Datasets:

ByteDance-Seed
/

EdgeBench

task_id stringlengths 10 39	name stringlengths 10 39	category stringclasses 6 values	description stringlengths 123 252	language stringclasses 6 values	metric stringclasses 4 values	internet bool 2 classes
bipedalwalker_locomotion_rl	Bipedalwalker Locomotion Rl	Scientific Problems & ML	Train a CPU-only locomotion policy for BipedalWalker and its Hardcore variant. The judge evaluates only the submitted policy checkpoint, not the training process. Pre-trained policies and external RL libraries are prohibited.	Python	score (maximize)	false
capecod_plume_reconstruction	Capecod Plume Reconstruction	Scientific Problems & ML	Reconstruct a multi-analyte groundwater plume from sparse monitoring wells: predict concentrations at withheld locations and times, compute plume metrics, and propose an optimal monitoring network under budget constraints.	Python	score (maximize)	false
dabic_gravity_inversion	Dabic Gravity Inversion	Scientific Problems & ML	Implement the D-ABIC regularization method for 3D gravity inversion within the SimPEG framework, run on both synthetic and real Vinton salt dome data under L0 and L1 sparse norms, and compare against a Hamiltonian Monte Carlo baseline.	Python	score (maximize)	false
graph_node_classification	Graph Node Classification	Scientific Problems & ML	Implement graph neural networks from scratch using only base PyTorch for semi-supervised node classification on an unseen graph under CPU-only constraints.	Python	score (maximize)	false
ann_vector_search_qps	Ann Vector Search Qps	Systems & Software Engineering	Replace a brute-force NumPy nearest-neighbor baseline with a high-performance approximate nearest-neighbor implementation under a hard recall constraint. Scored by queries per second.	Python	score (maximize)	false
arc_compiler_runtime	Arc Compiler Runtime	Systems & Software Engineering	Implement a complete TypeScript compiler pipeline (lexer, parser, type checker, code generator) for a novel programming language defined by specification documents.	Python	score (maximize)	false
exchange_core_throughput	Exchange Core Throughput	Systems & Software Engineering	Maximize peak throughput of a Java financial matching engine built on the LMAX Disruptor by tuning thread topology, wait strategies, ring-buffer sizing, order-book implementation, and JVM configuration.	Java	score (maximize)	false
ffmpeg_swscale_reimplementation	Ffmpeg Swscale Reimplementation	Systems & Software Engineering	Reimplement FFmpeg's libswscale pixel-format conversion and scaling library in Rust, handling multiple pixel formats and scaling algorithms. A correctness-passing scaffold is provided; the agent must optimize for speed via SIMD.	C++	score (maximize)	false
git_rewrite_in_zig	Git Rewrite In Zig	Systems & Software Engineering	Reimplement git as a drop-in Zig binary producing identical CLI output, exit codes, and repository state as the C reference implementation. The C source is available for reading but cannot be compiled.	C++	score (maximize)	false
integer_compression_codec	Integer Compression Codec	Systems & Software Engineering	Improve a C++ integer compression codec for better compression ratio and decode throughput on uint32 datasets via techniques such as delta encoding, bit-packing, and SIMD vectorization. Exact round-trip correctness is mandatory.	C++	score (maximize)	false
juliet_vulnerability_analyzer	Juliet Vulnerability Analyzer	Systems & Software Engineering	Implement a deterministic static analyzer that processes structured program facts to detect vulnerabilities across six CWE categories (stack/heap overflow, integer overflow, null dereference, use-after-free, command injection).	Python	score (maximize)	false
rust_multicrate_reconstruction	Rust Multicrate Reconstruction	Systems & Software Engineering	Reconstruct missing Rust implementations across a multi-crate content-addressable storage workspace, given only type signatures and public API contracts.	Rust	score (maximize)	false
schemathesis_config_modernization	Schemathesis Config Modernization	Systems & Software Engineering	Implement six modernization targets in Schemathesis: a TOML-based configuration system with auto-discovery, API namespace reorganization, a metrics framework, transport and response abstractions, and a redesigned check registration system.	Python	pass rate	false
schemathesis_datagen_pipeline	Schemathesis Datagen Pipeline	Systems & Software Engineering	Implement eight feature targets in the Schemathesis Python API testing framework, including structured HTTP header generation strategies, coverage-phase hooks, discriminator-aware validation and data generation, and schema-driven code generation fixes.	Python	pass rate	false
schemathesis_reporting_observability	Schemathesis Reporting Observability	Systems & Software Engineering	Implement five targets in Schemathesis: a post-validation hook system, multi-format test report writers (VCR, HAR, JUnit, NDJSON), pytest plugin integration, and schema-branch-aware example generation.	Python	pass rate	false
vliw_kernel_optimization	Vliw Kernel Optimization	Systems & Software Engineering	Optimize a VLIW/SIMD kernel generator for correctness and minimum cycle count on a custom architecture simulator. Hard-coded answers for specific inputs are forbidden.	Python	score (minimize)	false
