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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