| --- |
| license: apache-2.0 |
| task_categories: |
| - tabular-regression |
| language: |
| - en |
| tags: |
| - llm-inference |
| - benchmarking |
| - gpu-profiling |
| - vllm |
| - sglang |
| - agentic-workloads |
| size_categories: |
| - 100K<n<1M |
| pretty_name: AgentPerfBench |
| version: "1.0" |
| configs: |
| - config_name: trace_replay |
| data_files: |
| - split: summary |
| path: trace_replay/summary.parquet |
| - config_name: distributional |
| data_files: |
| - split: summary |
| path: distributional/summary.parquet |
| - config_name: kernels_labeled |
| data_files: |
| - split: train |
| path: kernel_profiles/kernels_labeled.parquet |
| - config_name: roofline_quadrant |
| data_files: |
| - split: train |
| path: kernel_profiles/roofline_quadrant.parquet |
| - config_name: predictions |
| data_files: |
| - split: train |
| path: predictions/serving_predictions.parquet |
| dataset_info: |
| - config_name: trace_replay |
| features: |
| - name: run_id |
| dtype: string |
| - name: model |
| dtype: string |
| - name: model_family |
| dtype: string |
| - name: hardware |
| dtype: string |
| - name: engine |
| dtype: string |
| - name: tensor_parallelism |
| dtype: int64 |
| - name: profile |
| dtype: string |
| - name: concurrency |
| dtype: int64 |
| - name: num_requests |
| dtype: int64 |
| - name: duration_s |
| dtype: float64 |
| - name: successful_requests |
| dtype: int64 |
| - name: failed_requests |
| dtype: int64 |
| - name: request_throughput |
| dtype: float64 |
| - name: input_token_throughput |
| dtype: float64 |
| - name: output_token_throughput |
| dtype: float64 |
| - name: total_token_throughput |
| dtype: float64 |
| - name: mean_ttft_ms |
| dtype: float64 |
| - name: median_ttft_ms |
| dtype: float64 |
| - name: p90_ttft_ms |
| dtype: float64 |
| - name: p99_ttft_ms |
| dtype: float64 |
| - name: mean_tpot_ms |
| dtype: float64 |
| - name: median_tpot_ms |
| dtype: float64 |
| - name: p90_tpot_ms |
| dtype: float64 |
| - name: p99_tpot_ms |
| dtype: float64 |
| - name: mean_itl_ms |
| dtype: float64 |
| - name: median_itl_ms |
| dtype: float64 |
| - name: p90_itl_ms |
| dtype: float64 |
| - name: p99_itl_ms |
| dtype: float64 |
| - name: mean_e2el_ms |
| dtype: float64 |
| - name: median_e2el_ms |
| dtype: float64 |
| - name: p90_e2el_ms |
| dtype: float64 |
| - name: p99_e2el_ms |
| dtype: float64 |
| splits: |
| - name: summary |
| num_examples: 3147 |
| num_bytes: 694254 |
| - config_name: distributional |
| features: |
| - name: run_id |
| dtype: string |
| - name: model |
| dtype: string |
| - name: model_family |
| dtype: string |
| - name: hardware |
| dtype: string |
| - name: engine |
| dtype: string |
| - name: tensor_parallelism |
| dtype: int64 |
| - name: profile |
| dtype: string |
| - name: concurrency |
| dtype: int64 |
| - name: num_requests |
| dtype: int64 |
| - name: duration_s |
| dtype: float64 |
| - name: successful_requests |
| dtype: int64 |
| - name: failed_requests |
| dtype: int64 |
| - name: request_throughput |
| dtype: float64 |
| - name: input_token_throughput |
| dtype: float64 |
| - name: output_token_throughput |
| dtype: float64 |
| - name: total_token_throughput |
| dtype: float64 |
| - name: mean_ttft_ms |
| dtype: float64 |
| - name: median_ttft_ms |
| dtype: float64 |
| - name: p90_ttft_ms |
| dtype: float64 |
| - name: p99_ttft_ms |
| dtype: float64 |
| - name: mean_tpot_ms |
| dtype: float64 |
| - name: median_tpot_ms |
| dtype: float64 |
| - name: p90_tpot_ms |
| dtype: float64 |