ad_placement_optimization	Ad Placement Optimization	Combinatorial Optimization	Partition a large integer grid into non-overlapping rectangles, each containing a designated anchor point, maximizing total satisfaction from how closely each rectangle's area matches its target.	C++	score (maximize)	false
apple_incremental_game	Apple Incremental Game	Combinatorial Optimization	Decide each turn whether to invest in machines or collect output in an incremental production game, balancing short-term gains against long-horizon compounding.	Python	score (maximize)	false
equivalence_class_divide_and_conquer	Equivalence Class Divide And Conquer	Combinatorial Optimization	Solve six progressive competitive-programming problems centered on equivalence classes and divide-and-conquer, where techniques from earlier problems inform solutions to harder ones.	C++	score (maximize)	false
grid_turing_robot	Grid Turing Robot	Combinatorial Optimization	Design transition rules and initial coloring for a Turing-like robot on a colored grid to maximize the number of distinct cells visited while minimizing the rule set size.	Python	score (minimize)	false
jagua_nesting_optimization	Jagua Nesting Optimization	Combinatorial Optimization	Improve a Rust-based 2D irregular bin packing optimizer for non-convex polygonal pieces. Solution geometry is independently verified; improvements below a minimum threshold receive no credit.	Rust	score (maximize)	false
molecular_self_assembly	Molecular Self Assembly	Combinatorial Optimization	Schedule bonding operations over discrete time steps to assemble atoms into a specified number of connected molecules, respecting spatial proximity and temporal ordering constraints.	Python	score (maximize)	false
order_addition_permutation_optimization	Order Addition Permutation Optimization	Combinatorial Optimization	Find a permutation of 1,000 elements that minimizes a black-box cost function, using metaheuristic search (simulated annealing, genetic algorithms, local search) without access to the cost function's internals.	Python	score (maximize)	false
smt_solver	Smt Solver	Combinatorial Optimization	Build an SMT solver from scratch for four quantifier-free theories (uninterpreted functions, linear real and integer arithmetic, and their combination). External SMT solvers are forbidden; model witnesses are independently validated.	Python	score (maximize)	false
treant_forest	Treant Forest	Combinatorial Optimization	Strategically place obstacles in a grid maze to maximize the shortest-path length between start and goal, or block the path entirely.	Python	score (maximize)	false
tree_block_partitioning	Tree Block Partitioning	Combinatorial Optimization	Solve six progressive problems on tree decomposition and block partitioning, where algorithmic ideas discovered in simpler variants transfer to harder ones.	C++	score (maximize)	false
triangulation_coloring_optimization	Triangulation Coloring Optimization	Combinatorial Optimization	Minimize a cost function over a triangulation by jointly recoloring vertices and flipping edges, where the dominant term is a quadratic penalty on monochromatic (``ugly'') triangles.	Python	score (minimize)	false
vehicle_routing_time_windows	Vehicle Routing Time Windows	Combinatorial Optimization	Implement a capacitated vehicle routing solver with time windows for Solomon-style benchmarks. Scored against best-known solutions on vehicle count and total travel distance.	Python	score (maximize)	false
vibrating_path_graph_coloring	Vibrating Path Graph Coloring	Combinatorial Optimization	Color graph vertices and selectively remove edges to minimize a cost that penalizes both removed edges and monochromatic surviving edges.	Python	score (minimize)	false
warehouse_forklift_routing	Warehouse Forklift Routing	Combinatorial Optimization	Route a forklift in a grid warehouse to receive goods arriving in random order, store them, and dispatch them in sequential order, minimizing total movement.	Python	score (minimize)	false
wireless_electricity_layout	Wireless Electricity Layout	Combinatorial Optimization	Position wire segments on a 2D plane to deliver wireless electricity from two fixed source plates to thousands of cities, minimizing a quadratic cost over city-to-wire distances and wire displacements while avoiding short circuits.	C++	score (minimize)	false
college_english_exam_bank	College English Exam Bank	Professional Knowledge Work	Produce five parallel examination papers with answer keys for a college English course, plus a blueprint table and an overlap self-check matrix ensuring cross-paper diversity meets pedagogical thresholds.	Python	score (maximize)	true
cta_risk_budget_optimization	Cta Risk Budget Optimization	Professional Knowledge Work	Build a complete CTA multi-strategy futures trading system: multiple signal classes, dynamic risk budgeting, a multi-currency backtest engine with transaction costs, drawdown control, and performance attribution.	Python	score (maximize)	false
