---
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: synthetic_distributional
    data_files:
      - split: summary
        path: synthetic_distributional/summary.parquet
  - config_name: kernels_labeled
    data_files:
      - split: train
        path: kernel_profiles/kernels_labeled.parquet
  - config_name: mse_validation
    data_files:
      - split: summary
        path: mse_validation/summary.parquet
  - config_name: layer_roofline
    data_files:
      - split: summary
        path: layer_roofline/summary.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: synthetic_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: mse_validation
    features:
      - name: validation_id
        dtype: string
      - name: tier
        dtype: string
      - name: stage
        dtype: string
      - name: stage_label
        dtype: string
      - name: comparison_group
        dtype: string
      - name: raw_json_r2_uri
        dtype: string
      - name: per_turn_json_r2_uri
        dtype: string
      - name: replay_kind
        dtype: string
      - name: workload
        dtype: string
      - name: profile
        dtype: string
      - name: model
        dtype: string
      - name: hardware
        dtype: string
      - name: engine
        dtype: string
      - name: tensor_parallelism
        dtype: int64
      - name: concurrency
        dtype: int64
      - name: sessions
        dtype: int64
      - name: source_locked
        dtype: bool
      - name: prefix_caching_state
        dtype: string
      - name: chunked_prefill
        dtype: string
      - name: prefix_aware_synthetic
        dtype: bool
      - name: shared_prefix_tokens
        dtype: int64
      - name: shared_prefix_block_aligned
        dtype: bool
      - name: synthetic_filler_style
        dtype: string
      - name: synthetic_target_chars_per_token
        dtype: float64
      - name: max_model_len
        dtype: int64
      - name: success_rate
        dtype: float64
      - 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: 28
        num_bytes: 40940
  - config_name: layer_roofline
    features:
      - name: record_type
        dtype: string
      - name: source_file
        dtype: string
      - name: model
        dtype: string
      - name: hardware
        dtype: string
      - name: engine
        dtype: string
      - name: dtype
        dtype: string
      - name: tensor_parallelism
        dtype: int64
      - name: phase
        dtype: string
      - name: batch_size
        dtype: int64
      - name: sequence_length
        dtype: int64
      - name: q_len
        dtype: int64
      - name: kv_len
        dtype: int64
      - name: component_name
        dtype: string
      - name: component_bound
        dtype: string
      - name: flops
        dtype: float64
      - name: bytes
        dtype: float64
      - name: operational_intensity_flop_per_byte
        dtype: float64
      - name: ridge_point_flop_per_byte
        dtype: float64
      - name: total_flops
        dtype: float64
      - name: total_bytes
        dtype: float64
      - name: overall_bound
        dtype: string
      - name: kernel_id
        dtype: int64
      - name: kernel_name
        dtype: string
      - name: block_size
        dtype: string
      - name: grid_size
        dtype: string
      - name: duration_us
        dtype: float64
      - name: compute_sm_throughput_pct
        dtype: float64
      - name: dram_throughput_pct
        dtype: float64
      - name: memory_throughput_pct
        dtype: float64
      - name: l1_tex_cache_throughput_pct
        dtype: float64
      - name: l2_cache_throughput_pct
        dtype: float64
      - name: sm_frequency_ghz
        dtype: float64
      - name: dram_frequency_ghz
        dtype: float64
      - name: artifact_path
        dtype: string
      - name: artifact_kind
        dtype: string
      - name: artifact_bytes
        dtype: int64
      - name: artifact_description
        dtype: string
      - name: notes
        dtype: string
    splits:
      - name: summary
        num_examples: 56
        num_bytes: 27430
---

# AgentPerfBench

LLM inference benchmark: 3,392 main sweep rows measuring TTFT, TPOT, ITL, and throughput across 9 models, up to 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. The dataset also includes 148,077 per-kernel NCU profiles, 28 curated tabular MSE validation rows for the distributional synthetic replay generator, and 56 layer-roofline validation rows.

## Dataset configurations

The dataset provides five configurations. `trace_replay` replays exact input/output sequences from recorded agent sessions. `synthetic_distributional` samples from statistical distributions fitted to those same workloads, trading fidelity for faster sweeps across the hardware matrix. `kernels_labeled` contains per-kernel Nsight Compute labels. `mse_validation` contains tabular paired synthetic-vs-real validation rows and ablations for the final APC-aware synthetic generator, with raw JSON artifacts referenced in R2 rather than stored in the dataset repo. `layer_roofline` exposes the per-layer roofline validation artifacts as a loadable tabular subset.

### trace_replay (3,147 rows)

Replays exact ISL/OSL sequences from recorded agent sessions (SWE-Bench, TerminalBench, OSWorld, ShareGPT). Covers 77 unique (model, hardware, engine) combinations across 17 profiles and 6 concurrency levels. The full 5-dimensional matrix is 12.2% filled; not all models run on all hardware.

