Model
string | Size
string | Precision
string | GPU_Type
string | Num_GPUs
int64 | Serving_Engine
string | Concurrency
int64 | Tokens_per_sec
float64 | TTFT_ms
float64 | TPOT_ms
float64 | Prompt_Tokens
int64 | Output_Tokens
int64 | Context_Window
int64 | Quantization
string | Source_URL
string | Source_Notes
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
DeepSeek-R1-Distill-Qwen
|
7B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 3,362.71
| 309.36
| 14.96
| null | null | 8,192
| null | null |
DeepSeek distill vLLM test on A100; concurrency=50
|
DeepSeek-R1-Distill-Qwen
|
14B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 3,003.57
| 579.43
| 25.31
| null | null | 8,192
| null | null |
DeepSeek distill vLLM test on A100; concurrency=50
|
DeepSeek-R1-Distill-Qwen
|
32B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 577.17
| 1,299.31
| 52.65
| null | null | 8,192
| null | null |
DeepSeek distill vLLM test on A100; concurrency=50
|
QwQ (Qwen preview)
|
32B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 615.31
| 1,301.37
| 59.92
| null | null | 8,192
| null | null |
QwQ preview on vLLM; concurrency=50
|
Gemma-2
|
9B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 1,868.44
| 405.48
| 71.98
| null | null | 8,192
| null | null |
Gemma-2 9B vLLM; concurrency=50
|
Gemma-2
|
27B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 495.93
| 1,109.74
| 45.87
| null | null | 8,192
| null | null |
Gemma-2 27B vLLM; concurrency=50
|
DeepSeek-R1-Distill-Llama
|
8B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 50
| 3,003.57
| 327.75
| 17.88
| null | null | 8,192
| null | null |
DeepSeek distill Llama-8B vLLM; concurrency=50
|
Llama-3.1
|
8B
|
FP8
|
NVIDIA B200
| 8
|
vLLM
| null | 128,794
| null | null | null | null | null | null | null |
MLPerf-style server aggregate; engine vLLM. [1] indicates 8xB200 hits ~160k tok/s.
|
Llama-3.1
|
8B
|
FP8
|
NVIDIA H200
| 8
|
vLLM
| null | 64,915
| null | null | null | null | null | null | null |
MLPerf-style server aggregate; engine vLLM. [1] indicates 8xH200 hits ~140k tok/s.
|
Llama-3.1
|
70B
|
BF16
|
Intel Gaudi 3
| 8
|
vLLM
| null | 21,264
| null | null | null | null | null | null | null |
Intel/third-party measurement; open weights
|
Llama-3.1
|
70B
|
BF16
|
NVIDIA H200
| 8
|
SGLang
| 10
| null | 7.292
| 0.042
| 4,096
| 256
| null | null |
[2]
|
VMware benchmark; E2E Latency 18ms. TPOT is extremely low.
|
Llama-3.1
|
70B
|
BF16
|
AMD MI300X
| 8
|
vLLM
| null | null | null | null | null | null | null | null |
[3]
|
1.8x higher throughput and 5.1x faster TTFT than TGI at 32 QPS.
|
Llama-3.1
|
70B
|
FP8
|
NVIDIA B200
| 8
|
vLLM
| null | null | null | null | null | null | null | null | null |
Target row; populate once B200 MLPerf v5.1+ data is available.
|
Llama-3.1
|
405B
|
FP8
|
NVIDIA H100
| 8
|
vLLM
| null | 291.5
| null | null | null | null | null | null | null |
Approx aggregate tok/s reported; low concurrency.
|
Llama-3.1
|
405B
|
FP8
|
AMD MI300X
| 8
|
vLLM (ROCm)
| 256
| 1,846
| null | 138.67
| 128
| 128
| null | null |
[4]
|
Per-token latency 17.75s E2E. (17750ms / 128 tokens = 138.67ms TPOT).
|
Qwen-2.5
|
7B
|
BF16
|
NVIDIA L40S
| 1
|
vLLM
| 32
| null | null | null | null | null | null |
AWQ
|
[5]
|
Target row. Source [5] inaccessible.
|
Qwen-2.5
|
14B
|
BF16
|
NVIDIA L40S
| 1
|
vLLM
| 32
| null | null | null | null | null | null |
AWQ
|
[5]
|
Target row. Source [5] inaccessible.
|
Qwen-2.5
|
32B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 64
| null | null | null | null | null | null |
AWQ
|
[5]
|
Target row. Source [5] inaccessible.