k12_math_recommendation	K12 Math Recommendation	Professional Knowledge Work	Build a knowledge-tracing and question-recommendation system from hundreds of thousands of student interaction records, evaluated on prediction accuracy, mastery calibration, learning gain, and pedagogical constraint satisfaction.	Python	score (maximize)	false
portfolio_risk_calibration	Portfolio Risk Calibration	Professional Knowledge Work	Implement a multi-module portfolio management system (risk calibration, constrained optimization, execution cost modeling, dynamic rebalancing) for a cross-asset ETF portfolio. Evaluated out-of-sample on risk-adjusted return metrics.	Python	score (maximize)	false
carleson_formalization	Carleson Formalization	Formal Math & Theorem Proving	Fill proof obligations in the Lean 4 formalization of Carleson's theorem on pointwise convergence of L^2 Fourier series. Transitive axiom checking ensures no dependence on unproved prerequisites.	Lean 4	pass rate	false
combinatorial_games_formalization	Combinatorial Games Formalization	Formal Math & Theorem Proving	Resolve proof obligations in a Lean 4 formalization of combinatorial game theory, covering surreal numbers, game arithmetic, and the Sprague-Grundy theorem.	Lean 4	pass rate	false
flt_regular_formalization	Flt Regular Formalization	Formal Math & Theorem Proving	Resolve proof obligations in a Lean 4 formalization of Fermat's Last Theorem for regular primes via Kummer's cyclotomic theory. Top-level results earn no credit unless foundational prerequisites are also fully proved.	Lean 4	pass rate	false
lean_analysis_proofs	Lean Analysis Proofs	Formal Math & Theorem Proving	Complete proof obligations across a multi-file Lean 4 project formalizing results in real and functional analysis. Proofs are checked transitively: a theorem counts only if its entire dependency chain is fully proved.	Lean 4	pass rate	false
new_foundations_consistency	New Foundations Consistency	Formal Math & Theorem Proving	Complete proof obligations in the ConNF Lean 4 project formalizing the consistency of Quine's New Foundations, involving permutation models and tangled type theory.	Lean 4	pass rate	false
ordinal_notation_well_foundedness	Ordinal Notation Well Foundedness	Formal Math & Theorem Proving	Construct well-foundedness proofs for ordinal notation systems in Coq, involving Cantor Normal Form and ordinal arithmetic.	Coq	score (maximize)	false
pfr_formalization	Pfr Formalization	Formal Math & Theorem Proving	Resolve proof obligations in the Lean 4 formalization of the Polynomial Freiman–Ruzsa conjecture (Gowers–Green–Manners–Tao 2023), involving Shannon entropy, Ruzsa distance, and subgroup covering arguments.	Lean 4	pass rate	false
sphere_eversion_formalization	Sphere Eversion Formalization	Formal Math & Theorem Proving	Complete proof obligations in a Lean 4 formalization of sphere eversion, spanning smooth immersions, jet bundles, ample differential relations, and convex integration.	Lean 4	pass rate	false
anchorhead_text_adventure	Anchorhead Text Adventure	Interactive Games & Simulators	Play the Lovecraftian interactive fiction game Anchorhead via an HTTP API, sending text commands and receiving prose observations. Scored by peak in-game score, reflecting progression through the multi-day narrative and puzzle chain.	Python	game score	false
dcss_dungeon_ai	Dcss Dungeon Ai	Interactive Games & Simulators	Write a Lua bot for Dungeon Crawl Stone Soup that autonomously explores, fights, and descends dungeon levels as a Minotaur Berserker under a wall-clock time budget. Scored by mean in-game score across multiple runs.	Python	score (maximize)	false
nethack_dungeon_agent	Nethack Dungeon Agent	Interactive Games & Simulators	Implement a decision policy for NetHack via the NLE harness, parsing ASCII map observations and stat vectors to navigate, fight, and survive across multiple procedurally generated runs.	Python	score (maximize)	false
openrct2_theme_park_ai	Openrct2 Theme Park Ai	Interactive Games & Simulators	Write a JavaScript plugin for OpenRCT2 that autonomously builds rides, hires staff, sets pricing, and grows park company value across multiple scenarios of increasing complexity.	Python	score (maximize)	false
openttd_transport_ai	Openttd Transport Ai	Interactive Games & Simulators	Write an AI script for OpenTTD that builds road, rail, and air transport networks to connect towns and industries and grow company value across diverse procedurally generated maps.	Python	score (maximize)	false
trinity_text_adventure	Trinity Text Adventure	Interactive Games & Simulators	Play Infocom's Trinity via an HTTP game API. The game requires precise object manipulation and understanding of symbolic and temporal clues across interconnected zones.	Python	game score	false
tryst_text_adventure	Tryst Text Adventure	Interactive Games & Simulators	Play Tryst of Fate via an HTTP game API. The branching narrative with irreversible choices requires strategic exploration to reach high-scoring endings.	Python	game score	false
wesnoth_tactical_ai	Wesnoth Tactical Ai	Interactive Games & Simulators	Write tactical AI logic for Battle for Wesnoth that defeats the built-in AI through custom recruitment, focus-fire targeting, terrain exploitation, and village-capture timing across multiple maps.	Python	score (maximize)	false