| - name: p99_tpot_ms |
| dtype: float64 |
| - name: mean_itl_ms |
| dtype: float64 |
| - name: median_itl_ms |
| dtype: float64 |
| - name: p90_itl_ms |
| dtype: float64 |
| - name: p99_itl_ms |
| dtype: float64 |
| - name: mean_e2el_ms |
| dtype: float64 |
| - name: median_e2el_ms |
| dtype: float64 |
| - name: p90_e2el_ms |
| dtype: float64 |
| - name: p99_e2el_ms |
| dtype: float64 |
| splits: |
| - name: summary |
| num_examples: 245 |
| num_bytes: 70836 |
| - config_name: kernels_labeled |
| features: |
| - name: source |
| dtype: string |
| - name: gpu |
| dtype: string |
| - name: model |
| dtype: string |
| - name: kernel_family |
| dtype: string |
| - name: kernel_name |
| dtype: string |
| - name: dtype |
| dtype: string |
| - name: held_out |
| dtype: bool |
| - name: M |
| dtype: float64 |
| - name: N |
| dtype: float64 |
| - name: K |
| dtype: float64 |
| - name: bs |
| dtype: float64 |
| - name: seq |
| dtype: float64 |
| - name: n_heads |
| dtype: float64 |
| - name: head_dim |
| dtype: float64 |
| - name: kv_heads |
| dtype: float64 |
| - name: numel |
| dtype: float64 |
| - name: op_type |
| dtype: string |
| - name: gpu_time_duration_ms |
| dtype: float64 |
| - name: launch_block_size |
| dtype: float64 |
| - name: launch_grid_size |
| dtype: float64 |
| - name: dram_bytes_sum |
| dtype: float64 |
| - name: launch_registers_per_thread |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 148077 |
| - config_name: roofline_quadrant |
| features: |
| - name: model |
| dtype: string |
| - name: profile |
| dtype: string |
| - name: concurrency |
| dtype: int64 |
| - name: engine |
| dtype: string |
| - name: hardware |
| dtype: string |
| - name: oi |
| dtype: float64 |
| - name: cf_gb |
| dtype: float64 |
| - name: output_tput |
| dtype: float64 |
| - name: tpot_ms |
| dtype: float64 |
| - name: ttft_ms |
| dtype: float64 |
| splits: |
| - name: train |
| num_examples: 2163 |
| - config_name: predictions |
| features: |
| - name: hardware_config |
| dtype: string |
| - name: model |
| dtype: string |
| - name: backend |
| dtype: string |
| - name: profile |
| dtype: string |
| - name: data_scope |
| dtype: string |
| - name: concurrency |
| dtype: int64 |
| - name: isl |
| dtype: int64 |
| - name: osl |
| dtype: int64 |
| - name: calibration_status |
| dtype: string |
| - name: ttft_validation_scope |
| dtype: string |
| - name: ttft_kernel_ms |
| dtype: float64 |
| - name: ttft_base_ms |
| dtype: float64 |
| - name: ttft_floor_ms |
| dtype: float64 |
| - name: ttft_first_decode_ms |
| dtype: float64 |
| - name: ttft_queue_ms |
| dtype: float64 |
| - name: itl_meas |
| dtype: float64 |
| - name: total_context_tokens |
| dtype: int64 |
| - name: new_prefill_tokens |
| dtype: int64 |
| - name: cached_context_tokens |
| dtype: int64 |
| - name: cache_hit_rate |
| dtype: float64 |
| - name: cache_aware_applied |
| dtype: bool |
| - name: cache_feature_source |
| dtype: string |
| - name: cache_prediction_regime |
| dtype: string |
| - name: ttft_prediction_supported |
| dtype: bool |
| - name: multiturn_prediction_mode |
| dtype: string |
| - name: predicted_turn_count |
| dtype: float64 |
| - name: total_successful_turn_requests |
| dtype: float64 |
| - name: mean_predicted_turn_ttft_ms |
| dtype: float64 |
| - name: mean_predicted_turn_tpot_ms |
| dtype: float64 |
| - name: multiturn_turn_predictions |
| dtype: string |
| - name: ttft_pred |
| dtype: float64 |
| - name: ttft_meas |
| dtype: float64 |
| - name: ttft_err |
