Oracle Cloud Infrastructure Documentation

Scenario 3: Generation Heavy Benchmarks in Generative AI

The generation heavy scenario is for generation / model response heavy use cases. For example, a long job description generated from a short bullet list of items.

The generation heavy scenario is performed with the following token lengths:

  • The prompt length is fixed to 100 tokens
  • The response length is fixed to 1,000 tokens
Important

The performance (inference speed, throughput, latency) of a hosting dedicated AI cluster depends on the traffic scenarios going through the model that it's hosting. Traffic scenarios depend on:

  1. The number of concurrent requests.
  2. The number of tokens in the prompt.
  3. The number of tokens in the response.
  4. The variance of (2) and (3) across requests.

Review the terms used in the hosting dedicated AI cluster benchmarks. For a list of scenarios and their descriptions, see Chat and Text Generation Scenarios. The generation heavy scenario is performed in the following region.

Brazil East (Sao Paulo)

Model: cohere.command-r-08-2024 (Cohere Command R 08-2024) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 147.84 148.54 8.18 7.25
2 146.96 292.45 10.59 11.16
4 139.14 520.57 8.46 26.20
8 128.71 923.73 9.73 43.55
16 122.33 1,631.48 10.76 73.30
32 114.14 2,586.64 12.99 102.60
64 95.98 4,124.24 13.42 186.47
128 69.06 6,366.06 19.24 285.92
256 40.02 6,973.92 35.71 305.09
Model: cohere.command-r-plus-08-2024 (Cohere Command R+ 08-2024) model hosted on one Large Cohere V2_2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 132.10 131.90 16.12 3.70
2 130.10 256.33 15.61 7.62
4 125.23 495.22 17.36 13.61
8 111.15 832.88 18.74 23.87
16 104.75 1,375.51 21.45 36.61
32 100.82 2,974.72 21.65 81.76
64 79.67 4,635.15 26.36 131.98
128 60.49 6,290.61 37.0 171.76
256 31.69 7,010.75 62.48 196.58
Model: meta.llama-3.3-70b-instruct (Meta Llama 3.3 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 53.55 53.21 18.70 3.19
2 52.83 103.10 18.97 6.19
4 53.40 206.18 18.77 12.37
8 53.25 412.36 18.85 24.74
16 51.53 812.24 19.48 48.73
32 45.99 1,447.02 21.861 86.82
64 45.99 2,599.88 23.81 156.00
128 34.76 4,216.35 29.32 252.98
256 23.72 3,826.77 44.02 229.61
Model: meta.llama-3.2-90b-vision-instruct (Meta Llama 3.2 90B Vision) model (text input only) hosted on one Large Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 49.15 48.33 20.37 2.90
2 48.73 96.67 20.57 2.90
4 48.17 186.67 20.85 11.20
8 47.53 373.33 21.20 22.40
16 46.69 720.00 21.75 43.20
32 41.65 1,279.99 24.54 76.80
64 41.92 1,279.98 47.75 76.80
128 41.93 1,279.96 91.49 76.80
256 41.88 1,279.93 166.93 76.80
Model: meta.llama-3.2-11b-vision-instruct (Meta Llama 3.2 11B Vision) model (text input only) hosted on one Small Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 106.36 105.00 9.41 6.30
2 104.89 206.67 9.55 12.40
4 101.93 400.00 9.84 24.00
8 98.89 773.33 10.17 46.40
16 91.20 1,439.99 11.07 86.40
32 72.13 2,239.98 14.03 134.40
64 72.29 2,293.30 27.49 137.60
128 72.30 2,239.89 53.75 134.39
256 72.27 2,239.84 102.37 134.39
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 2 unit of a dedicated AI cluster
Important

You can host the meta.llama-3.1-405b-instruct model only on a dedicated AI cluster of type Large Generic 2. This type in intended to provide better throughput with less hardware and a lower cost than its predecessor, Large Generic 4.

The following tables provide benchmarks that were performed for the meta.llama-3.1-405b-instruct model hosted on one Large Generic 2 unit and on one Large Generic 4 unit. If your model is currently hosted on a Large Generic 4 unit, compare the following tables to decide whether to host the model on this new unit.

Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 27.35 26.65 36.65 1.60
2 26.72 49.97 37.53 3.00
4 26.21 99.94 38.27 6.00
8 26.42 199.89 38.00 11.99
16 22.60 346.45 44.45 20.79
32 21.97 692.91 45.77 41.57
64 20.10 1,177.63 50.14 70.66
128 17.06 2,086.85 60.70 125.21
256 11.05 2,024.72 109.59 121.48
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 4 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 31.28 26.55 18.50 3.24
2 30.79 50.88 16.14 7.12
4 29.46 93.36 18.15 12.09
8 28.20 170.20 19.40 21.40
16 26.37 271.80 17.73 40.56
32 25.24 419.13 21.06 55.06
64 22.19 755.43 24.38 98.29
128 17.43 1,248.19 29.45 168.00
256 11.27 1,794.88 44.85 236.65
Model: meta.llama-3.1-70b-instruct (Meta Llama 3.1 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 95.37 52.01 19.56 3.07
2 92.77 101.29 20.04 5.98
4 91.60 191.83 20.34 11.32
8 86.83 338.87 21.51 19.97
16 78.12 547.34 23.92 32.23
32 64.77 1,111.24 28.91 65.46
64 50.52 1,722.11 37.23 101.48
128 31.29 2,123.49 60.17 125.12
256 14.93 2,002.12 126.87 117.98
Model: meta.llama-3-70b-instruct (Meta Llama 3) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 50.18 50.14 20.43 2.94
2 49.28 97.61 20.78 5.72
4 48.22 186.82 21.32 10.94
8 47.20 365.89 21.75 21.43
16 44.69 650.22 22.89 38.03
32 37.29 989.98 27.31 58.04
64 29.53 1621.76 32.68 95.08
128 19.17 1784.76 53.14 104.56
256 10.79 2271.18 94.78 133.05
Model: cohere.command-r-16k (Cohere Command R) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 47.20 50.32 3.53 16.65
2 45.06 98.42 3.61 32.48
4 43.85 165.60 3.26 63.91
8 40.56 292.22 3.04 133.20
16 38.35 416.13 3.61 171.22
32 28.68 557.5 4.64 219.01
64 15.19 613.72 9.65 171.83
128 10.74 664.11 11.67 233.87
256 5.83 721.50 22.78 253.54
Model: cohere.command-r-plus (Cohere Command R+) model hosted on one Large Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 126.40 110.90 13.07 4.57
2 122.93 213.92 13.33 8.87
4 117.03 403.27 15.32 15.26
8 106.11 707.45 16.86 26.78
16 98.06 1,258.94 18.22 47.94
32 86.74 2,147.82 21.04 79.38
64 72.43 3,011.59 25.50 107.48
128 55.80 5,058.49 32.38 191.22
256 36.56 5,025.93 52.34 189.68

Germany Central (Frankfurt)

Model: cohere.command-r-08-2024 (Cohere Command R 08-2024) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 147.84 148.54 8.18 7.25
2 146.96 292.45 10.59 11.16
4 139.14 520.57 8.46 26.20
8 128.71 923.73 9.73 43.55
16 122.33 1,631.48 10.76 73.30
32 114.14 2,586.64 12.99 102.60
64 95.98 4,124.24 13.42 186.47
128 69.06 6,366.06 19.24 285.92
256 40.02 6,973.92 35.71 305.09
Model: cohere.command-r-plus-08-2024 (Cohere Command R+ 08-2024) model hosted on one Large Cohere V2_2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 132.10 131.90 16.12 3.70
2 130.10 256.33 15.61 7.62
4 125.23 495.22 17.36 13.61
8 111.15 832.88 18.74 23.87
16 104.75 1,375.51 21.45 36.61
32 100.82 2,974.72 21.65 81.76
64 79.67 4,635.15 26.36 131.98
128 60.49 6,290.61 37.0 171.76
256 31.69 7,010.75 62.48 196.58
Model: meta.llama-3.3-70b-instruct (Meta Llama 3.3 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 53.55 53.21 18.70 3.19
2 52.83 103.10 18.97 6.19
4 53.40 206.18 18.77 12.37
8 53.25 412.36 18.85 24.74
16 51.53 812.24 19.48 48.73
32 45.99 1,447.02 21.861 86.82
64 45.99 2,599.88 23.81 156.00
128 34.76 4,216.35 29.32 252.98
256 23.72 3,826.77 44.02 229.61
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 2 unit of a dedicated AI cluster
Important

You can host the meta.llama-3.1-405b-instruct model only on a dedicated AI cluster of type Large Generic 2. This type in intended to provide better throughput with less hardware and a lower cost than its predecessor, Large Generic 4.