EdgeBench

Overview

EdgeBench is a benchmark of 134 real-world tasks for evaluating how autonomous AI agents learn from real-world environments. Instead of measuring one-shot performance, EdgeBench places agents in executable task environments with realistic, multi-level feedback and lets them iterate for 12+ hours per task — tracking the full trajectory of improvement, not just the final score. We publicly release 51 tasks along with the full evaluation framework.

Analyzing ~38,000 hours of agent interaction on all 134 tasks, we find that performance follows a log-sigmoid scaling law as a function of interaction time ($R^2 = 0.998$). See the tech report for details.

Log-sigmoid scaling fit across 134 tasks

Leaderboard

Full Benchmark (134 tasks)

Model	@2h	@4h	@6h	@8h	@10h	@12h
Claude Opus 4.8	39.0	45.7	48.1	49.8	50.9	51.3
GPT-5.5	36.8	42.1	44.5	46.3	47.6	48.4
GPT-5.4	29.7	34.0	36.5	38.0	38.9	39.3
GLM-5.1	26.0	30.4	32.9	34.9	36.5	37.4
DS-V4-Pro	23.3	27.1	29.0	29.9	30.9	31.0

Category Scores @12h (134 tasks)

Model	Scientific & ML	Systems & SE	Optimization	Knowledge	Formal	Games
Claude Opus 4.8	48.5	67.4	36.5	47.0	55.0	39.3
GPT-5.5	44.3	65.0	33.6	45.7	50.0	39.1
GPT-5.4	33.5	54.1	27.9	38.8	40.8	29.0
GLM-5.1	33.8	50.9	26.4	43.5	24.6	29.3
DS-V4-Pro	30.0	43.0	21.5	37.0	14.1	16.9

Open-Source Subset (51 tasks)

Model	@2h	@4h	@6h	@8h	@10h	@12h
Claude Opus 4.8	33.2	38.4	40.6	41.9	42.9	43.6
GPT-5.5	31.0	35.7	37.9	39.9	41.7	42.7
GPT-5.4	25.1	28.3	30.4	32.2	33.4	34.3
GLM-5.1	21.4	24.2	26.7	28.2	29.1	30.3
DS-V4-Pro	17.1	21.0	22.8	23.5	24.6	25.1

Category Scores @12h (51 tasks)

Model	Scientific & ML	Systems & SE	Optimization	Knowledge	Formal	Games
Claude Opus 4.8	31.8	62.0	38.2	38.7	40.9	39.3
GPT-5.5	27.7	60.5	32.3	38.4	49.0	39.1
GPT-5.4	25.7	50.1	29.9	31.6	30.2	29.0
GLM-5.1	25.7	43.6	26.7	31.0	19.9	29.3
DS-V4-Pro	23.8	37.6	24.1	33.2	12.7	16.9

Per-Task Scores by Time Budget (51 tasks)

Each model cell reports scores at @2h / @4h / @6h / @8h / @10h / @12h. Missing valid results are shown as —.

