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Validated Model Performance

  1. LLM Quantization

  2. LLM Runtime Inference based on Pytorch Mode

    2.1 LLMs

    2.2 Stable Diffusion

    2.3 Electra

  3. LLM Runtime (GGML-Compatible)

    3.1 MPT-7B

    3.2 GPT-j-6B

    3.3 Falcon-7B

    3.4 GPT-NEOX-20B

    3.5 Dolly-V2-3B

    3.6 OPT-1.3B

    3.7 StarCoder-3B

  4. LLM Finetuning

System summary: Test by Intel on 09/19/2023. 1-node, 1x Intel(R) Xeon(R) Platinum 8480+ @3.8GHz, 56 cores/socket, HT On, Turbo On, Total Memory 256GB (16x16GB DDR5 4800 MT/s [4800 MT/s]), BIOS 3A14.TEL2P1, microcode 0x2b0001b0, CentOS Stream 8, gcc (GCC) 8.5.0 20210514 (Red Hat 8.5.0-10), DL Models, Frameworks/Backends: PyTorch/ONNXRT/LLM Runtime/GGML, Datatype: FP32/INT8/BF16/FP8. Using 1 socket, 56 cores/instance, 1 instance and batch size 1

Performance varies by use, configuration and other factors. For more complete information about performance and benchmark results, visit www.intel.com/benchmarks

LLM Quantization

Environment:

Pytorch: 2.0.1+cpu

Intel Extension for Pytorch: 2.0.100+cpu

Intel Neural Compressor: 2.3

INT8 FP32 INT8/FP32
Framework Model Datasets Throughput (samples/sec) Accuracy Throughput (samples/sec) Accuracy Throughput Gain Relative Accuracy (INT8- FP32)/FP32
pytorch opt_1.3b NeelNanda/pile-10k 34.07 57.05% 19.92 57.89% 1.71 -1.44%
pytorch bloom_1b7 NeelNanda/pile-10k 29.74 49.95% 13.3 46.34% 2.24 7.79%
pytorch bloom_7b1 NeelNanda/pile-10k 12.36 60.14% 3.22 57.64% 3.83 4.34%
pytorch opt_2.7b NeelNanda/pile-10k 23.19 63.67% 12.24 63.65% 1.89 0.03%
pytorch opt_6.7b NeelNanda/pile-10k 13.5 67.01% 4.1 67.69% 3.29 -1.00%
pytorch gpt_j_6b NeelNanda/pile-10k 10.76 67.59% 4.38 68.31% 2.46 -1.05%
pytorch flan_t5_large samsum 69.75 46.25 (rougeLsum) 33.16 47.67 (rougeLsum) 2.1 -2.99%
pytorch gpt_neox_clm wikitext 1.47 4.04 (eval_loss) 0.65 3.52 (eval_loss) 2.27 -14.78%
pytorch gpt_j_6b_clm wikitext 0.86 3 (eval_loss) 0.28 2.34 (eval_loss) 3.1 -28.67%
onnx whisper_large lambda-openai 2.11 97.07% 1.13 96.96% 1.87 0.12%

LLM Runtime Inference based on Pytorch Mode

Environment:

Pytorch: 2.0.1+cpu

LLMs

Framework Model Input Output INT8 FP32 BF16 FP8 INT8/FP32 BF16/FP32 FP8/FP32
pytorch gpt-neox-20b 32 32 9283 (ms)
pytorch dolly-v2-3b 32 32 3191 (ms) 3798 (ms) 2689 (ms) 1.19x 1.41x
pytorch gpt-j-6b-pruned 32 32 4523 (ms) 2421 (ms) 1758 (ms) 1.87x 2.57x
pytorch gpt-j-6b 32 32 1658 (ms) 4561 (ms) 2429 (ms) 1793 (ms) 2.75x 1.88x 2.54x

Stable Diffusion

Model Steps Output INT8 FP32 BF16 INT8+BF16* INT8/FP32 BF16/FP32
stable_diffusion_v2_1 20 512*512 16.98 (s) 2.83 (s) 6.00x
stable_diffusion_v1_5 20 512*512 2.18 (s) 10.94 (s) 2.74 (s) 5.01x 3.99x
stable_diffusion_v1_5 50 512*512 5.2 (s) / FID=35.46 6.3 (s) / FID = 31.07 5.5 (s) / FID = 30.58
stable_diffusion_v1_4 20 512*512 11.39 (s) 2.83 (s) 4.02x

Note: *Only works when steps = 50, using BF16 for inference from steps 1 to 5 and from steps 46 to 50, and INT8 for inference from steps 6 to 45. In this inference mode, accuracy and speed can achieve a good balance.

