| 1 |
| Ecosystem | 0 | 1 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $5/mo (Mini) |
| Capabilities | 8 decomposed | 14 decomposed |
| Times Matched | 0 | 0 |
Aggregates 2,500 exam questions sourced from 100+ named contributors across academic disciplines through a collaborative curation process. Questions are vetted through a bug bounty program (closed 03/21/2025) that identified and removed searchable/contaminated items, with replacements integrated into the final dataset. The compilation represents a snapshot of expert consensus on difficult, knowledge-testing problems designed to challenge AI reasoning across domains.
Unique: Implements post-hoc contamination mitigation through a formal bug bounty program (03/21/2025) that identified and replaced searchable questions before finalization, addressing a critical gap in benchmark validity that most static benchmarks ignore. The collaborative curation model involves 100+ named contributors from diverse institutions rather than a single lab, creating distributed expertise validation.
vs alternatives: Differs from static benchmarks (MMLU, ARC) by actively removing known contamination via bug bounty rather than assuming training data isolation; differs from rolling benchmarks (HELM) by providing a fixed 2,500-question snapshot with explicit Nature publication (01/28/2026) rather than continuous updates.
Provides HLE-Rolling, a dynamic fork released 10/08/2025 that accepts ongoing question contributions from the community via email submission to agibenchmark@safe.ai. Contributors can propose new exam questions that are integrated into a living version of the benchmark with update logs. This enables continuous evolution of the benchmark as new domains emerge or expert consensus shifts, while maintaining the original 2,500-question snapshot as a fixed reference point.
Unique: Decouples the fixed peer-reviewed benchmark (2,500 questions, Nature publication) from a rolling community version (HLE-Rolling) that accepts contributions via email, enabling continuous evolution without requiring full revalidation. This dual-version approach allows researchers to use the stable snapshot for reproducibility while community members drive innovation in the rolling version.
vs alternatives: Combines the reproducibility of static benchmarks with the adaptability of rolling benchmarks, whereas most benchmarks choose one approach (MMLU is static; HELM is rolling but centrally managed). The email-based contribution system is simpler than GitHub-based workflows but less transparent than formal peer review.
Exposes the 2,500-question benchmark via HuggingFace Datasets library under the dataset ID `cais/hle`, enabling one-line programmatic loading via `load_dataset('cais/hle')`. This integration provides standardized data format compatibility with the HuggingFace ecosystem, allowing researchers to load, filter, and evaluate models using standard HF evaluation frameworks without custom data pipelines. The dataset is versioned and hosted on HuggingFace Hub infrastructure.
Unique: Leverages HuggingFace Datasets' Arrow-backed columnar storage and Hub infrastructure for efficient data loading and versioning, rather than distributing raw JSON/CSV files. This enables automatic caching, version pinning, and compatibility with HF Evaluate and Transformers libraries without custom integration code.
vs alternatives: Faster and more reproducible than downloading raw files from GitHub (no manual versioning); more ecosystem-integrated than providing only a GitHub link, as it works seamlessly with HF Evaluate and other standard tools. However, it locks users into the HF ecosystem and adds a dependency on HF Hub availability.
Provides HLE-Rolling Live Submission Dashboard where researchers can submit model predictions and view real-time rankings. The submission process is email-based (agibenchmark@safe.ai) with an unspecified format and evaluation timeline. The dashboard aggregates results across submitted models and displays comparative performance, enabling researchers to benchmark their models against peers and track progress over time. Submission mechanics, evaluation latency, and result publication policy are not documented.
Unique: Implements a rolling leaderboard tied to HLE-Rolling's dynamic question updates, meaning leaderboard rankings may shift as new questions are added by the community. This differs from static leaderboards (MMLU, ARC) where rankings are stable across evaluation runs, introducing temporal dynamics where older submissions may be re-evaluated against expanded question sets.
vs alternatives: Provides public visibility and competitive incentives for model evaluation, whereas many benchmarks only publish results in papers. However, the email-based submission system is less transparent and scalable than GitHub-based leaderboards (e.g., OpenCompass) or web-based submission portals with automated evaluation.
Implements a formal bug bounty program (closed 03/21/2025) that incentivizes researchers to identify questions in the benchmark that are searchable in public training data or otherwise contaminated. Identified questions are flagged, removed from the final 2,500-question set, and replaced with new questions. This post-hoc contamination mitigation approach addresses a critical validity threat by explicitly removing known leakage risks before publication, rather than assuming training data isolation.
Unique: Formalizes contamination detection as a structured, incentivized process rather than assuming it away or addressing it only in post-hoc analysis. By closing the bug bounty before publication and replacing flagged items, the benchmark provides explicit evidence of contamination awareness and remediation, increasing confidence in validity compared to benchmarks that ignore the issue.
vs alternatives: More rigorous than benchmarks that ignore contamination (MMLU, ARC); less comprehensive than continuous contamination monitoring (HELM's rolling updates). The bug bounty approach is transparent and community-driven but time-limited, whereas continuous monitoring would catch contamination in models trained after the benchmark's publication.