|
Qwen-2.5
|
72B
|
BF16
|
NVIDIA H100
| 8
|
SGLang
| 128
| null | null | null | null | null | null | null |
[6]
|
Target row. Source [6] confirms vLLM/SGLang tests on 8xH100 but provides no hard numbers.
|
Qwen-3
|
14B
|
BF16
|
NVIDIA H200
| 1
|
vLLM
| 64
| null | null | null | null | null | null |
AWQ
| null |
Target row for 2025 posts with concurrency curves.
|
Qwen-3
|
32B
|
BF16
|
NVIDIA H200
| 4
|
vLLM
| 128
| null | null | null | null | null | null |
AWQ
| null |
Target row for 2025 posts with concurrency curves.
|
Qwen-3
|
72B
|
BF16
|
NVIDIA B200
| 8
|
SGLang
| 128
| null | null | null | null | null | null | null | null |
Target row; large-model serving.
|
Qwen-3
|
110B
|
BF16
|
AMD MI300X
| 8
|
vLLM (ROCm)
| 128
| null | null | null | null | null | null | null |
[7]
|
Target row; populate from ROCm case studies. Source [7] confirms support but gives no metrics.
|
Qwen-3
|
235B
|
BF16
|
Intel Gaudi 3
| 8
|
SGLang
| 64
| null | null | null | null | null | null | null |
[8]
|
Target row; [8] reference this but provide no data.
|
Qwen-3
|
235B
|
BF16
|
NVIDIA H200
| 4
|
SGLang
| 32
| null | null | null | 1,000
| 1,000
| null |
FP8
|
[9]
|
SGLang benchmark on H200 (proxy for B200). 45 tok/s *per user*. 1400 tok/s *total*.
|
DeepSeek-V3-Base
|
37B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 32
| null | null | null | null | null | null | null |
[10]
|
Target row. [10] confirms 671B total / 37B active params.
|
DeepSeek-V3
|
37B
|
BF16
|
NVIDIA H100
| 4
|
SGLang
| 128
| null | null | null | null | null | null | null |
[11]
|
Target row; [11, 12] confirm SGLang support and optimizations.
|
DeepSeek-R1-Distill
|
70B
|
BF16
|
NVIDIA H200
| 8
|
vLLM
| 128
| null | null | null | null | null | null | null |
[13]
|
Target row. [13] lists 8-GPU (Latency) and 4-GPU (Throughput) optimized configs.
|
DeepSeek-R1-Distill
|
70B
|
BF16
|
AMD MI355X
| 8
|
vLLM (ROCm)
| 128
| null | null | null | null | null | null | null |
[7]
|
Target row; [7] confirms platform support, no metrics provided.
|
DeepSeek-R1-Distill
|
32B
|
BF16
|
Intel Gaudi 3
| 4
|
SGLang
| 64
| null | null | null | null | null | null | null | null |
Target row.
|
Gemma-3
|
12B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 32
| 477.49
| null | null | null | null | null | null |
[14]
|
Low end of a 50-concurrency benchmark range (477-4193 tok/s).
|
Gemma-3
|
27B
|
BF16
|
NVIDIA H200
| 1
|
vLLM
| 64
| null | null | null | null | null | null | null |
[15]
|
Target row. [15] discusses benchmarking but provides no results.
|
Gemma-2
|
9B
|
BF16
|
NVIDIA L40S
| 1
|
SGLang
| 32
| null | null | null | null | null | null | null | null |
Target row.
|
Gemma-2
|
27B
|
BF16
|
Intel Gaudi 3
| 2
|
vLLM
| 32
| null | null | null | null | null | null | null |
[16]
|
Target row. [16] mentions Gaudi 2, not 3.
|
Phi-4
|
14B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 32
| 260.01
| null | null | null | null | null | null | null |
Microsoft Phi-4 speed note; [17] confirms benchmarking at 16 RPS.
|
Phi-4-mini
|
3.8B
|
FP16
|
NVIDIA A100
| 1
|
vLLM
| 64
| null | null | null | null | null | null |
INT4/FP8
|
[18]
|
Target row. [18] notes tokenizer bugs impacting vLLM use.
|
Yi-1.5
|
9B
|
FP16
|
NVIDIA H100
| 1
|
vLLM
| 32
| null | null | null | null | null | null | null | null |
Target row.
|
Yi-1.5
|
34B
|
BF16
|
NVIDIA H200
| 2
|
SGLang
| 64
| null | null | null | null | null | null | null | null |
Target row.