Task	Category	Opus 4.8	GPT-5.5	GPT-5.4	GLM-5.1	DS-V4-Pro
bipedalwalker_locomotion_rl	Scientific & ML	16.7/20.8/22.4/23.3/23.3/23.3	14.7/14.9/15.2/15.2/16.0/21.0	13.9/13.9/13.9/14.5/14.5/17.5	13.9/20.3/21.5/22.5/22.5/22.5	8.9/14.8/17.6/20.4/20.4/20.6
capecod_plume_reconstruction	Scientific & ML	10.0/15.3/17.3/18.0/18.2/19.9	11.7/13.7/15.1/16.2/16.4/16.4	10.7/11.5/12.2/12.5/12.5/12.6	8.6/9.0/9.2/10.3/10.5/10.9	7.9/8.5/8.5/8.8/8.8/8.8
dabic_gravity_inversion	Scientific & ML	9.5/15.2/15.7/17.4/17.5/17.5	15.9/16.2/16.7/17.0/17.2/17.3	14.6/14.6/15.5/15.5/15.0/15.0	9.2/13.7/16.0/16.5/16.5/17.1	—/12.7/12.7/12.7/13.0/13.8
graph_node_classification	Scientific & ML	59.4/62.7/65.0/65.6/66.5/66.6	54.7/55.1/55.1/55.3/55.9/56.0	54.9/56.2/56.5/56.9/57.5/57.6	49.4/52.3/52.3/52.3/52.3/52.3	46.0/48.2/49.2/51.3/51.7/51.8
ann_vector_search_qps	Systems & SE	26.2/57.0/58.6/58.7/59.4/59.7	22.3/34.3/35.1/36.0/40.0/40.7	27.5/30.2/44.5/45.2/49.7/50.2	6.7/24.4/25.6/25.6/26.1/38.3	9.4/19.6/22.4/22.8/23.8/23.8
arc_compiler_runtime	Systems & SE	49.3/52.0/52.0/52.0/52.0/52.0	55.5/56.5/60.9/70.3/71.0/72.4	45.1/46.5/49.8/49.8/50.0/50.0	47.7/48.0/48.4/48.7/48.7/48.7	40.3/41.7/44.2/44.2/44.2/44.2
exchange_core_throughput	Systems & SE	40.7/57.0/58.5/58.9/59.7/59.7	15.4/37.2/39.9/44.3/51.3/53.2	14.3/40.8/41.0/45.2/46.4/47.3	29.2/43.7/46.5/48.6/50.3/52.6	32.9/33.8/45.0/47.7/48.4/48.6
ffmpeg_swscale_reimplementation	Systems & SE	9.9/17.6/19.8/20.9/21.1/21.1	8.8/14.3/15.1/15.3/15.3/15.3	5.4/8.5/9.4/11.6/13.3/13.9	0.3/0.3/0.4/2.2/2.2/2.2	0.1/1.9/2.0/3.8/3.8/3.8
git_rewrite_in_zig	Systems & SE	22.0/22.8/22.8/22.8/23.1/23.1	16.1/16.9/17.7/18.2/18.2/18.4	9.6/13.8/14.0/14.2/14.2/15.4	12.0/20.2/23.3/23.4/23.4/23.5	8.5/13.5/16.0/17.6/17.8/17.9
integer_compression_codec	Systems & SE	69.4/69.7/74.8/74.9/75.2/75.3	61.1/67.6/73.9/73.9/74.3/74.4	38.6/40.9/41.2/42.2/42.2/42.3	23.5/27.3/28.5/28.7/28.9/28.9	15.9/16.0/16.2/16.2/16.2/16.2
juliet_vulnerability_analyzer	Systems & SE	71.9/74.9/75.4/75.6/75.6/75.6	81.0/83.2/85.4/86.8/87.4/89.8	52.9/66.1/74.3/76.0/76.8/77.2	59.3/60.7/62.8/63.5/63.5/63.5	46.8/63.1/66.1/66.2/66.2/66.2
rust_multicrate_reconstruction	Systems & SE	—/—/—/—/—/—	27.5/42.6/53.1/54.9/57.8/57.8	16.7/19.9/21.3/21.4/21.4/21.4	24.8/24.8/25.2/25.2/37.5/38.5	20.5/21.7/22.7/23.1/23.5/23.6
schemathesis_config_modernization	Systems & SE	82.5/85.0/86.1/87.4/87.4/87.7	79.1/82.2/82.9/83.2/83.6/84.0	67.2/68.8/68.8/71.7/71.7/71.9	58.3/59.7/60.4/61.2/61.7/61.7	54.3/54.3/55.3/55.3/55.3/55.6
schemathesis_datagen_pipeline	Systems & SE	68.0/70.2/70.2/70.2/70.2/70.2	54.6/54.6/56.7/56.7/56.7/56.7	56.6/56.6/56.6/56.6/56.6/56.6	62.1/64.2/64.2/67.0/67.0/67.0	47.9/50.1/52.3/52.3/52.3/52.3