| dtype: float64 |
| - name: tpot_pred |
| dtype: float64 |
| - name: tpot_meas |
| dtype: float64 |
| - name: tpot_err |
| dtype: float64 |
| - name: e2el_pred |
| dtype: float64 |
| - name: e2el_meas |
| dtype: float64 |
| - name: e2el_err |
| dtype: float64 |
| - name: measurement_semantics_warning |
| dtype: string |
| splits: |
| - name: train |
| num_examples: 4715 |
| --- |
| |
| # AgentPerfBench |
|
|
| LLM inference benchmark: 3,392 serving runs, 148,077 per-kernel NCU profiles, and 4,715 latency predictions across 9 models, 14 GPU configurations, and 2 serving engines (vLLM 0.19.0, SGLang 0.5.9). All models served in BF16 except gpt-oss, which uses mxfp4 for projection weights. |
|
|
| ## Dataset configurations |
|
|
| ### trace_replay (3,147 rows) |
| |
| Replays exact ISL/OSL sequences from recorded agent sessions (SWE-Bench, TerminalBench, OSWorld, ShareGPT). 77 (model, hardware, engine) combinations, 17 profiles, 6 concurrency levels. |
| |
| 17 profiles: `chat-medium`, `chat-multiturn-long`, `chat-multiturn-medium`, `chat-multiturn-short`, `chat-short`, `chat-singleturn`, `coding-singleturn`, `decode-heavy`, `osworld-multiturn-long`, `osworld-multiturn-medium`, `osworld-multiturn-short`, `prefill-heavy`, `random-1k`, `swebench-multiturn-medium`, `swebench-multiturn-short`, `terminalbench-multiturn-medium`, `terminalbench-multiturn-short` |
| |
| ### distributional (245 rows) |
| |
| ISL/OSL sampled from lognormal fits to real workload statistics. 42 combinations, 6 profiles, 7 concurrency levels. |
| |
| 6 profiles: `chat-multiturn`, `chat-singleturn`, `coding-singleturn`, `osworld-multiturn`, `swebench-multiturn`, `terminalbench-multiturn` |
| |
| ### kernels_labeled (148,077 rows) |
|
|
| Per-kernel Nsight Compute (ncu) profiles across 4 GPUs (A100, H100, RTX 3090, RTX 2080 Ti) and 13 model/sweep sources. |
|
|
| ### roofline_quadrant (2,163 rows) |
| |
| Operational intensity and achieved throughput per kernel, for roofline analysis. H100 reference hardware (989 peak TFLOPS, 3.35 TB/s HBM). |
| |
| ### predictions (4,715 rows) |
| |
| Predicted vs. measured TTFT, TPOT, and E2EL for each serving configuration, with cache-aware prediction metadata. 14 hardware configs. |
| |
| ### Concurrency filtering |
| |
| Concurrency is controlled by a fixed-size connection pool. Trace replay uses levels {1, 5, 10, 20, 40, 80}; distributional uses {1, 5, 10, 40, 80, 200, 320}. |
| |
| Early runs used a session-pool size smaller than the declared concurrency (`num_sessions=100` for trace replay, `num_sessions=10` for distributional), capping actual load below the nominal value. Rows where declared concurrency exceeded the session pool were dropped. |
| |
| | Config | Rows | |
| |--------|------| |
| | trace_replay | 3,147 | |
| | distributional | 245 | |
| | **Total** | **3,392** | |
|
|
| ## Coverage |
|
|
| ### Hardware |
|
|
| All benchmarks collected on PyTorch 2.10.0, CUDA 12.8. |
|
|
| | GPU | VRAM | HBM bandwidth | Peak half-precision TFLOPS | |
| |-----|------|---------------|---------------------------| |
| | NVIDIA H100 SXM | 80 GB | 3.35 TB/s | 989 | |
| | NVIDIA A100 SXM4 | 40 GB | 1.56 TB/s | 312 | |
| | NVIDIA RTX 3090 | 24 GB | 936 GB/s | 71 | |
| | NVIDIA RTX 2080 Ti | 11 GB | 616 GB/s | 27 | |
|
|
| Multi-GPU configurations: 1, 2, 4, or 8 GPUs with tensor parallelism. |
|
|
| ### Models |
|
|
| All models served in BF16 unless noted. |
|
|
| | Model | Family | Parameters | Architecture | Notes | |
| |-------|--------|-----------|--------------|-------| |
