datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cc-traces-weka-062126
semianalysisai/cc-traces-weka-062126
WekaTrace corpus derived from SemiAnalysis Claude Code proxy traces. Built 2026-06-21 17:48:24 UTC via utils/agentic/build_weka_hf_dataset.py.
Filters
Trace version: exactly v7
min Anthropic requests per session: 20
Claude Code CLI ≥ 2.1.139 (every row)
peak concurrent sub-agent groups ≤ 10
Non-image rows only (image content excluded at source)
Classifier calls excluded (max_tokens<=64 AND no tools → SUGGESTION MODE, title-gen… See the full description on the dataset page: https://huggingface.co/datasets/semianalysisai/cc-traces-weka-062126.Open-SWE-Traces
Open-SWE-Traces: Advancing Distillation for Software Engineering Agents
🚨 What's New
[09/26] Release v1.2: Added new agent trajectories generated by Qwen3.8-27B for
mini-swe-agent. Trajectories for OpenCode and Claude Code harnesses will be released soon.
[08/26] Release v1.1: Added new agent trajectories generated by DeepSeek-V4-Flash and
Qwen3.6-27B across OpenHands,
SWE-agent, and mini-swe-agent harnesses.
[06/21] Release v1.0: Released 207k agent… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Open-SWE-Traces.cc-traces-weka-062126-256k
semianalysisai/cc-traces-weka-062126-256k
WekaTrace corpus derived from SemiAnalysis Claude Code proxy traces. Built 2026-06-21 17:49:45 UTC via utils/agentic/build_weka_hf_dataset.py.
Derived from semianalysisai/cc-traces-weka-062126 by applying the 256k per-request cap and preserving the surviving requests' relative timestamps.
Filters
Trace version: exactly v7
min Anthropic requests per session: 20
Claude Code CLI ≥ 2.1.139 (every row)
peak concurrent… See the full description on the dataset page: https://huggingface.co/datasets/semianalysisai/cc-traces-weka-062126-256k.rl-game-traces-rise-of-the-tomb-raider
古墓丽影：崛起
This public dataset repository contains gameplay trace data uploaded from F:\古墓丽影：崛起.
Contents
Files: 647
Total local size: 496.11 GB
Generated: 2026-06-06T01:03:39+00:00
File Types
.jsonl: 196
.json: 149
.png: 129
.parquet: 49
.mkv: 49
.txt: 49
.jpg: 15
.exe: 11
Notes
This repository may contain gameplay video, Parquet files, JSON/JSONL metadata, and input event logs.
The license is marked as other; review game footage… See the full description on the dataset page: https://huggingface.co/datasets/yinhuankuang/rl-game-traces-rise-of-the-tomb-raider.cot-eval-traces-2.0flashinfer-trace
FlashInfer Trace
We provide an official dataset called FlashInfer Trace with kernels and workloads in real-world AI system deployment environments. FlashInfer-Bench can use this dataset to measure and compare the performance of kernels. It follows the FlashInfer Trace Schema.
It is organized as follows:
flashinfer_trace/ # Here
├── definitions/
└── workloads/
flashinfer-trace/ # On Hugging Face
├── solutions/
└── traces/
Example solutions and traces directories, featuring… See the full description on the dataset page: https://huggingface.co/datasets/flashinfer-ai/flashinfer-trace.chankhavu-imo-reasoning-tracesfunes-nvidia-Open-SWE-Traces
Funes recall store — NVIDIA Open-SWE-Traces (resolved)
A funes recall store built by indexing the
resolved==1 trajectories of
nvidia/Open-SWE-Traces
(65244 sessions, across both harnesses — SWE-agent and OpenHands — and both models,
Minimax-M2.5 and Qwen3.5-122B).
What this is
This is not a raw trace dataset — it is a pre-built funes index: the source
trajectories chunked into content blocks and embedded, stored as a
Lance table (chunks.lance).
Source… See the full description on the dataset page: https://huggingface.co/datasets/dacorvo/funes-nvidia-Open-SWE-Traces.kernelbench-mega-traces
KernelBench-Mega agent traces
Coding agents writing full GPU megakernels across Blackwell / H100 / B200, scored as speedup over reference; contamination-audited (23 verified cells).
Each .jsonl file is one agent run in Claude-Code session format, viewable with the agent trace viewer. Filename = run id; manifest.csv maps each run to model / harness / problem / GPU / score.
23 agent traces · live leaderboard: https://kernelbench.com/mega
Secrets redacted. Full reasoning for… See the full description on the dataset page: https://huggingface.co/datasets/Infatoshi/kernelbench-mega-traces.kernelbench-hard-traces
KernelBench-Hard agent traces
Frontier coding agents writing optimized CUDA/Triton kernels (FP8 GEMM, paged
attention, MoE, W4A16, KDA, Top-k) on RTX PRO 6000 Blackwell, H100 PCIe, and
B200; roofline-graded.