|
Mixtral
|
8x7B MoE
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 32
| null | null | null | null | null | null | null |
[19]
|
Target row. [19] confirms vLLM/TP/PP benchmarks exist. 2 active experts.
|
Mixtral
|
8x22B MoE
|
BF16
|
NVIDIA H200
| 8
|
SGLang
| 128
| null | null | null | null | null | null | null |
[20]
|
Target row. [20] notes MoE complexity, no hard numbers.
|
DBRX
|
132B
|
BF16
|
NVIDIA H100
| 8
|
vLLM
| 64
| null | null | null | null | null | null | null |
[21]
|
Target row. 4 active experts. [21] notes 2x+ throughput over 70B dense model at batch > 32.
|
DBRX
|
132B
|
BF16
|
AMD MI300X
| 8
|
vLLM (ROCm)
| 64
| null | null | null | null | null | null | null | null |
Target row.
|
Llama-3.2
|
3B
|
BF16
|
NVIDIA L40S
| 1
|
vLLM
| 32
| 95
| null | null | 128
| 2,048
| 131,072
| null | null |
Single-GPU L40S example.
|
Hermes-3 (Llama-3.2)
|
3B
|
BF16
|
NVIDIA RTX 4090
| 1
|
vLLM
| null | 60.69
| null | null | null | null | null | null |
[22]
|
SGLang vs vLLM benchmark. 4090 is proxy for L40S.
|
Hermes-3 (Llama-3.2)
|
3B
|
BF16
|
NVIDIA RTX 4090
| 1
|
SGLang
| null | 118.34
| null | null | null | null | null | null |
[22]
|
SGLang is ~2x faster than vLLM on this small model.
|
Llama-3.1
|
8B
|
BF16
|
Intel Gaudi 3
| 1
|
SGLang
| 32
| null | null | null | null | null | null | null |
[23]
|
Target row. [23, 24] confirm SGLang support on Gaudi 3.
|
Llama-3.1
|
8B
|
BF16
|
Intel Gaudi 3
| 1
|
vLLM
| 1,000
| 9,579.96
| null | null | null | null | null | null |
[25]
|
Added row. Total throughput at 1000 concurrent requests (27.7 QPS).
|
Llama-3.1
|
8B
|
BF16
|
AMD MI300X
| 1
|
vLLM (ROCm)
| null | 18,752
| null | null | null | null | null | null |
[1]
|
Added row. Single-GPU benchmark. Compare to H200 (25k tok/s).
|
Llama-3.1
|
70B
|
BF16
|
NVIDIA L40S
| 8
|
vLLM
| 64
| null | null | null | null | null | null | null |
[26]
|
Target row. [26] notes L40S.8x used for DBRX (132B), proving 70B is feasible.
|
Llama-3.1
|
70B
|
BF16
|
Intel Gaudi 3
| 8
|
SGLang
| 128
| null | null | null | null | null | null | null |
[27]
|
Target row. [27] confirms vLLM FP8 calibration for 70B on Gaudi.
|
Llama-3.1
|
70B
|
BF16
|
Intel Gaudi 3
| 4
|
vLLM
| 1,000
| 9,072.96
| null | null | null | null | null | null |
[25]
|
Added row. Normalized throughput (per-param basis) at 1000 requests.
|
Mistral
|
7B
|
BF16
|
Intel Gaudi 3
| 1
|
vLLM
| 1,000
| 10,382.47
| null | 38.54
| null | null | null | null |
[25]
|
Added row. 23.51 QPS. TPOT is ms per token.
|
Qwen-3-Math
|
72B
|
BF16
|
NVIDIA H200
| 8
|
vLLM
| 64
| null | null | null | null | null | null | null | null |
Target row.
|
Qwen-2.5-Coder
|
32B
|
BF16
|
NVIDIA H100
| 2
|
SGLang
| 64
| null | null | null | null | null | null | null |
[28]
|
Target row. [28] discusses training, not inference.
|
Phi-4
|
14B
|
BF16
|
Intel Gaudi 3
| 1
|
vLLM
| 32
| null | null | null | null | null | null | null |
[29]
|
Target row. [29] confirms FP8 support on Gaudi.
|
Gemma-2
|
27B
|
BF16
|
AMD MI355X
| 4
|
vLLM (ROCm)
| 64
| null | null | null | null | null | null | null |
[30]
|
Target row. [30] confirms "Paiton" optimizations for Gemma 2 27B on AMD.
|
Yi-1.5
|
34B
|
BF16
|
Intel Gaudi 3
| 4
|
SGLang
| 64
| null | null | null | null | null | null | null | null |
Target row.
|
Qwen-3
|
110B
|
BF16
|
NVIDIA B200
| 8
|
vLLM
| 128
| null | null | null | null | null | null | null | null |
Target row.
|
Qwen-3
|
235B
|
BF16
|
NVIDIA B200
| 8
|
SGLang
| 128
| null | null | null | null | null | null | null | null |
Target row.
