对 M5 MAX 跑本地大模型有点失望
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基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

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基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

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基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

@566656661 看來真的是 兩張r9700的合體都做不了...
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@566656661 感谢数据,不错的,就是体感感觉NVFP4的精度稍差,回头我跑一下4bit和fp8之间的benchmark,看看困惑度有多少差距。
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@566656661 看來真的是 兩張r9700的合體都做不了...
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5 566656661 被引用 于这个主题
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推荐一个很适合 macOS 跑的模型 https://huggingface.co/LibraxisAI/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-vmlx-mxfp4
我自己的 benchmark 和实测都完全有 27B bf16 mlx 版本的功力,但是速度快多了
关键是还越狱
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推荐一个很适合 macOS 跑的模型 https://huggingface.co/LibraxisAI/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-vmlx-mxfp4
我自己的 benchmark 和实测都完全有 27B bf16 mlx 版本的功力,但是速度快多了
关键是还越狱
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@tomcatzh 硬件什么配置?
@johnnybegood 占显存大概 20G 不到,连 cache,m4 max跑的飞快
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基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

看了都觉得爽, 可惜买不起
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基本上我是把上下文拉爆(日間Coding需要), 然後concurrency單純調1, 並沒有特別針對hermes做什麼特別優化 (也許研究一下會更好, 不過得要有空)
趁現在午休的時候跑了一下llama benchy
llama-benchy \ --base-url "http://localhost:7380/v1" \ --model "Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --tokenizer "$HOME/vllm/models/sakamakismile/Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP" \ --pp 2048 \ --tg 480 \ --depth 0 1000 5000 10000 20000 50000 100000 150000 200000 \ #(不同上下文長度) --latency-mode generation \ --skip-coherence \ --concurrency 1 \Context Ladder
| model | test | t/s | peak t/s | ttfr (ms) | est_ppt (ms) | e2e_ttft (ms) | |:-----------------------------------------|-----------------:|------------------:|-------------:|------------------:|------------------:|------------------:| | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 | 7741.01 ± 1375.30 | | 373.94 ± 54.49 | 274.26 ± 54.49 | 373.94 ± 54.49 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 | 68.87 ± 6.65 | 81.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d1000 | 8136.73 ± 32.84 | | 474.32 ± 1.44 | 374.64 ± 1.44 | 474.32 ± 1.44 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d1000 | 67.73 ± 5.06 | 88.00 ± 5.72 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d5000 | 6615.23 ± 22.79 | | 1165.21 ± 3.86 | 1065.53 ± 3.86 | 1165.21 ± 3.86 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d5000 | 72.92 ± 3.56 | 89.33 ± 3.77 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d10000 | 6008.73 ± 10.16 | | 2104.88 ± 3.47 | 2005.20 ± 3.47 | 2104.88 ± 3.47 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d10000 | 65.25 ± 2.21 | 82.00 ± 4.32 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d20000 | 5152.21 ± 0.52 | | 4379.13 ± 0.52 | 4279.45 ± 0.52 | 4380.19 ± 0.46 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d20000 | 70.45 ± 1.27 | 89.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d50000 | 3690.36 ± 5.88 | | 14203.66 ± 22.59 | 14103.98 ± 22.59 | 14205.86 ± 22.80 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d50000 | 67.03 ± 1.67 | 84.67 ± 0.47 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d100000 | 2528.58 ± 0.55 | | 40457.51 ± 8.72 | 40357.83 ± 8.72 | 40461.50 ± 8.69 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d100000 | 60.96 ± 0.75 | 78.33 ± 3.68 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d150000 | 1922.36 ± 0.98 | | 79194.84 ± 39.68 | 79095.17 ± 39.68 | 79201.49 ± 39.50 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d150000 | 62.53 ± 3.29 | 76.33 ± 1.89 | | | | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | pp2048 @ d200000 | 1556.00 ± 0.99 | | 129951.65 ± 82.49 | 129851.97 ± 82.49 | 129959.72 ± 82.53 | | Huihui-Qwen3.6-27B-abliterated-NVFP4-MTP | tg480 @ d200000 | 59.58 ± 1.31 | 69.67 ± 1.70 | | | |Token速度相當可用, 200K上下都能大約有60 tks

看了都觉得爽, 可惜买不起
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@applejuice
他这张是 Pro 4500,比M5 max便宜很多,性价比很好,只是显存稍显紧张一点儿 -
M5 Max 跑 Qwen 122b a10b Q4 的话, 如果内存够, 不大可能只有 20-25t/s.
我的M5 pro 跑 Qwen 27b 稠密加上MTP之后, 还能跑到20以上, 64k上下文时候掉到 17多.
按这个速度推理, M5 max 是我显存带宽的两倍, 它能到 40t/s 以上.
122b A10b 肯定比27b 稠密要快, 应该能跑到 60t/s以上, 我估计.
另外, 122A10 的智力应该不如 27b 稠密, 只是知识面更宽.
M5 Max 跑 Qwen 122b a10b Q4 的话, 如果内存够, 不大可能只有 20-25t/s.
我的M5 pro 跑 Qwen 27b 稠密加上MTP之后, 还能跑到20以上, 64k上下文时候掉到 17多.
按这个速度推理, M5 max 是我显存带宽的两倍, 它能到 40t/s 以上.
122b A10b 肯定比27b 稠密要快, 应该能跑到 60t/s以上, 我估计.
另外, 122A10 的智力应该不如 27b 稠密, 只是知识面更宽.
请教一下Tony的Qwen27B MTP用的哪个版本的模型?我下了oQ8-mtp,omlx经常退出,看日志好像是mtp的bug,求推荐稳定运行的模型版本,谢谢!
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@Tony-Wang 涡轮卡的散热策略偏安静,max-q的出厂设置在300w功耗,温度干到90度的时候风扇也只吹到80%。都是可调整的,up说的不可调整估计是用官方的NVIDIA X Server Settings工具,温控功能确实是置灰的不能调。这个问题当时也是卡了我一下午,问了几个大模型,推荐了若干工具。最后试过一遍之后,LACT工具完美解决,拉一拉曲线都能整,小工具还支持多卡不同曲线。4090+max-q已测试通过非常好用,up也可以试试看

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@Tony-Wang 涡轮卡的散热策略偏安静,max-q的出厂设置在300w功耗,温度干到90度的时候风扇也只吹到80%。都是可调整的,up说的不可调整估计是用官方的NVIDIA X Server Settings工具,温控功能确实是置灰的不能调。这个问题当时也是卡了我一下午,问了几个大模型,推荐了若干工具。最后试过一遍之后,LACT工具完美解决,拉一拉曲线都能整,小工具还支持多卡不同曲线。4090+max-q已测试通过非常好用,up也可以试试看