Each .jsonl file is one agent run in Claude-Code session format, viewable with
the Hugging Face Agent Trace viewer (Data Studio → open a row). Filename =
run id.
Live leaderboard: https://kernelbench.com/hard
Secrets redacted. Full reasoning for open-provider routes… See the full description on the dataset page: https://huggingface.co/datasets/Infatoshi/kernelbench-hard-traces.gpt-oss-20b-moe-expert-power-traces-320k
GPT-OSS-20B MoE Expert Power Traces (320k, ChipWhisperer)
This dataset contains analog power traces captured with a ChipWhisperer Husky while running forced single-expert MoE computations derived from openai/gpt-oss-20b on an NVIDIA H100.
What is recorded
Each trace corresponds to one capture trial where:
A fixed expert id is selected (expert_00 ... expert_31).
A random hidden-state tensor is generated once per trial.
The selected expert computation is executed… See the full description on the dataset page: https://huggingface.co/datasets/masterpieceexternal/gpt-oss-20b-moe-expert-power-traces-320k.TraceSpatial-Trace
TraceSpatial-Trace
Project · Paper · Code
TraceSpatial-Trace is the RGB-and-QA tracing subset of TraceSpatial, introduced by the RoboTracer project. It supports learning to translate language instructions into spatial waypoints for object manipulation and robot end-effector motion.
This release contains 517,215 referenced RGB images and 3,623,880 question–answer pairs, extracted from 1,067,822 original conversation records across AgiBot, CA-1M, DROID, RoboTwin, and ScanNet. It… See the full description on the dataset page: https://huggingface.co/datasets/VCG-EAI/TraceSpatial-Trace.aime_1983_2023_deepseek-r1_traces_16384wham3d-cts-trace-markov-rollouts-20260923
3D WHAM Trace+Markov cached video continuations
Growing, publicly downloadable video-backed rollout dataset for the trace_markov ablation arm at training step 500, seed 20260921. Each selected frozen observational prefix has exactly one cached continuation in each of two routes: null-intervention observational and diagnostic do(X=1). Prefix IDs are sorted once within each (W,Z) stratum and remain balanced as the cohort grows. The direct route of an observationally trained arm is… See the full description on the dataset page: https://huggingface.co/datasets/osazuwa/wham3d-cts-trace-markov-rollouts-20260923.wham3d-cts-trace-rollouts-20260923
3D WHAM Trace cached video continuations
Growing, publicly downloadable video-backed rollout dataset for the trace ablation arm at training step 500, seed 20260921. Each selected frozen observational prefix has exactly one cached continuation in each of two routes: null-intervention observational and diagnostic do(X=1). Prefix IDs are sorted once within each (W,Z) stratum and remain balanced as the cohort grows. The direct route of an observationally trained arm is a diagnostic;… See the full description on the dataset page: https://huggingface.co/datasets/osazuwa/wham3d-cts-trace-rollouts-20260923.misc-merged-claude-code-traces-v1
MISC Unification of Public Claude Code Traces
A unified dataset of 32,133 deduplicated Claude API conversation traces focused on software engineering and code generation tasks. This dataset merges and normalizes traces from 10 different source datasets into a single, consistent format.
Dataset Description
This dataset contains real Claude API interaction traces capturing software engineering workflows including:
Code generation and modification
Bug fixing and debugging… See the full description on the dataset page: https://huggingface.co/datasets/nlile/misc-merged-claude-code-traces-v1.schedulerlens-tracesqwen36-27b-length-traces
Qwen3.6-27B generation-length prediction: heads, calibrations and workloads
Artifacts for conformal length-aware LLM scheduling on Qwen/Qwen3.6-27B — predicting a
request's remaining generation length from a hidden layer during decoding, wrapping it in a
split-conformal interval, and scheduling with SRPT inside vLLM. Extends TRAIL
(Don't Stop Me Now, ICLR'25) to a hybrid-attention reasoning model.
This repo contains the derived artifacts, not the raw activations. The 3250… See the full description on the dataset page: https://huggingface.co/datasets/dungnv/qwen36-27b-length-traces.vllm-traces-v2NatureBench-traces
NatureBench-traces
NatureBench-traces contains the full solving process
of coding agents on the 90 tasks of NatureBench.
The task packages themselves (task brief, data, evaluator, SOTA
scores) live in the sibling repository FrontisAI/NatureBench.
Harbor-compatible task packages are available in
FrontisAI/NatureBench-Harbor.
The traces released here were collected with NatureBench's native task format, not from the Harbor tasks.
This repository releases only the process traces:… See the full description on the dataset page: https://huggingface.co/datasets/FrontisAI/NatureBench-traces.wmo-terminal-tasks-traces
terminal-tasks — real agent-environment traces
Computer-use agent runs in real terminal containers: bash commands and their true outputs from live task environments.