Electra

FP32 BF16 BF16/FP32
Model Batch Size Seq Length Latency (ms) Latency (ms) Latency
electra_base_chinese_discriminator 1 16 11.50 4.30 2.67x
4 16 5.50 1.80 3.06x
8 16 6.20 1.70 3.65x
16 16 5.60 1.30 4.31x
32 16 5.70 1.20 4.75x
64 16 5.20 1.10 4.73x
electra_base_chinese_generator 1 128 13.72 3.89 3.53x
4 128 11.60 2.83 4.10x
8 128 11.44 2.85 4.01x
16 128 12.04 2.70 4.46x
32 128 11.29 2.52 4.48x
64 128 11.75 2.54 4.63x

LLM Runtime (GGML-Compatible)

Environment: GCC / G++: 12.1.0 Transformers version: 4.35.2

MPT-7B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 36.95 3522 108.74 958.5 37.24 92.32
LLM Runtime 1024 32 32 INT4 INT8 128 46.69 4913 15834 17281 46.83 10940
LLM Runtime 32 32 48 INT4 INT8 128 34.76 5206 100.94 900 34.9 85.92
LLM Runtime 1024 32 48 INT4 INT8 128 44.98 5147 15506 16901 45.38 10713
LLM Runtime 32 32 56 INT4 INT8 128 35.84 5230 98.71 922 36.07 84.33
LLM Runtime 1024 32 56 INT4 INT8 128 45.54 5197 15180 16591 45.73 10488
LLM Runtime 32 32 32 INT4 INT8 32 38.33 4101 157.31 1345 38.59 120.53
LLM Runtime 1024 32 32 INT4 INT8 32 48.19 5346 17178 18672 48.35 11868
LLM Runtime 32 32 48 INT4 INT8 32 37.75 5199 140.79 1310 37.94 108.99
LLM Runtime 1024 32 48 INT4 INT8 32 47.21 5282 17245 18708 47.36 11914
LLM Runtime 32 32 56 INT4 INT8 32 38.04 5227 137.21 1316 38.19 106.53
LLM Runtime 1024 32 56 INT4 INT8 32 47.88 5274 17454 18939 48.15 12058
GGML 32 32 32 INT4 INT8 32 37.92 4047 447.6 1622 38.26 320.8
GGML 1024 32 32 INT4 INT8 32 47.74 5207 26552 28032 48.03 18336
GGML 32 32 48 INT4 INT8 32 34.78 5192 330.06 1408 35.02 238.66
GGML 1024 32 48 INT4 INT8 32 44.64 5231 22389 23772 44.81 15462
GGML 32 32 56 INT4 INT8 32 34.53 5225 313.45 1383 34.79 227.08
GGML 1024 32 56 INT4 INT8 32 44.64 5242 21568 22951 44.86 14896