The following tables provide benchmarks that were performed for the meta.llama-3.1-405b-instruct model hosted on one Large Generic 2 unit and on one Large Generic 4 unit. If your model is currently hosted on a Large Generic 4 unit, compare the following tables to decide whether to host the model on this new unit.

Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 27.35 26.65 36.65 1.60
2 26.72 49.97 37.53 3.00
4 26.21 99.94 38.27 6.00
8 26.42 199.89 38.00 11.99
16 22.60 346.45 44.45 20.79
32 21.97 692.91 45.77 41.57
64 20.10 1,177.63 50.14 70.66
128 17.06 2,086.85 60.70 125.21
256 11.05 2,024.72 109.59 121.48
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 4 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 31.28 26.55 18.50 3.24
2 30.79 50.88 16.14 7.12
4 29.46 93.36 18.15 12.09
8 28.20 170.20 19.40 21.40
16 26.37 271.80 17.73 40.56
32 25.24 419.13 21.06 55.06
64 22.19 755.43 24.38 98.29
128 17.43 1,248.19 29.45 168.00
256 11.27 1,794.88 44.85 236.65
Model: meta.llama-3.1-70b-instruct (Meta Llama 3.1 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 95.37 52.01 19.56 3.07
2 92.77 101.29 20.04 5.98
4 91.60 191.83 20.34 11.32
8 86.83 338.87 21.51 19.97
16 78.12 547.34 23.92 32.23
32 64.77 1,111.24 28.91 65.46
64 50.52 1,722.11 37.23 101.48
128 31.29 2,123.49 60.17 125.12
256 14.93 2,002.12 126.87 117.98
Model: meta.llama-3-70b-instruct (Meta Llama 3) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 50.18 50.14 20.43 2.94
2 49.28 97.61 20.78 5.72
4 48.22 186.82 21.32 10.94
8 47.20 365.89 21.75 21.43
16 44.69 650.22 22.89 38.03
32 37.29 989.98 27.31 58.04
64 29.53 1621.76 32.68 95.08
128 19.17 1784.76 53.14 104.56
256 10.79 2271.18 94.78 133.05
Model: cohere.command-r-16k (Cohere Command R) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 47.20 50.32 3.53 16.65
2 45.06 98.42 3.61 32.48
4 43.85 165.60 3.26 63.91
8 40.56 292.22 3.04 133.20
16 38.35 416.13 3.61 171.22
32 28.68 557.5 4.64 219.01
64 15.19 613.72 9.65 171.83
128 10.74 664.11 11.67 233.87
256 5.83 721.50 22.78 253.54
Model: cohere.command-r-plus (Cohere Command R+) model hosted on one Large Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 126.40 110.90 13.07 4.57
2 122.93 213.92 13.33 8.87
4 117.03 403.27 15.32 15.26
8 106.11 707.45 16.86 26.78
16 98.06 1,258.94 18.22 47.94
32 86.74 2,147.82 21.04 79.38
64 72.43 3,011.59 25.50 107.48
128 55.80 5,058.49 32.38 191.22
256 36.56 5,025.93 52.34 189.68

Japan Central (Osaka)