schemathesis_reporting_observability	Systems & SE	73.9/75.6/76.2/76.2/76.2/76.2	76.6/76.6/76.6/76.6/77.1/77.1	70.0/73.7/74.7/75.7/76.2/76.2	61.9/61.9/61.9/61.9/61.9/61.9	59.4/62.4/63.0/63.0/65.0/65.0
vliw_kernel_optimization	Systems & SE	74.0/76.0/77.7/79.5/79.6/80.9	71.6/75.7/77.1/79.5/83.1/85.6	75.7/77.0/77.2/78.7/79.1/79.1	5.6/9.5/27.5/35.0/35.9/35.9	0.2/24.9/28.1/33.0/33.9/34.1
ad_placement_optimization	Optimization	65.2/66.1/66.9/67.1/67.4/67.7	44.0/53.3/59.5/61.6/62.9/62.9	41.8/42.4/43.1/47.7/47.9/48.1	48.7/52.7/53.3/56.5/58.5/58.8	25.5/28.5/35.2/35.8/36.2/36.2
apple_incremental_game	Optimization	42.7/44.9/45.9/48.6/49.9/50.6	26.6/29.8/30.6/32.7/33.1/33.6	28.3/30.3/32.0/33.3/33.9/34.9	19.0/19.0/19.1/19.1/19.1/19.1	19.6/19.7/19.7/19.7/19.7/19.7
equivalence_class_divide_and_conquer	Optimization	11.2/15.3/17.0/20.1/20.8/21.3	11.8/15.5/15.8/21.3/22.2/22.4	14.5/17.0/18.3/18.7/20.2/20.3	3.8/4.2/10.0/8.0/10.6/10.6	0.7/1.8/3.2/3.2/3.4/3.4
grid_turing_robot	Optimization	34.7/37.1/37.3/39.6/40.3/40.3	40.4/41.6/41.9/42.0/42.1/42.2	26.8/26.8/27.2/28.9/28.9/28.9	20.0/21.0/24.6/24.6/24.6/25.7	23.7/24.1/24.1/24.1/24.2/24.2
jagua_nesting_optimization	Optimization	11.2/17.8/24.5/31.4/41.0/44.2	15.9/19.4/20.0/20.6/21.3/21.6	22.4/23.0/23.9/24.0/24.1/24.1	8.9/9.0/10.0/12.2/12.3/12.4	10.7/20.2/23.7/26.7/28.1/28.4
molecular_self_assembly	Optimization	22.4/33.4/34.0/34.1/34.4/34.7	20.2/20.3/20.5/20.7/20.7/20.7	20.8/21.1/21.1/21.5/21.5/21.6	10.0/12.5/12.9/13.0/13.1/13.2	19.4/21.7/21.8/21.8/21.9/21.9
order_addition_permutation_optimization	Optimization	22.6/31.6/34.0/34.4/35.7/36.4	16.7/20.5/21.5/22.4/23.0/23.3	1.6/10.6/13.1/14.0/14.2/14.3	2.0/2.1/23.6/25.8/25.8/33.2	4.6/16.5/17.8/22.9/25.4/30.8
smt_solver	Optimization	10.3/17.4/19.0/23.1/23.3/23.9	7.2/7.8/8.4/8.6/8.6/8.6	6.7/7.9/8.9/9.1/9.1/9.2	2.7/2.7/2.7/2.7/2.7/3.6	1.4/2.8/3.3/3.3/3.3/3.3
treant_forest	Optimization	14.5/15.9/16.1/16.2/16.4/18.0	12.1/14.2/14.9/15.2/15.5/15.6	12.2/12.2/12.7/13.0/13.2/13.3	8.0/11.6/11.7/14.1/14.5/16.9	6.8/8.1/9.7/10.1/12.7/13.5
tree_block_partitioning	Optimization	21.5/30.1/32.4/36.8/37.7/37.7	28.8/31.1/33.0/33.0/35.0/36.4	23.1/26.8/28.8/32.9/34.3/34.3	12.1/15.4/17.1/19.3/20.3/23.4	11.2/11.8/11.9/11.9/14.6/16.1
triangulation_coloring_optimization	Optimization	70.8/71.4/71.9/73.2/73.3/73.4	73.7/74.3/74.5/75.0/75.1/75.2	74.1/74.2/74.3/74.3/74.3/74.3	68.8/71.2/71.6/72.0/72.7/73.0	56.1/58.0/59.0/59.1/59.1/59.3
vehicle_routing_time_windows	Optimization	72.5/72.6/72.9/73.6/73.7/74.0	88.7/89.0/89.4/89.7/89.7/90.8	85.3/88.6/88.7/89.5/89.5/89.6	76.6/76.6/76.6/76.6/76.6/77.9	54.7/76.8/81.9/82.2/82.9/83.1