GPT-j-6B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 23.59  4018 62.48 793.86 23.82 50.55
LLM Runtime 1024 32 32 INT4 INT8 128 26.2 4036 2055 2867 26.43 1426
LLM Runtime 2012 32 32 INT4 INT8 128 29.21 4553 6114 7019 29.33 4228
LLM Runtime 32 32 48 INT4 INT8 128 21.56 5230 60.56 729 21.75 48.68
LLM Runtime 1024 32 48 INT4 INT8 128 23.92 5212 1763 2504 24.17 1224
LLM Runtime 2012 32 48 INT4 INT8 128 26.62 5119 5230 6055 26.81 3617
LLM Runtime 32 32 56 INT4 INT8 128 21.98 5244 60.85 742.08 22.28 49.05
LLM Runtime 1024 32 56 INT4 INT8 128 24.54 5234 2007 2768 24.7 1393
LLM Runtime 2012 32 56 INT4 INT8 32 27.16 5184 5151 5993 27.4 3563
LLM Runtime 32 32 32 INT4 INT8 32 25.35 3739 107.52 893.52 25.42 82.17
LLM Runtime 1024 32 32 INT4 INT8 32 28.04 4435 3405 4275.2 28.07 2359
LLM Runtime 2012 32 32 INT4 INT8 32 30.36 4914 8916 9857 30.42 6161
LLM Runtime 32 32 48 INT4 INT8 32 24.09 5228 95.24 842.1 24.13 74.4
LLM Runtime 1024 32 48 INT4 INT8 32 26.65 5190 3307 4133 26.89 2290
LLM Runtime 2012 32 48 INT4 INT8 32 29.09 5164 8021 8923 29.18 5544
LLM Runtime 32 32 56 INT4 INT8 32 24.66 5243 98.16 862.7 24.93 75.54
LLM Runtime 1024 32 56 INT4 INT8 32 27.07 5222 3060 3899 27.38 2120
LLM Runtime 2012 32 56 INT4 INT8 32 29.56 5210 7599 8515 29.85 5253
GGML 32 32 32 INT4 INT8 32 33.69 3585 393.24 1437 33.9 281.6
GGML 1024 32 32 INT4 INT8 32 36.24 4389 12702 13825 36.39 8775
GGML 2012 32 32 INT4 INT8 32 39.19 5232 27264 28479 39.44 18824
GGML 32 32 48 INT4 INT8 32 30.34 5223 291.84 1232 30.57 210
GGML 1024 32 48 INT4 INT8 32 33.09 5137 9206 10231 33.21 6362
GGML 2012 32 48 INT4 INT8 32 37.34 5245 21341 22499 37.66 14737
GGML 32 32 56 INT4 INT8 32 31.62 5241 262.3 1242 32 192.2
GGML 1024 32 56 INT4 INT8 32 34.03 5193 8363 9418 34.3 5781
GGML 2012 32 56 INT4 INT8 32 36.94 5257 18868 20013 37.66 13031

Falcon-7B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 37.36 3797 92.94 1251 37.69 75.88
LLM Runtime 1024 32 32 INT4 INT8 128 40.33 4707 5507 6757 40.63 3813
LLM Runtime 32 32 48 INT4 INT8 128 35.84 4990 88.29 1199 36.32 72.68
LLM Runtime 1024 32 48 INT4 INT8 128 37.95 4951 5025 6201 38.14 3479
LLM Runtime 32 32 56 INT4 INT8 128 36.1 5019 83.89 1202 36.36 69.19
LLM Runtime 1024 32 56 INT4 INT8 128 38.88 4993 5432 6637 39.41 3761
LLM Runtime 32 32 32 INT4 INT8 32 39.15 4395 146.7 1359 39.43 113.16
LLM Runtime 1024 32 32 INT4 INT8 32 41.61 5213 6947 8237 42.54 4807
LLM Runtime 32 32 48 INT4 INT8 32 38.08 4980 134.9 1315 38.23 105.1
LLM Runtime 1024 32 48 INT4 INT8 32 40.58 5085 6847 8105 40.82 4737
LLM Runtime 32 32 56 INT4 INT8 32 38.33 5011 142.4 1330 38.55 110.8
LLM Runtime 1024 32 56 INT4 INT8 32 40.87 5084 6860 8127 41.18 4746
GGML 32 32 32 INT4 INT8 32 38.44 4269 458.3 1650 38.55 328.4
GGML 1024 32 32 INT4 INT8 32 41.64 4997 17585 18876 41.94 12147
GGML 32 32 48 INT4 INT8 32 35.87 4971 338.3 1450 36 244.7
GGML 1024 32 48 INT4 INT8 32 38.68 5024 13064 14263 39.06 9026
GGML 32 32 56 INT4 INT8 32 36.22 5005 318.9 1441 36.43 231.2
GGML 1024 32 56 INT4 INT8 32 38.65 5045 11943 13142 38.83 8253