Model: cohere.command-r-08-2024 (Cohere Command R 08-2024) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 147.84 148.54 8.18 7.25
2 146.96 292.45 10.59 11.16
4 139.14 520.57 8.46 26.20
8 128.71 923.73 9.73 43.55
16 122.33 1,631.48 10.76 73.30
32 114.14 2,586.64 12.99 102.60
64 95.98 4,124.24 13.42 186.47
128 69.06 6,366.06 19.24 285.92
256 40.02 6,973.92 35.71 305.09
Model: cohere.command-r-plus-08-2024 (Cohere Command R+ 08-2024) model hosted on one Large Cohere V2_2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 132.10 131.90 16.12 3.70
2 130.10 256.33 15.61 7.62
4 125.23 495.22 17.36 13.61
8 111.15 832.88 18.74 23.87
16 104.75 1,375.51 21.45 36.61
32 100.82 2,974.72 21.65 81.76
64 79.67 4,635.15 26.36 131.98
128 60.49 6,290.61 37.0 171.76
256 31.69 7,010.75 62.48 196.58
Model: meta.llama-3.3-70b-instruct (Meta Llama 3.3 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 53.55 53.21 18.70 3.19
2 52.83 103.10 18.97 6.19
4 53.40 206.18 18.77 12.37
8 53.25 412.36 18.85 24.74
16 51.53 812.24 19.48 48.73
32 45.99 1,447.02 21.861 86.82
64 45.99 2,599.88 23.81 156.00
128 34.76 4,216.35 29.32 252.98
256 23.72 3,826.77 44.02 229.61
Model: meta.llama-3.2-90b-vision-instruct (Meta Llama 3.2 90B Vision) model (text input only) hosted on one Large Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 49.15 48.33 20.37 2.90
2 48.73 96.67 20.57 2.90
4 48.17 186.67 20.85 11.20
8 47.53 373.33 21.20 22.40
16 46.69 720.00 21.75 43.20
32 41.65 1,279.99 24.54 76.80
64 41.92 1,279.98 47.75 76.80
128 41.93 1,279.96 91.49 76.80
256 41.88 1,279.93 166.93 76.80
Model: meta.llama-3.2-11b-vision-instruct (Meta Llama 3.2 11B Vision) model (text input only) hosted on one Small Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 106.36 105.00 9.41 6.30
2 104.89 206.67 9.55 12.40
4 101.93 400.00 9.84 24.00
8 98.89 773.33 10.17 46.40
16 91.20 1,439.99 11.07 86.40
32 72.13 2,239.98 14.03 134.40
64 72.29 2,293.30 27.49 137.60
128 72.30 2,239.89 53.75 134.39
256 72.27 2,239.84 102.37 134.39
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 2 unit of a dedicated AI cluster
Important

You can host the meta.llama-3.1-405b-instruct model only on a dedicated AI cluster of type Large Generic 2. This type in intended to provide better throughput with less hardware and a lower cost than its predecessor, Large Generic 4.

The following tables provide benchmarks that were performed for the meta.llama-3.1-405b-instruct model hosted on one Large Generic 2 unit and on one Large Generic 4 unit. If your model is currently hosted on a Large Generic 4 unit, compare the following tables to decide whether to host the model on this new unit.

Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 27.35 26.65 36.65 1.60
2 26.72 49.97 37.53 3.00
4 26.21 99.94 38.27 6.00
8 26.42 199.89 38.00 11.99
16 22.60 346.45 44.45 20.79
32 21.97 692.91 45.77 41.57
64 20.10 1,177.63 50.14 70.66
128 17.06 2,086.85 60.70 125.21
256 11.05 2,024.72 109.59 121.48
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 4 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 31.28 26.55 18.50 3.24
2 30.79 50.88 16.14 7.12
4 29.46 93.36 18.15 12.09
8 28.20 170.20 19.40 21.40
16 26.37 271.80 17.73 40.56
32 25.24 419.13 21.06 55.06
64 22.19 755.43 24.38 98.29
128 17.43 1,248.19 29.45 168.00
256 11.27 1,794.88 44.85 236.65
Model: meta.llama-3.1-70b-instruct (Meta Llama 3.1 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 95.37 52.01 19.56 3.07
2 92.77 101.29 20.04 5.98
4 91.60 191.83 20.34 11.32
8 86.83 338.87 21.51 19.97
16 78.12 547.34 23.92 32.23
32 64.77 1,111.24 28.91 65.46
64 50.52 1,722.11 37.23 101.48
128 31.29 2,123.49 60.17 125.12
256 14.93 2,002.12 126.87 117.98
Model: cohere.command-r-16k (Cohere Command R) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 47.20 50.32 3.53 16.65
2 45.06 98.42 3.61 32.48
4 43.85 165.60 3.26 63.91
8 40.56 292.22 3.04 133.20
16 38.35 416.13 3.61 171.22
32 28.68 557.5 4.64 219.01
64 15.19 613.72 9.65 171.83
128 10.74 664.11 11.67 233.87
256 5.83 721.50 22.78 253.54
Model: cohere.command-r-plus (Cohere Command R+) model hosted on one Large Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 126.40 110.90 13.07 4.57
2 122.93 213.92 13.33 8.87
4 117.03 403.27 15.32 15.26
8 106.11 707.45 16.86 26.78
16 98.06 1,258.94 18.22 47.94
32 86.74 2,147.82 21.04 79.38
64 72.43 3,011.59 25.50 107.48
128 55.80 5,058.49 32.38 191.22
256 36.56 5,025.93 52.34 189.68

UK South (London)

