2.19 ms per token, 457.36 tokens per second)
2.19.131.197 I slot print_timing: id 0 | task 0 | eval time = 40581.32 ms / 2166 tokens ( 18.74 ms per token, 53.35 tokens per second)
2.19.131.198 I slot print_timing: id 0 | task 0 | total time = 40942.09 ms / 2331 tokens
2.19.131.204 I slot print_timing: id 0 | task 0 | graphs reused = 1001
2.19.131.206 I slot print_timing: id 0 | task 0 | draft acceptance = 0.57178 ( 1155 accepted / 2020 generated), mean len = 2.14
2.19.131.268 I slot release: id 0 | task 0 | stop processing: n_tokens = 2330, truncated = 0実装
Prompt: 1518.63 tokens per second
Generate: 71.28 tokens per second
5.12.257.069 I slot print_timing: id 0 | task 1014 | prompt eval time = 1447.35 ms / 2198 tokens ( 0.66 ms per token, 1518.63 tokens per second)
5.12.257.072 I slot print_timing: id 0 | task 1014 | eval time = 108957.92 ms / 7768 tokens ( 14.03 ms per token, 71.28 tokens per second)
5.12.257.073 I slot print_timing: id 0 | task 1014 | total time = 110405.28 ms / 9966 tokens
5.12.257.074 I slot print_timing: id 0 | task 1014 | graphs reused = 3706
5.12.257.076 I slot print_timing: id 0 | task 1014 | draft acceptance = 0.91941 ( 5031 accepted / 5472 generated), mean len = 2.84
5.12.257.194 I slot release: id 0 | task 1014 | stop processing: n_tokens = 10126, truncated = 0UD-Q2_K_XL (VRAM: 16 GB)
RTX5070Ti / Context Length: 64K
CUDA_VISIBLE_DEVICES=0 \
llama-server -hf unsloth/Qwen3.8-27B-GGUF:UD-Q2_K_XL \
-ngl 99 -fa on \
--temp 1.0 --top-p 0.95 --top-k 20 --min-p 0.0 \
--presence-penalty 0.0 --repeat-penalty 1.0 \
--jinja --chat-template-kwargs '{"reasoning_effort": "low"}' \
-cb -np 1 \
--spec-type draft-mtp --spec-draft-n-max 2 \
-c 65536 -ctk q8_0 -ctv q8_0nvidia-smi
Sat Aug 15 11:19:25 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 610.43.02 KMD Version: 610.43.02 CUDA UMD Version: 13.3 |
+-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GeForce RTX 5070 Ti On | 00000000:01:00.0 Off | N/A |
| 0% 43C P8 14W / 300W | 14709MiB / 16303MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA GeForce RTX 5070 On | 00000000:04:00.0 Off | N/A |
| 0% 35C P8 4W / 250W | 15MiB / 12227MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 3449 G /usr/lib/xorg/Xorg 4MiB |
| 0 N/A N/A 28245 C llama-server 14686MiB |
| 1 N/A N/A 3449 G /usr/lib/xorg/Xorg 4MiB |
+-----------------------------------------------------------------------------------------+設計
Prompt: 547.33 tokens per second
Generate: 84.97 tokens per second
0.47.757.044 I slot print_timing: id 0 | task 0 | prompt eval time = 301.46 ms / 165 tokens ( 1.83 ms per token, 547.33 tokens per second)
0.47.757.047 I slot print_timing: id 0 | task 0 | eval time = 26104.45 ms / 2219 tokens ( 11.77 ms per token, 84.97 tokens per second)
0.47.757.047 I slot print_timing: id 0 | task 0 | total time = 26405.92 ms / 2384 tokens
0.47.757.052 I slot print_timing: id 0 | task 0 | graphs reused = 1036
0.47.757.054 I slot print_timing: id 0 | task 0 | draft acceptance = 0.56124 ( 1173 accepted / 2090 generated), mean len = 2.12
0.47.757.106 I slot release: id 0 | task 0 | stop processing: n_tokens = 2383, truncated = 0実装
Prompt: 1580.41 tokens per second
Generate: 107.59 tokens per second
2.11.070.865 I slot print_timing: id 0 | task 1049 | prompt eval time = 1415.46 ms / 2237 tokens ( 0.63 ms per token, 1580.41 tokens per second)
2.11.070.868 I slot print_timing: id 0 | task 1049 | eval time = 59961.08 ms / 6452 tokens ( 9.29 ms per token, 107.59 tokens per second)
2.11.070.869 I slot print_timing: id 0 | task 1049 | total time = 61376.53 ms / 8689 tokens
2.11.070.870 I slot print_timing: id 0 | task 1049 | graphs reused = 3342
2.11.070.871 I slot print_timing: id 0 | task 1049 | draft acceptance = 0.88336 ( 4120 accepted / 4664 generated), mean len = 2.77
2.11.070.977 I slot release: id 0 | task 1049 | stop processing: n_tokens = 8850, truncated = 0生成の雰囲気
生成されたもの
ゲームとして面白かったもの
何回か生成したので、その中で出来が良かったものを記録として。
Best Game (UD-Q2_K_XL ワンショット)
Best UI (UD-Q4_K_XL ワンショット)
（おまけ）Ngram を添えて
気持ち早くなる（かな？）
--spec-type draft-mtp,ngram-mod
--spec-draft-n-max 6
--spec-draft-p-min 0.75
--spec-ngram-mod-n-match 24
--spec-ngram-mod-n-min 48
--spec-ngram-mod-n-max 64
--reasoning-budget 8196
--chat-template-kwargs "{\"preserve_thinking\": true}"How to combine mtp and ngram to get extra performance ? I just use these flags, I have an app to help with that you can use that if you want it's open source.
— Ark (@quimedesu) August 14, 2026
--spec-type draft-mtp,ngram-mod
--spec-draft-n-max 6
--spec-draft-p-min 0.75
--spec-ngram-mod-n-match 24… https://t.co/2xuq53dRFA