Every trace is a REAL run: an LLM agent stepping against the actual benchmark environment, with
each transition (tool call → true environment observation) recorded as OpenTelemetry GenAI spans
(traces.otel.jsonl, one span per line). Captured by
world-model-harness's
environment-capture package, which also holds the… See the full description on the dataset page: https://huggingface.co/datasets/experiential-labs/wmo-terminal-tasks-traces.wmo-bird-sql-traces
bird-sql — real agent-environment traces
Text-to-SQL over real SQLite databases: the agent explores a copy of the task's database and schema, then submits a SQL query.
Every trace is a REAL run: an LLM agent stepping against the actual benchmark environment, with
each transition (tool call → true environment observation) recorded as OpenTelemetry GenAI spans
(traces.otel.jsonl, one span per line). Captured by
world-model-harness's
environment-capture package, which also holds… See the full description on the dataset page: https://huggingface.co/datasets/experiential-labs/wmo-bird-sql-traces.agent-llm-traces-v2
Exgentic Agent LLM Traces v2 — Agent Chat Only
OpenTelemetry-shaped execution traces for 10,057 agent runs across 6 benchmarks (AppWorld, SWE-bench, BrowseCompPlus, τ²-bench Airline/Retail/Telecom), filtered to the agent under test's chat-only LLM calls. This is the dataset for replay testing, behavioral analysis, or any task where you care about what the benchmarked model actually did — not the eval scaffolding around it.
This v2 release expands upon Exgentic/agent-llm-traces… See the full description on the dataset page: https://huggingface.co/datasets/Exgentic/agent-llm-traces-v2.sweeperbench-traces
Sweeperbench run database
runs.csv is the append-only raw table. Each row describes one prediction, core evaluation, or preservation evaluation. schema.json documents the fields.
Primary key: run_id (UUID). Each top-level UUID directory is exactly that run, with matching metadata.json, artifact manifest, prompts, traces, verdicts and any collected recordings.
Relationships: experiment_id groups a launch; evaluations reference the exact prediction_run_id. Model, harness… See the full description on the dataset page: https://huggingface.co/datasets/tonychenxyz/sweeperbench-traces.Ox-Alpha-Pi-TracesThis dataset was generated using teich by TeichAI
Ox-Alpha Pi Agent Coding Traces
This directory contains raw agent trace files generated by teich.
JSONL files: 2247
Model metadata: stealth/ox-alpha
Domains and prompt distribution
Topic
Traces
Games & simulation (headless)
196
Frontend & Node-testable web
159
Health & medicine informatics
139
ML & scientific computing (CPU)
123
Data analysis & reporting
122
Computational biology & chemistry… See the full description on the dataset page: https://huggingface.co/datasets/TeichAI/Ox-Alpha-Pi-Traces.optiq-lab-traces
OptiQ Lab Traces
Research and tool-calling sessions produced by OptiQ Lab, the local web UI that ships with mlx-optiq. Each session is a complete run: a deep-research report built from live web sources, or a multi-turn agent loop driving the Lab's own sandboxed tools.
The dataset is 866 sessions in HuggingFace Session-Traces format (the agent-traces viewer). Each .jsonl file is one session: a header line carrying the run's metadata, then one message per turn.
The two… See the full description on the dataset page: https://huggingface.co/datasets/mlx-community/optiq-lab-traces.Fable-GPT-5.5-Distillation-Traces
Agent Traces Curated 2026 (v3 Merged)
A unified distillation corpus of 9,057,143 records spanning agentic
coding traces, math/code/science reasoning, tool-use trajectories, and
preference data. 8,876,012 train + 181,131 eval, stratified by source.
What this is
This is the v3 merged corpus that supersedes both v1 and v2 of this dataset.
It combines five major source groups through a unified normalization
pipeline:
Original v2 RESMP-DEV (de-fragmented, re-deduped):… See the full description on the dataset page: https://huggingface.co/datasets/RESMP-DEV/Fable-GPT-5.5-Distillation-Traces.MoE_expert_selection_trace
📖 Introduction
This repository serves as a supplement to our paper "Patterns behind Chaos: Forecasting Data Movement for Efficient Large-Scale MoE LLM Inference".
It contains expert selection profiling traces of four top-tier MoE LLMs ranging from 235B to 1T (DeepSeek-R1, Kimi-K2-Thinking, Llama4-Marverick, and Qwen3-235B) across multiple benchmarks. For each query or request, we log the activated expert ID of every model layer of every generated token.
We provide analyses and… See the full description on the dataset page: https://huggingface.co/datasets/core12345/MoE_expert_selection_trace.hal_tracesreal-pi-coding-agent-traces-sessions
Real Pi Coding Agent Traces Sessions
An aggregated dataset of real human–AI coding agent sessions, collected from 21 independently published Hugging Face datasets and hand-filtered to exclude synthetic or AI-generated content.
Every session is an unedited (but redacted) trace of a real person using pi — an open-source AI coding agent harness — to build, debug, and ship real open-source software. Real prompts, real tool calls, real errors, real backtracking.
Why this… See the full description on the dataset page: https://huggingface.co/datasets/MaxDevv/real-pi-coding-agent-traces-sessions.