Model: cohere.command-r-08-2024 (Cohere Command R 08-2024) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 147.84 148.54 8.18 7.25
2 146.96 292.45 10.59 11.16
4 139.14 520.57 8.46 26.20
8 128.71 923.73 9.73 43.55
16 122.33 1,631.48 10.76 73.30
32 114.14 2,586.64 12.99 102.60
64 95.98 4,124.24 13.42 186.47
128 69.06 6,366.06 19.24 285.92
256 40.02 6,973.92 35.71 305.09
Model: cohere.command-r-plus-08-2024 (Cohere Command R+ 08-2024) model hosted on one Large Cohere V2_2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 132.10 131.90 16.12 3.70
2 130.10 256.33 15.61 7.62
4 125.23 495.22 17.36 13.61
8 111.15 832.88 18.74 23.87
16 104.75 1,375.51 21.45 36.61
32 100.82 2,974.72 21.65 81.76
64 79.67 4,635.15 26.36 131.98
128 60.49 6,290.61 37.0 171.76
256 31.69 7,010.75 62.48 196.58
Model: meta.llama-3.3-70b-instruct (Meta Llama 3.3 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 53.55 53.21 18.70 3.19
2 52.83 103.10 18.97 6.19
4 53.40 206.18 18.77 12.37
8 53.25 412.36 18.85 24.74
16 51.53 812.24 19.48 48.73
32 45.99 1,447.02 21.861 86.82
64 45.99 2,599.88 23.81 156.00
128 34.76 4,216.35 29.32 252.98
256 23.72 3,826.77 44.02 229.61
Model: meta.llama-3.2-90b-vision-instruct (Meta Llama 3.2 90B Vision) model (text input only) hosted on one Large Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 49.15 48.33 20.37 2.90
2 48.73 96.67 20.57 2.90
4 48.17 186.67 20.85 11.20
8 47.53 373.33 21.20 22.40
16 46.69 720.00 21.75 43.20
32 41.65 1,279.99 24.54 76.80
64 41.92 1,279.98 47.75 76.80
128 41.93 1,279.96 91.49 76.80
256 41.88 1,279.93 166.93 76.80
Model: meta.llama-3.2-11b-vision-instruct (Meta Llama 3.2 11B Vision) model (text input only) hosted on one Small Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 106.36 105.00 9.41 6.30
2 104.89 206.67 9.55 12.40
4 101.93 400.00 9.84 24.00
8 98.89 773.33 10.17 46.40
16 91.20 1,439.99 11.07 86.40
32 72.13 2,239.98 14.03 134.40
64 72.29 2,293.30 27.49 137.60
128 72.30 2,239.89 53.75 134.39
256 72.27 2,239.84 102.37 134.39
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 2 unit of a dedicated AI cluster
Important

You can host the meta.llama-3.1-405b-instruct model only on a dedicated AI cluster of type Large Generic 2. This type in intended to provide better throughput with less hardware and a lower cost than its predecessor, Large Generic 4.

The following tables provide benchmarks that were performed for the meta.llama-3.1-405b-instruct model hosted on one Large Generic 2 unit and on one Large Generic 4 unit. If your model is currently hosted on a Large Generic 4 unit, compare the following tables to decide whether to host the model on this new unit.

Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 27.35 26.65 36.65 1.60
2 26.72 49.97 37.53 3.00
4 26.21 99.94 38.27 6.00
8 26.42 199.89 38.00 11.99
16 22.60 346.45 44.45 20.79
32 21.97 692.91 45.77 41.57
64 20.10 1,177.63 50.14 70.66
128 17.06 2,086.85 60.70 125.21
256 11.05 2,024.72 109.59 121.48
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 4 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 31.28 26.55 18.50 3.24
2 30.79 50.88 16.14 7.12
4 29.46 93.36 18.15 12.09
8 28.20 170.20 19.40 21.40
16 26.37 271.80 17.73 40.56
32 25.24 419.13 21.06 55.06
64 22.19 755.43 24.38 98.29
128 17.43 1,248.19 29.45 168.00
256 11.27 1,794.88 44.85 236.65
Model: meta.llama-3.1-70b-instruct (Meta Llama 3.1 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 95.37 52.01 19.56 3.07
2 92.77 101.29 20.04 5.98
4 91.60 191.83 20.34 11.32
8 86.83 338.87 21.51 19.97
16 78.12 547.34 23.92 32.23
32 64.77 1,111.24 28.91 65.46
64 50.52 1,722.11 37.23 101.48
128 31.29 2,123.49 60.17 125.12
256 14.93 2,002.12 126.87 117.98
Model: meta.llama-3-70b-instruct (Meta Llama 3) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 50.18 50.14 20.43 2.94
2 49.28 97.61 20.78 5.72
4 48.22 186.82 21.32 10.94
8 47.20 365.89 21.75 21.43
16 44.69 650.22 22.89 38.03
32 37.29 989.98 27.31 58.04
64 29.53 1621.76 32.68 95.08
128 19.17 1784.76 53.14 104.56
256 10.79 2271.18 94.78 133.05
Model: cohere.command-r-16k (Cohere Command R) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 47.20 50.32 3.53 16.65
2 45.06 98.42 3.61 32.48
4 43.85 165.60 3.26 63.91
8 40.56 292.22 3.04 133.20
16 38.35 416.13 3.61 171.22
32 28.68 557.5 4.64 219.01
64 15.19 613.72 9.65 171.83
128 10.74 664.11 11.67 233.87
256 5.83 721.50 22.78 253.54
Model: cohere.command-r-plus (Cohere Command R+) model hosted on one Large Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 126.40 110.90 13.07 4.57
2 122.93 213.92 13.33 8.87
4 117.03 403.27 15.32 15.26
8 106.11 707.45 16.86 26.78
16 98.06 1,258.94 18.22 47.94
32 86.74 2,147.82 21.04 79.38
64 72.43 3,011.59 25.50 107.48
128 55.80 5,058.49 32.38 191.22
256 36.56 5,025.93 52.34 189.68

US Midwest (Chicago)

Model: cohere.command-r-08-2024 (Cohere Command R 08-2024) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 147.84 148.54 8.18 7.25
2 146.96 292.45 10.59 11.16
4 139.14 520.57 8.46 26.20
8 128.71 923.73 9.73 43.55
16 122.33 1,631.48 10.76 73.30
32 114.14 2,586.64 12.99 102.60
64 95.98 4,124.24 13.42 186.47
128 69.06 6,366.06 19.24 285.92
256 40.02 6,973.92 35.71 305.09
Model: cohere.command-r-plus-08-2024 (Cohere Command R+ 08-2024) model hosted on one Large Cohere V2_2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 132.10 131.90 16.12 3.70
2 130.10 256.33 15.61 7.62
4 125.23 495.22 17.36 13.61
8 111.15 832.88 18.74 23.87
16 104.75 1,375.51 21.45 36.61
32 100.82 2,974.72 21.65 81.76
64 79.67 4,635.15 26.36 131.98
128 60.49 6,290.61 37.0 171.76
256 31.69 7,010.75 62.48 196.58
Model: meta.llama-3.3-70b-instruct (Meta Llama 3.3 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 53.55 53.21 18.70 3.19
2 52.83 103.10 18.97 6.19
4 53.40 206.18 18.77 12.37
8 53.25 412.36 18.85 24.74
16 51.53 812.24 19.48 48.73
32 45.99 1,447.02 21.861 86.82
64 45.99 2,599.88 23.81 156.00
128 34.76 4,216.35 29.32 252.98
256 23.72 3,826.77 44.02 229.61
Model: meta.llama-3.2-90b-vision-instruct (Meta Llama 3.2 90B Vision) model (text input only) hosted on one Large Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 49.15 48.33 20.37 2.90
2 48.73 96.67 20.57 2.90
4 48.17 186.67 20.85 11.20
8 47.53 373.33 21.20 22.40
16 46.69 720.00 21.75 43.20
32 41.65 1,279.99 24.54 76.80
64 41.92 1,279.98 47.75 76.80
128 41.93 1,279.96 91.49 76.80
256 41.88 1,279.93 166.93 76.80
Model: meta.llama-3.2-11b-vision-instruct (Meta Llama 3.2 11B Vision) model (text input only) hosted on one Small Generic V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 106.36 105.00 9.41 6.30
2 104.89 206.67 9.55 12.40
4 101.93 400.00 9.84 24.00
8 98.89 773.33 10.17 46.40
16 91.20 1,439.99 11.07 86.40
32 72.13 2,239.98 14.03 134.40
64 72.29 2,293.30 27.49 137.60
128 72.30 2,239.89 53.75 134.39
256 72.27 2,239.84 102.37 134.39
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 2 unit of a dedicated AI cluster
Important

You can host the meta.llama-3.1-405b-instruct model only on a dedicated AI cluster of type Large Generic 2. This type in intended to provide better throughput with less hardware and a lower cost than its predecessor, Large Generic 4.