GPT-NEOX-20B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 68.77 10621 234.18 2365 69.11 183.16
LLM Runtime 1024 32 32 INT4 INT8 128 76.55 12537 9817 12190 77.06 6798
LLM Runtime 32 32 48 INT4 INT8 128 60.35 13639 214.2 2085 60.59 167.34
LLM Runtime 1024 32 48 INT4 INT8 128 68.19 13524 9213 11327 68.48 6378
LLM Runtime 32 32 56 INT4 INT8 128 80.16 13650 221.5 2706 107.23 186.9
LLM Runtime 1024 32 56 INT4 INT8 128 88.48 13586 10045 12788 111.93 6968
LLM Runtime 32 32 32 INT4 INT8 32 73.78 11970 390.1 2308 74.13 308.2
LLM Runtime 1024 32 32 INT4 INT8 32 80.75 13871 14993 17496 81.07 10370
LLM Runtime 32 32 48 INT4 INT8 32 68.17 13616 348.6 2121 68.54 275.9
LLM Runtime 1024 32 48 INT4 INT8 32 74.84 13717 15278 17598 75.24 10566
LLM Runtime 32 32 56 INT4 INT8 32 79.57 13638 398.2 2467 103.79 324.2
LLM Runtime 1024 32 56 INT4 INT8 32 86.06 13703 18119 20787 118.86 12541
GGML 32 32 32 INT4 INT8 32 98.23 11660 1403 4448 99.04 998.9
GGML 1024 32 32 INT4 INT8 32 105.33 13686 45434 48699 105.79 31382
GGML 32 32 48 INT4 INT8 32 86.19 13582 980 3651 86.74 703.1
GGML 1024 32 48 INT4 INT8 32 93.79 13674 32966 35873 94.4 22776
GGML 32 32 56 INT4 INT8 32 92.36 13621 1136 3999 119.08 823.6
GGML 1024 32 56 INT4 INT8 32 95.49 13675 39914 42874 115.03 27579

Dolly-V2-3B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 21.84 2653 78.37 755.43 22.29 61.18
LLM Runtime 1024 32 32 INT4 INT8 128 24.46 2653 3725 4483 24.69 2578
LLM Runtime 32 32 48 INT4 INT8 128 22.76 2665 81.26 786.95 23.06 63.31
LLM Runtime 1024 32 48 INT4 INT8 128 25.54 2677 3399 4191 25.73 2354
LLM Runtime 32 32 56 INT4 INT8 128 22.02 2693 78.17 760.6 22.14 61
LLM Runtime 1024 32 56 INT4 INT8 128 33.41 2693 3799 4834 66.96 2643
LLM Runtime 32 32 32 INT4 INT8 32 22.5 2653 95.91 793.2 22.78 73.27
LLM Runtime 1024 32 32 INT4 INT8 32 25.77 2653 4374 5173 25.88 3026
LLM Runtime 32 32 48 INT4 INT8 32 23.77 2665 97.84 834.5 23.84 75.06
LLM Runtime 1024 32 48 INT4 INT8 32 26.29 2728 4361 5176 26.56 3018
LLM Runtime 32 32 56 INT4 INT8 32 23.79 2693 88.55 826.7 23.91 68.58
LLM Runtime 1024 32 56 INT4 INT8 32 29.4 2725 4822 5733 31.21 3348
GGML 32 32 32 INT4 INT8 32 21.53 2653 219.81 887.6 21.68 158.3
GGML 1024 32 32 INT4 INT8 32 24.43 2653 8011 8768 24.6 5535
GGML 32 32 48 INT4 INT8 32 22.04 2665 178.7 861.6 22.12 129.6
GGML 1024 32 48 INT4 INT8 32 23.85 2693 6342 7081 24.05 4384
GGML 32 32 56 INT4 INT8 32 22.18 2693 166.6 853.7 22.26 121.6
GGML 1024 32 56 INT4 INT8 32 28.84 2703 8715 9609 56.39 6034