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`

### synthetic_distributional (245 rows)

Samples ISL/OSL from lognormal distributions fitted to real workload statistics. Covers 42 unique (model, hardware, engine) combinations across 6 profiles and 7 concurrency levels (3.0% matrix fill). `gpt-oss-120b`, `3090x8`, and `A100-40GBx8` are excluded from this configuration.

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.

### mse_validation (28 rows)

Curated H100 / Llama-3.1-8B / vLLM validation table for the distributional synthetic replay generator. The main rows keep paired MSE distributional replay and real trace replay runs with success rate at least 75%; supplementary rows preserve no-replacement and high-concurrency debug runs. Raw aggregate/per-turn JSON artifacts are referenced through R2 URI columns, not stored as dataset files.

The headline SWE-bench C=5 source-locked cascade is:

| Condition | Turn 10-19 E2EL delta |
|-----------|----------------------:|
| APC on, English filler, source-locked | +45.5% |
| APC on, code-morph filler, no shared prefix | +31.1% |
| APC off, code-morph filler, no shared prefix | +11.7% |
| APC on, code-morph filler, 1024-token shared prefix | -3.2% |

See `mse_validation/README.md`, `mse_validation/manifest.csv`, and `mse_validation/fidelity_deltas.csv` for the filtering rule and R2 raw-artifact URIs.

### layer_roofline (56 rows)

Tabular view over the per-layer roofline evidence for Llama-3.1-8B on H100. This subset combines analytical component OI rows, selected NCU kernel summary rows, and an artifact manifest pointing to the raw `per_layer_oi_cf/` evidence files.

Record types: `analytical_total`, `analytical_component`, `ncu_kernel`, `artifact`.

### Concurrency filtering

The benchmark harness capped actual concurrent connections at the session pool size. Rows where declared concurrency exceeded the pool were excluded:

- trace_replay: concurrency > 100 removed (session pool was 100). Remaining values: {1, 5, 10, 20, 40, 80}.
- synthetic_distributional (pre-fix): concurrency > 10 removed (session pool was 10). Post-fix data has no cap. Remaining values: {1, 5, 10, 40, 80, 200, 320}.

| Config | Rows |
|--------|------|
| trace_replay | 3,147 |
| synthetic_distributional | 245 |
| mse_validation | 28 |
| layer_roofline | 56 |
| kernels_labeled | 148,077 |

### Failed requests

Some runs produce request failures, typically at high concurrency where the engine hits memory or timeout limits. 30.8% of trace_replay rows and 42% of synthetic_distributional rows have `failed_requests > 0`. Summary metrics (TTFT, TPOT, throughput) are computed from successful requests only.

## 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. TP degree depends on model size and available GPUs.

### 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 |

Model names in this table match the `model` column in the parquet files.

### Engines

- vLLM 0.19.0
- SGLang 0.5.9

## Schema

Each row in the serving `summary.parquet` 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 "synthetic_distributional", "kernels_labeled", "mse_validation", "layer_roofline"
```

## Benchmark methodology

- Closed-loop concurrency with semaphore control.
- Concurrency levels: {1, 5, 10, 20, 40, 80} (trace_replay), {1, 5, 10, 40, 80, 200, 320} (synthetic_distributional).
- 3-request warmup before each configuration.
- Metrics: TTFT, TPOT, ITL, E2EL, request throughput, token throughput.
- Summary statistics: mean, median, p90, p99.
- Collection period: March 2026 onwards.
- PyTorch 2.10.0, CUDA 12.8 on all machines. All models served in BF16 (gpt-oss: mxfp4 projection weights).

## Future releases

- Full per-request and multi-turn granularity data for the main sweep (pending raw JSON availability from collection infrastructure). Curated raw JSONs are referenced from R2 for `mse_validation`.
- Additional per-kernel roofline profiles beyond the included `kernels_labeled`, `layer_roofline`, and raw `per_layer_oi_cf` artifacts.
- This is version 1.0. Updates will be tagged with semantic versions.

## Intended uses

- Inference engine comparison under controlled conditions.
- Capacity planning for LLM deployments.
- TTFT scaling with context length in multi-turn sessions.

## Limitations

- Results are specific to tested hardware and software versions (vLLM 0.19.0, SGLang 0.5.9, PyTorch 2.10.0, CUDA 12.8).
- Synthetic distributional profiles approximate but do not replicate production traffic patterns.
- Consumer GPU coverage is limited to RTX 3090 and RTX 2080 Ti; no non-NVIDIA accelerators.
- Closed-loop concurrency only; no open-loop (Poisson) arrivals.
- The model-hardware-concurrency matrix is sparse (12.2% fill for trace_replay, 3.0% for synthetic_distributional). Not all model-hardware combinations are represented.
- No model quality metrics. This is a systems benchmark.

## 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}
}
```