vibrating_path_graph_coloring	Optimization	19.7/21.1/21.4/22.5/24.5/25.3	10.1/10.5/10.6/10.7/10.7/11.4	18.1/19.4/19.8/23.4/23.6/24.1	9.6/18.3/20.3/22.9/22.9/22.9	12.4/14.4/19.3/19.4/21.8/22.1
warehouse_forklift_routing	Optimization	7.7/9.5/10.4/10.5/11.1/11.2	9.8/11.0/11.8/11.9/12.1/12.6	0.0/0.0/0.0/0.0/0.0/0.0	—/0.0/0.0/0.6/0.7/0.5	0.0/0.0/0.0/0.0/0.0/0.0
wireless_electricity_layout	Optimization	6.5/13.7/14.4/14.5/14.5/14.5	6.2/6.9/7.1/7.1/7.1/7.2	10.9/11.1/11.1/11.1/11.1/11.1	7.2/9.4/6.6/8.1/9.4/9.5	0.0/0.0/0.0/0.0/0.0/0.0
college_english_exam_bank	Knowledge	24.8/28.3/34.8/35.5/35.8/39.8	24.5/35.5/35.5/35.5/37.8/37.8	30.7/30.7/31.3/34.0/34.0/34.5	22.2/26.0/29.3/30.0/32.3/32.5	19.2/21.7/22.5/22.7/29.2/34.7
cta_risk_budget_optimization	Knowledge	42.7/44.8/45.3/45.3/45.3/46.1	43.8/45.8/46.7/46.7/46.7/46.7	46.0/49.0/49.0/49.0/49.8/49.8	38.1/44.8/49.0/49.6/49.6/49.6	44.0/45.6/46.9/46.9/48.1/48.1
k12_math_recommendation	Knowledge	23.6/38.5/41.4/42.0/43.7/44.3	38.5/42.4/42.9/43.5/43.9/44.0	25.9/29.0/30.0/30.8/31.1/31.4	24.8/25.7/31.9/32.5/32.7/32.7	25.6/26.3/26.8/25.7/26.0/26.3
portfolio_risk_calibration	Knowledge	20.1/21.6/23.0/23.6/23.6/24.5	17.3/21.3/22.7/23.5/24.4/25.0	6.0/9.6/10.7/10.7/10.7/10.7	0.0/8.4/8.5/8.9/9.2/9.4	10.4/16.3/16.6/16.7/23.7/23.7
carleson_formalization	Formal	4.3/7.7/11.0/12.7/15.0/16.8	6.0/9.5/13.2/16.5/25.3/26.5	1.8/3.5/4.6/5.4/6.3/7.1	1.0/1.7/2.0/2.2/2.2/2.2	0.8/1.3/2.0/2.0/2.3/2.5
combinatorial_games_formalization	Formal	14.5/23.2/27.6/32.1/34.5/35.5	12.0/18.8/24.6/27.2/33.4/38.2	5.9/8.3/11.5/13.5/16.3/17.8	6.7/9.8/14.3/14.9/16.2/16.2	4.3/6.7/7.3/7.4/7.7/7.8
flt_regular_formalization	Formal	31.0/41.8/50.6/50.6/50.6/50.6	43.7/48.3/50.6/66.7/75.1/75.1	1.5/19.5/28.4/41.8/46.0/48.3	14.4/13.4/16.5/18.8/18.8/38.7	5.7/11.9/14.6/14.9/17.2/17.6
lean_analysis_proofs	Formal	17.9/25.1/28.6/30.2/32.6/33.0	16.8/23.2/28.4/33.9/39.0/42.5	3.6/8.1/10.8/12.9/15.5/16.4	5.2/5.9/5.9/5.9/5.9/5.9	5.8/7.3/8.2/8.8/9.3/9.5
new_foundations_consistency	Formal	28.9/36.2/50.0/62.7/64.2/65.1	13.7/38.2/55.1/56.4/65.1/66.5	3.3/12.2/14.9/20.5/30.7/39.8	2.2/3.3/5.1/21.9/24.6/27.0	2.2/3.4/6.5/7.2/10.5/11.4
ordinal_notation_well_foundedness	Formal	10.6/18.4/24.7/24.7/24.7/24.7	13.7/24.7/24.7/24.7/24.7/24.7	1.2/5.5/13.7/15.3/18.4/21.6	2.0/3.5/5.1/5.9/5.9/5.9	3.5/3.5/4.7/4.7/4.7/4.7
pfr_formalization	Formal	32.4/36.9/38.8/40.2/45.6/46.3	30.7/38.3/41.9/47.6/52.7/60.0	10.2/13.7/27.1/34.0/35.9/38.9	8.3/14.9/22.5/26.5/31.3/33.5	9.9/14.7/16.5/17.8/18.5/19.1