| | Llama-3.1-8B | Llama | 8B | Dense | | |
| | Llama-3.1-70B | Llama | 70B | Dense | | |
| | Llama-3.3-70B | Llama | 70B | Dense | | |
| | Qwen2.5-72B | Qwen | 72B | Dense | | |
| | Qwen3.5-9B | Qwen | 9B | Dense | | |
| | Qwen3.5-27B | Qwen | 27B | Dense | | |
| | Mixtral-8x7B | Mixtral | 46.7B (12.9B active) | MoE | | |
| | gpt-oss-20b | GPT-OSS | 21B (3.6B active) | MoE | mxfp4 projections | |
| | gpt-oss-120b | GPT-OSS | 117B (5.1B active) | MoE | mxfp4 projections | |
|
|
| ### Engines |
|
|
| - vLLM 0.19.0 |
| - SGLang 0.5.9 |
|
|
| ## Schema |
|
|
| Each row in `summary.parquet` (both configs): |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | run_id | string | Deterministic hash of run parameters | |
| | model | string | Model short name | |
| | model_family | string | Model family (llama, qwen, gpt-oss, mixtral) | |
| | hardware | string | GPU configuration (e.g., H100x4) | |
| | engine | string | Serving engine (vllm, sglang) | |
| | tensor_parallelism | int | TP degree | |
| | profile | string | Workload profile name | |
| | concurrency | int | Concurrent request level | |
| | num_requests | int | Total requests in run | |
| | duration_s | float | Total run duration | |
| | successful_requests | int | Completed requests | |
| | failed_requests | int | Failed requests | |
| | request_throughput | float | Requests/second | |
| | input_token_throughput | float | Input tokens/second | |
| | output_token_throughput | float | Output tokens/second | |
| | total_token_throughput | float | Total tokens/second | |
| | mean/median/p90/p99_ttft_ms | float | Time to first token | |
| | mean/median/p90/p99_tpot_ms | float | Time per output token | |
| | mean/median/p90/p99_itl_ms | float | Inter-token latency | |
| | mean/median/p90/p99_e2el_ms | float | End-to-end latency | |
|
|
| ## Loading |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("agent-perf-bench/AgentPerfBench", "trace_replay") |
| # or "distributional", "kernels_labeled", "roofline_quadrant", "predictions" |
| ``` |
|
|
| ## Benchmark methodology |
|
|
| - Closed-loop concurrency with semaphore control. |
| - 3-request warmup before each configuration. |
| - Metrics: TTFT, TPOT, ITL, E2EL, request throughput, token throughput (mean, median, p90, p99). |
| - Metrics computed over successful requests only. |
| - Collection period: March 2026 onwards. |
|
|
| ## Limitations |
|
|
| - Distributional profiles are fitted approximations, not direct production replays. |
| - Closed-loop concurrency only; no open-loop (Poisson) arrivals. |
|
|
| ## Ethical considerations |
|
|
| No PII. Trace-replay profiles derive from open benchmarks (SWE-Bench MIT, TerminalBench, OSWorld). Synthetic profiles use random tokens. |
|
|
| ## License |
|
|
| Benchmark data released under Apache-2.0. Source datasets retain their original licenses. |
|
|
| ## Source datasets |
|
|
| - [SWE-Bench](https://github.com/princeton-nlp/SWE-bench) (MIT) |
| - [TerminalBench](https://github.com/TerminalBench/TerminalBench) |
| - [ShareGPT (Aeala/ShareGPT_Vicuna_unfiltered)](https://huggingface.co/datasets/Aeala/ShareGPT_Vicuna_unfiltered) |
| - [OSWorld](https://github.com/xlang-ai/OSWorld) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{agentperfbench2026, |
| title={AgentPerfBench: A Benchmarking and Evaluation Suite for Inference Performance of Agentic LLMs}, |
| author={Anonymous}, |
| booktitle={NeurIPS 2026 Evaluations and Datasets Track}, |
| year={2026} |
| } |
| ``` |
|
|