The following tables provide benchmarks that were performed for the meta.llama-3.1-405b-instruct model hosted on one Large Generic 2 unit and on one Large Generic 4 unit. If your model is currently hosted on a Large Generic 4 unit, compare the following tables to decide whether to host the model on this new unit.

Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 27.35 26.65 36.65 1.60
2 26.72 49.97 37.53 3.00
4 26.21 99.94 38.27 6.00
8 26.42 199.89 38.00 11.99
16 22.60 346.45 44.45 20.79
32 21.97 692.91 45.77 41.57
64 20.10 1,177.63 50.14 70.66
128 17.06 2,086.85 60.70 125.21
256 11.05 2,024.72 109.59 121.48
Model: meta.llama-3.1-405b-instruct (Meta Llama 3.1 (405B)) model hosted on one Large Generic 4 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 31.28 26.55 18.50 3.24
2 30.79 50.88 16.14 7.12
4 29.46 93.36 18.15 12.09
8 28.20 170.20 19.40 21.40
16 26.37 271.80 17.73 40.56
32 25.24 419.13 21.06 55.06
64 22.19 755.43 24.38 98.29
128 17.43 1,248.19 29.45 168.00
256 11.27 1,794.88 44.85 236.65
Model: meta.llama-3.1-70b-instruct (Meta Llama 3.1 (70B)) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 95.37 52.01 19.56 3.07
2 92.77 101.29 20.04 5.98
4 91.60 191.83 20.34 11.32
8 86.83 338.87 21.51 19.97
16 78.12 547.34 23.92 32.23
32 64.77 1,111.24 28.91 65.46
64 50.52 1,722.11 37.23 101.48
128 31.29 2,123.49 60.17 125.12
256 14.93 2,002.12 126.87 117.98
Model: meta.llama-3-70b-instruct (Meta Llama 3) model hosted on one Large Generic unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 30.53 30.51 33.58 1.79
2 29.78 59.01 34.42 3.45
4 28.88 112.35 35.48 6.58
8 27.67 215.18 36.99 12.61
16 24.85 364.06 40.99 21.34
32 20.51 552.34 49.60 32.35
64 16.12 900.39 59.36 52.72
128 10.17 980.45 100.27 57.43
256 6.30 1334.59 162.08 78.19
Model: cohere.command-r-16k (Cohere Command R) model hosted on one Small Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 47.20 50.32 3.53 16.65
2 45.06 98.42 3.61 32.48
4 43.85 165.60 3.26 63.91
8 40.56 292.22 3.04 133.20
16 38.35 416.13 3.61 171.22
32 28.68 557.5 4.64 219.01
64 15.19 613.72 9.65 171.83
128 10.74 664.11 11.67 233.87
256 5.83 721.50 22.78 253.54
Model: cohere.command-r-plus (Cohere Command R+) model hosted on one Large Cohere V2 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 126.40 110.90 13.07 4.57
2 122.93 213.92 13.33 8.87
4 117.03 403.27 15.32 15.26
8 106.11 707.45 16.86 26.78
16 98.06 1,258.94 18.22 47.94
32 86.74 2,147.82 21.04 79.38
64 72.43 3,011.59 25.50 107.48
128 55.80 5,058.49 32.38 191.22
256 36.56 5,025.93 52.34 189.68
Model: cohere.command (Cohere Command 52 B) model hosted on one Large Cohere unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 35.78 33.43 10.98 5.33
8 31.41 99.67 13.87 16.61
32 28.49 237.1 19.48 40.24
128 23.01 326.93 53.13 54.89
Model: cohere.command-light (Cohere Command Light 6 B) model hosted on one Small Cohere unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 80.38 83.61 9.19 6.34
8 45.96 278.91 13.89 22.46
32 23.90 493.78 27.34 41.13
128 5.12 565.06 82.15 44.89
Model: meta.llama-2-70b-chat (Llama2 70 B) model hosted on one Llama2 70 unit of a dedicated AI cluster
Concurrency Token-level Inference Speed (token/second) Token-level Throughput (token/second) Request-level Latency (second) Request-level Throughput (Request per minute) (RPM)
1 18.12 17.58 21.44 2.72
8 15.96 64.28 26.83 8.91
32 13.72 195.48 29.43 27.99
128 8.61 541.75 48.50 71.52