OPT-1.3B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 9.85  1680 104.88 410.2 9.95 75.58
LLM Runtime 1024 32 32 INT4 INT8 128 11.38 1702 3080 3433 11.83 2129
LLM Runtime 2012 32 32 INT4 INT8 128 13.15 2513 7516 7924 13.41 5190
LLM Runtime 32 32 48 INT4 INT8 128 9.25 2709 110.7 397.3 9.3 79.38
LLM Runtime 1024 32 48 INT4 INT8 128 11.1 2698 3064 3408 11.15 2118
LLM Runtime 2012 32 48 INT4 INT8 128 12.77 2701 8045 8441 13.02 5555
LLM Runtime 32 32 56 INT4 INT8 128 9.78 2742 112.7 415.89 9.84 80.95
LLM Runtime 1024 32 56 INT4 INT8 128 16.96 2737 3125 3650 54.16 2174
LLM Runtime 2012 32 56 INT4 INT8 32 16.69 2729 7929 8447 24.51 5488
LLM Runtime 32 32 32 INT4 INT8 32 10.01  1703 109.6 419.9 10.1 78.87
LLM Runtime 1024 32 32 INT4 INT8 32 11.71 1760 3389 3752 11.8 2342
LLM Runtime 2012 32 32 INT4 INT8 32 13.58 2720 8061 8482 13.63 5566
LLM Runtime 32 32 48 INT4 INT8 32 9.69 2709 116.5 416.9 9.81 83.67
LLM Runtime 1024 32 48 INT4 INT8 32 11.51 2686 3290 3647 11.55 2274
LLM Runtime 2012 32 48 INT4 INT8 32 13.09 2753 8101 8507 13.14 5594
LLM Runtime 32 32 56 INT4 INT8 32 10.4 2742 117.3 439.8 10.48 84.37
LLM Runtime 1024 32 56 INT4 INT8 32 15.65 2730 3494 3979 37.89 2427
LLM Runtime 2012 32 56 INT4 INT8 32 20.52 2758 8395 9031 55.67 5811
GGML 32 32 32 INT4 INT8 32 8.47  1699 170 432.6 8.88 120.12
GGML 1024 32 32 INT4 INT8 32 10.07 1702 4940 5252 10.13 3412
GGML 2012 32 32 INT4 INT8 32 11.71 2709 11741 12104 11.75 8105
GGML 32 32 48 INT4 INT8 32 8.9 2709 154.83 430.6 9.05 109.7
GGML 1024 32 48 INT4 INT8 32 10.12 2669 4409 4723 10.2 3046
GGML 2012 32 48 INT4 INT8 32 12.16 2742 11009 11386 12.19 7600
GGML 32 32 56 INT4 INT8 32 9.48 2742 152.31 446.04 9.56 108.14
GGML 1024 32 56 INT4 INT8 32 14.39 2721 5843 6289 27.99 4049
GGML 2012 32 56 INT4 INT8 32 17.01 2751 13001 13529 51.84 8989

StarCoder-3B

Backend Input Output Cores/Instance Precision Compute Type Group Size Next Token(ms) Memory mean used (Top 50%) MB First Token(ms) Total Latency(ms) P90 Latency(ms) P99 Latency(ms)
LLM Runtime 32 32 32 INT4 INT8 128 26.85 2868 175.2 1007 27.12 129.3
LLM Runtime 32 32 48 INT4 INT8 128 26.78 2868 172.1 1002 26.95 127.2
LLM Runtime 32 32 56 INT4 INT8 128 28.31 2763 173.05 1050 28.53 128.7
LLM Runtime 32 32 32 INT4 INT8 32 27.8 2868 200.74 1062 28.2 147.4
LLM Runtime 32 32 48 INT4 INT8 32 27.97 2896 193.84 1060 28.12 142.9
LLM Runtime 32 32 56 INT4 INT8 32 29.16 2876 195.67 1099 29.31 144.7
GGML 32 32 32 INT4 INT8 32 26.57 2868 368.5 1192 26.74 262.1
GGML 32 32 48 INT4 INT8 32 26.5 2842 310.5 1132 26.67 222.3
GGML 32 32 56 INT4 INT8 32 27.17 2825 293.92 1136 27.28 211.2

LLM Finetuning

Environments:

PyTorch: 2.0.1+cpu

Framework Hidden Size Dataset (Alpaca) Concatenation Nodes PPN Precision LoRA LoRA rank/alpha Epoches Time/Epoch Total Time TruthfulQA (mc1/mc2) Global Batch Size Learning Rate
PyTorch 4096 13K Yes 1 1 BF16 Yes 8/16 3 3.2 Hour 9.6 Hours 0.30/0.45 128 1.00E-04
PyTorch 4096 13K Yes 2 2 BF16 Yes 8/16 3 1.2 Hour 3.6 Hours 0.30/0.45 128 1.00E-04
PyTorch 4096 13K Yes 4 2 BF16 Yes 8/16 3 0.67 Hour 2 Hours 0.30/0.45 128 1.00E-04

Intel Gaudi2 Environments:

Driver version 1.13.0-ee32e42, synapse AI v1.13.0

We will release data soon.