---
license: cc-by-4.0
pretty_name: LLM Network Study Data
tags:
- network-traffic
- pcap
- packet-capture
- llm-inference
- traffic-analysis
- bfcl
size_categories:
- 10K<n<100K
configs: []
---

# LLM-Network-Study-Data

Per-request network captures (`.pcapng`) collected by the
[LLM-Network-Study](../LLM-Network-Study) benchmark harness (`benchmark.py` and the
per-workload test scripts). Each directory holds one capture file per request,
named `request_<id>_run<n>_<timestamp>.pcapng`.

A directory name encodes four dimensions:

```
<capture-env>_<provider/model>_<workload>[_<dataset/variant>]_results
```

## Dimension legend

| Dimension | Values | Meaning |
|-----------|--------|---------|
| **Capture env** | `ethernet` | Wired connection to the cloud API. |
| | `mobile_tethered` | Phone-tethered cellular link (phone as modem). |
| | `mobile_untethered` | Capture on the mobile device itself over cellular. |
| | `local` | Self-hosted model; traffic split into `client` and `server` side captures. |
| **Provider** | direct (`claude_*`, `openai_gpt_*`, `gpt_image_1`) | Native vendor API (Anthropic / OpenAI). |
| | `openrouter_*` | Same model routed through OpenRouter. |
| | `siliconflow_*` | SiliconFlow inference provider. |
| **Workload** | `bfcl_*` | Function-calling prompts from the BFCL v4 dataset (see below). |
| | `image_to_text` | Vision captioning of DiffusionDB images. |
| | `text_to_image` | Image generation from DiffusionDB prompts. |
| | `text_to_text` | Plain text generation (local models). |
| | `video_download` | Baseline (non-LLM) video download for comparison. |
| **Variant** | `diffusiondb_{100,405,2k}` | Sample size drawn from the DiffusionDB dataset. |
| | `gen1` / `gen2` | Repeated capture batches of the same config. |
| | `unblocked` | Run without rate-limiting/throttling. |

**BFCL workloads** come from the Berkeley Function-Calling Leaderboard v4 categories:
`simple_python` (single function call), `parallel` (multiple calls from one prompt),
`live_multiple` (real-world prompt, pick among many tools), and
`live_parallel_multiple` (real-world prompt, multiple parallel calls among many tools).