sphere_eversion_formalization	Formal	41.7/47.4/49.1/50.4/54.1/55.4	45.0/51.1/55.0/55.9/56.9/58.5	13.3/20.2/32.7/43.7/50.4/51.4	15.5/24.2/26.7/28.7/30.2/30.2	2.9/14.1/22.3/24.9/28.6/29.3
anchorhead_text_adventure	Games	13.3/19.3/19.7/20.3/22.3/22.3	15.0/26.3/31.7/34.3/35.3/36.3	5.0/11.7/13.0/13.3/14.7/17.7	10.7/17.3/19.7/20.3/20.3/20.3	2.0/6.0/7.3/8.0/12.3/14.7
dcss_dungeon_ai	Games	4.2/4.9/5.9/6.3/6.3/8.3	8.9/9.7/10.0/10.0/13.3/13.4	2.6/5.6/5.6/5.6/6.1/6.1	2.8/3.0/3.3/3.3/5.1/7.6	2.8/3.6/4.4/4.5/5.1/5.7
nethack_dungeon_agent	Games	29.7/35.3/36.7/37.3/41.9/41.9	16.6/17.6/18.1/20.6/21.3/22.5	10.9/14.1/15.2/15.8/17.0/20.4	2.3/2.3/15.3/21.6/21.6/21.6	1.0/1.4/2.9/3.2/3.2/3.3
openrct2_theme_park_ai	Games	24.4/24.4/26.0/26.0/27.5/27.5	28.5/28.6/32.7/37.3/37.4/37.6	23.0/23.1/23.1/23.1/23.1/23.1	35.1/36.2/36.2/36.2/36.2/36.2	24.4/24.4/24.4/26.0/26.0/26.0
openttd_transport_ai	Games	50.0/50.4/50.6/51.7/51.8/52.0	10.1/11.6/13.2/21.9/25.6/28.1	10.8/11.4/11.6/11.9/11.9/11.9	0.0/0.0/0.0/0.0/0.0/0.0	4.8/9.2/9.3/12.3/15.2/15.2
trinity_text_adventure	Games	25.0/28.0/29.3/30.0/30.0/30.0	22.3/26.7/28.7/36.3/36.3/40.0	16.3/19.7/22.7/23.3/23.7/27.0	16.0/18.7/24.3/26.0/26.7/26.7	16.3/16.3/17.7/20.0/20.0/20.3
tryst_text_adventure	Games	18.1/33.8/36.7/40.0/40.0/44.3	32.1/42.4/44.3/48.6/55.2/55.7	19.5/20.0/20.0/31.0/38.6/44.3	18.6/28.6/36.2/40.5/42.9/43.3	8.6/11.4/11.4/11.4/11.4/13.8
wesnoth_tactical_ai	Games	84.0/85.3/87.7/87.7/87.7/88.0	64.7/73.0/76.3/78.0/78.3/79.3	79.7/79.7/80.3/80.3/81.3/81.3	75.7/78.3/78.3/78.3/78.3/78.3	17.0/36.3/36.3/36.3/36.3/36.3

Task Taxonomy

EdgeBench contains 134 realistic, diverse tasks spanning six capability categories, of which 51 are publicly released. Each task is designed as a day-scale challenge with a performance ceiling high enough that no current agent can saturate it. Recorded human expert effort averages 57.2 hours per task (up to 320 hours).

EdgeBench Task Taxonomy

Evaluation Harness: SForge

EdgeBench is powered by SForge, a two-container evaluation harness built for long-horizon agent evaluation. See the SForge documentation for setup and usage instructions.

Citation

If you find EdgeBench useful in your research, please cite our tech report:

@misc{edgebench2026,
  title  = {EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments},
  author = {Deyao Zhu and Xin Zhou and Shengling Qin and Xuekai Zhu and Hangliang Ding and Shu Zhong and others},
  year   = {2026},
  url    = {https://edge-bench.org/paper.pdf},
}

License

EdgeBench task datasets are released under CC BY 4.0.

Contact

To evaluate on the full 134-task suite, please contact zhongshu@bytedance.com.

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