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v0)
| 5
| 588.62
| 318
| null | null | null | null | null |
[31]
|
vLLM v0.9.0 benchmark; avg latency 16.98s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v0)
| 50
| 2,742.96
| 357
| null | null | null | null | null |
[31]
|
vLLM v0.9.0 benchmark; avg latency 26.18s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v0)
| 100
| 2,744.1
| 415
| null | null | null | null | null | null |
vLLM v0.9.0 benchmark; avg latency 26.16s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v1)
| 5
| 634.87
| 276
| null | null | null | null | null |
[31]
|
vLLM v0.9.0 (V1 sched) benchmark; avg latency 15.75s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v1)
| 50
| 3,141.16
| 348
| null | null | null | null | null |
[31]
|
vLLM v0.9.0 (V1 sched) benchmark; avg latency 22.80s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM (v1)
| 100
| 3,036.62
| 373
| null | null | null | null | null |
[31]
|
vLLM v0.9.0 (V1 sched) benchmark; avg latency 23.59s
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
SGLang
| 5
| 666.54
| 136
| null | null | null | null | null |
[31]
|
SGLang v0.4.9 benchmark; avg latency 15.00s. Note 2x better TTFT vs vLLM.
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
SGLang
| 50
| 3,077.68
| 258
| null | null | null | null | null |
[31]
|
SGLang v0.4.9 benchmark; avg latency 23.38s.
|
Llama-3.1-8B-Instruct
|
8B
|
BF16
|
NVIDIA H100
| 1
|
SGLang
| 100
| 3,088.08
| 254
| null | null | null | null | null |
[31]
|
SGLang v0.4.9 benchmark; avg latency 23.29s. Note stable TTFT.
|
Llama-3.1
|
70B
|
FP8
|
NVIDIA H100
| 2
|
vLLM
| 1
| 35
| null | null | null | null | null | null |
[32]
|
Sequential requests.
|
Llama-3.1
|
70B
|
FP8
|
NVIDIA H100
| 2
|
SGLang
| 1
| 38
| null | null | null | null | null | null |
[32]
|
Sequential requests.
|
Llama-3.1
|
70B
|
FP8
|
NVIDIA H100
| 2
|
vLLM
| null | null | null | null | null | null | null | null |
[32]
|
Concurrent requests; performance *collapses* by ~50%.
|
Llama-3.1
|
70B
|
FP8
|
NVIDIA H100
| 2
|
SGLang
| null | null | null | null | null | null | null | null |
[32]
|
Concurrent requests; performance is *stable*.
|
Llama-3.1
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| 1
| 80
| null | null | null | null | null | null |
[32]
|
Sequential requests.
|
Llama-3.1
|
8B
|
BF16
|
NVIDIA H100
| 1
|
SGLang
| 1
| 91
| null | null | null | null | null | null |
[32]
|
Sequential requests.
|
Llama-3.1
|
8B
|
BF16
|
NVIDIA H100
| 1
|
vLLM
| null | null | null | null | null | null | null | null |
[32]
|
Concurrent requests; performance *collapses* by >50%.
|
Llama-3.1
|
8B
|
BF16
|
NVIDIA H100
| 1
|
SGLang
| null | null | null | null | null | null | null | null |
[32]
|
Concurrent requests; performance is *stable*.
|
Qwen-1.5B
|
1.5B
| null | null | 1
|
vLLM
| null | 98.27
| null | null | null | null | null | null | null |
Latency 0.13s; precision and hardware not specified.
|
Qwen-1.5B
|
1.5B
| null | null | 1
|
SGLang
| null | 210.48
| null | null | null | null | null | null | null |
Latency 0.58s; precision and hardware not specified.
|
Hermes-3
| null | null | null | 1
|
vLLM
| null | 60.69
| null | null | null | null | null | null | null |
Latency 0.21s; model size, precision and hardware not specified.
|
Hermes-3
| null | null | null | 1
|
SGLang
| null | 118.34
| null | null | null | null | null | null | null |
Latency 1.03s; model size, precision and hardware not specified.
|
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