## Datasets

| Directory | Capture env | Model / Provider | Workload |
|-----------|-------------|------------------|----------|
| `ethernet_claude_opus_4_6_bfcl_live_multiple_results` | ethernet | Claude Opus 4.6 (Anthropic) | BFCL live_multiple |
| `ethernet_claude_opus_4_6_bfcl_live_parallel_multiple_results` | ethernet | Claude Opus 4.6 (Anthropic) | BFCL live_parallel_multiple |
| `ethernet_claude_opus_4_6_bfcl_parallel_results` | ethernet | Claude Opus 4.6 (Anthropic) | BFCL parallel |
| `ethernet_claude_opus_4_6_bfcl_simple_python_results` | ethernet | Claude Opus 4.6 (Anthropic) | BFCL simple_python |
| `ethernet_gpt_5_4_image_to_text_diffusiondb` | ethernet | GPT-5.4 (OpenAI) | Image-to-text (DiffusionDB) |
| `ethernet_gpt_image_1_text_to_image_diffusiondb_100_results` | ethernet | gpt-image-1 (OpenAI) | Text-to-image (DiffusionDB, 100) |
| `ethernet_gpt_image_1_text_to_image_diffusiondb_2k_unblocked_results` | ethernet | gpt-image-1 (OpenAI) | Text-to-image (DiffusionDB, 2k, unblocked) |
| `ethernet_openai_gpt_5_4_bfcl_live_multiple_results` | ethernet | GPT-5.4 (OpenAI direct) | BFCL live_multiple |
| `ethernet_openai_gpt_5_4_bfcl_live_parallel_multiple_results` | ethernet | GPT-5.4 (OpenAI direct) | BFCL live_parallel_multiple |
| `ethernet_openai_gpt_5_4_bfcl_parallel_results` | ethernet | GPT-5.4 (OpenAI direct) | BFCL parallel |
| `ethernet_openai_gpt_5_4_bfcl_simple_python_results` | ethernet | GPT-5.4 (OpenAI direct) | BFCL simple_python |
| `ethernet_openrouter_claude_sonnet_4_6_gen1_bfcl_live_multiple_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL live_multiple (batch 1) |
| `ethernet_openrouter_claude_sonnet_4_6_gen1_bfcl_live_parallel_multiple_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL live_parallel_multiple (batch 1) |
| `ethernet_openrouter_claude_sonnet_4_6_gen1_bfcl_parallel_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL parallel (batch 1) |
| `ethernet_openrouter_claude_sonnet_4_6_gen1_bfcl_simple_python_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL simple_python (batch 1) |
| `ethernet_openrouter_claude_sonnet_4_6_gen2_bfcl_live_multiple_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL live_multiple (batch 2) |
| `ethernet_openrouter_claude_sonnet_4_6_gen2_bfcl_live_parallel_multiple_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL live_parallel_multiple (batch 2) |
| `ethernet_openrouter_claude_sonnet_4_6_gen2_bfcl_parallel_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL parallel (batch 2) |
| `ethernet_openrouter_claude_sonnet_4_6_gen2_bfcl_simple_python_results` | ethernet | Claude Sonnet 4.6 (OpenRouter) | BFCL simple_python (batch 2) |
| `ethernet_openrouter_gemini_3_1_pro_bfcl_live_multiple_results` | ethernet | Gemini 3.1 Pro (OpenRouter) | BFCL live_multiple |
| `ethernet_openrouter_gemini_3_1_pro_bfcl_live_parallel_multiple_results` | ethernet | Gemini 3.1 Pro (OpenRouter) | BFCL live_parallel_multiple |
| `ethernet_openrouter_gemini_3_1_pro_bfcl_parallel_results` | ethernet | Gemini 3.1 Pro (OpenRouter) | BFCL parallel |
| `ethernet_openrouter_gemini_3_1_pro_bfcl_simple_python_results` | ethernet | Gemini 3.1 Pro (OpenRouter) | BFCL simple_python |
| `ethernet_openrouter_gpt_5_4_bfcl_live_multiple_results` | ethernet | GPT-5.4 (OpenRouter) | BFCL live_multiple |
| `ethernet_openrouter_gpt_5_4_bfcl_live_parallel_multiple_results` | ethernet | GPT-5.4 (OpenRouter) | BFCL live_parallel_multiple |
| `ethernet_openrouter_gpt_5_4_bfcl_parallel_results` | ethernet | GPT-5.4 (OpenRouter) | BFCL parallel |
| `ethernet_openrouter_gpt_5_4_bfcl_simple_python_results` | ethernet | GPT-5.4 (OpenRouter) | BFCL simple_python |
| `ethernet_openrouter_nemotron_3_super_120b_bfcl_live_multiple_results` | ethernet | Nemotron 3 Super 120B (OpenRouter) | BFCL live_multiple |
| `ethernet_openrouter_nemotron_3_super_120b_bfcl_parallel_results` | ethernet | Nemotron 3 Super 120B (OpenRouter) | BFCL parallel |
| `ethernet_openrouter_nemotron_3_super_120b_bfcl_simple_python_results` | ethernet | Nemotron 3 Super 120B (OpenRouter) | BFCL simple_python |
| `ethernet_siliconflow_image_to_text_results` | ethernet | SiliconFlow VLM | Image-to-text (DiffusionDB) |
| `ethernet_siliconflow_text_to_image_diffusiondb_405_results` | ethernet | SiliconFlow image model | Text-to-image (DiffusionDB, 405) |
| `ethernet_siliconflow_text_to_text_bfcl_parallel_results` | ethernet | SiliconFlow LLM | BFCL parallel (text) |
| `ethernet_video_download_results` | ethernet | — (baseline) | Video download baseline |
| `local_image_to_text_client_results` | local (client side) | Self-hosted VLM | Image-to-text (DiffusionDB) |
| `local_image_to_text_server_results` | local (server side) | Self-hosted VLM | Image-to-text (DiffusionDB) |
| `local_text_to_image_diffusiondb_client_results` | local (client side) | Self-hosted image model | Text-to-image (DiffusionDB) |
| `local_text_to_image_diffusiondb_server_results` | local (server side) | Self-hosted image model | Text-to-image (DiffusionDB) |
| `local_text_to_text_bfcl_parallel_client_results` | local (client side) | Self-hosted LLM | BFCL parallel (text) |
| `local_text_to_text_bfcl_parallel_server_results` | local (server side) | Self-hosted LLM | BFCL parallel (text) |
| `mobile_tethered_gpt_5_4_image_to_text_results` | mobile, tethered | GPT-5.4 (OpenAI) | Image-to-text (DiffusionDB) |
| `mobile_tethered_gpt_image_1_text_to_image_diffusiondb_405_unblocked_results` | mobile, tethered | gpt-image-1 (OpenAI) | Text-to-image (DiffusionDB, 405, unblocked) |
| `mobile_tethered_openai_gpt_5_4_bfcl_parallel_results` | mobile, tethered | GPT-5.4 (OpenAI) | BFCL parallel |
| `mobile_untethered_gpt_5_4_image_to_text_diffusiondb_100_results` | mobile, untethered | GPT-5.4 (OpenAI) | Image-to-text (DiffusionDB, 100) |
| `mobile_untethered_openai_gpt_5_4_bfcl_parallel_results` | mobile, untethered | GPT-5.4 (OpenAI) | BFCL parallel |

## Backup

These directories are mirrored to Box at
`RPI WAYS LAB/LLM/Result Pcaps/LLM-Network-Study-Data` via rclone
(`rclone copy . "box:RPI WAYS LAB/LLM/Result Pcaps/LLM-Network-Study-Data"`).