The benchmark is published in Nature (Nature 649, 1139–1146, 01/28/2026), providing formal peer review and editorial validation of the benchmark's methodology, validity, and results. This publication signals that the benchmark has undergone rigorous scrutiny by domain experts and meets standards for reproducibility and scientific rigor. The Nature publication establishes the benchmark as a citable reference point for AI evaluation and provides methodological transparency through the peer-reviewed paper.
Unique: Achieves publication in a top-tier multidisciplinary journal (Nature) rather than a specialized AI conference, signaling that the benchmark's design and validity are of interest to the broader scientific community. This differs from most AI benchmarks (MMLU, ARC, HELM) which are published in AI-specific venues, providing cross-disciplinary validation.
vs alternatives: Nature publication provides higher prestige and broader scientific credibility than conference papers or preprints; however, it also means the benchmark is evaluated against standards for biological, physical, and social sciences, not just AI evaluation practices. The peer review process may be slower and more conservative than rapid iteration in the AI community.
Aggregates exam questions from 100+ named contributors spanning diverse academic institutions and disciplines. The curation process involves distributed expertise validation where questions are proposed by domain experts and vetted through the bug bounty and editorial process. This collaborative approach ensures breadth of coverage across disciplines and reduces single-lab bias compared to benchmarks created by a single research team. Contributor affiliations and discipline distribution are documented but not detailed in available materials.
Unique: Distributes curation across 100+ named contributors from diverse institutions rather than centralizing question creation in a single lab, reducing single-perspective bias and enabling domain-specific expertise validation. The collaborative model is more transparent about contributor identity than benchmarks created by anonymous crowdsourcing or single teams.
vs alternatives: Broader expertise than single-lab benchmarks (MMLU, ARC created by specific teams); more transparent contributor attribution than crowdsourced benchmarks (which often anonymize workers). However, distributed curation may introduce inconsistency in question quality or difficulty compared to centralized editorial control.
Provides a stable, finalized set of 2,500 exam questions (as of 04/03/2025) that serves as the reference benchmark for reproducible evaluation. This fixed snapshot is distinct from the rolling HLE-Rolling version and enables researchers to conduct evaluations that can be exactly reproduced by other teams using the same question set. The snapshot is versioned and published in Nature, establishing it as a canonical reference point for AI evaluation.
Unique: Decouples the fixed reference benchmark (2,500 questions, Nature publication, reproducible) from the rolling version (HLE-Rolling, community contributions, evolving). This dual-version approach allows researchers to use the stable snapshot for reproducible comparisons while the rolling version evolves with community input, balancing reproducibility and adaptability.
vs alternatives: Provides reproducibility guarantees that rolling benchmarks (HELM) cannot offer, since HELM's question set changes over time. However, it sacrifices adaptability compared to rolling benchmarks, potentially becoming outdated as AI capabilities advance. The fixed snapshot is more reproducible than GitHub-based benchmarks without version pinning.
Converts text prompts describing website requirements into complete, multi-page responsive website layouts with copy, images, and animations in seconds. The system ingests natural language descriptions (e.g., 'three unique landing pages in dark mode for a modern design startup'), processes them through an undisclosed LLM pipeline, and outputs design variations as editable React-compatible components in the visual editor. Generation appears to be single-pass without iterative refinement loops, producing immediately-editable designs rather than requiring approval workflows.
Unique: Generates complete multi-page websites with layout, copy, images, and animations from single text prompts, outputting directly into a Figma-quality visual editor where designs remain fully editable rather than locked outputs. Most competitors (Wix, Squarespace) use template selection; Framer generates custom layouts per prompt.
vs alternatives: Faster than hiring a designer and more customizable than template-based builders, but slower and less flexible than human designers for complex brand requirements.
Browser-based visual design interface with design-tool-grade capabilities including responsive layout editing, effects/interactions/animations, shader effects (Holo Shader, Chromatic Aberration, Logo Shaders), and real-time multi-user collaboration. The editor supports role-based permissions (viewers read-only, editors can modify), direct copy editing on published pages, and simultaneous editing by multiple team members. Built on React component architecture allowing both visual design and custom code insertion without leaving the editor.
Unique: Combines Figma-level visual design capabilities with direct website publishing and custom React component integration in a single tool, eliminating the designer→developer handoff. Includes proprietary shader effects library (Holo, Chromatic Aberration) not available in standard design tools. Real-time collaboration uses Framer's infrastructure rather than relying on external sync services.
More design-capable than Webflow (which prioritizes no-code logic) and more publishing-integrated than Figma (which requires export to separate hosting), but less feature-rich for complex interactions than Webflow's visual logic builder.
Framer scores higher at 82/100 vs Humanity's Last Exam at 62/100.
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Enables creation and management of website content in multiple languages with separate content variants per locale. Available as a Pro-tier add-on with undisclosed pricing. Allows content creators to maintain language-specific versions of pages, CMS items, and copy. Implementation details (language detection, URL structure, fallback behavior, supported languages) are not documented.
Unique: Integrates multi-language content management directly into the CMS and visual editor, allowing designers to manage language variants without external translation tools. Content structure is shared across languages; only content is localized.
vs alternatives: Simpler than Contentful with language variants because no separate content model configuration required, but less flexible for complex localization workflows or translation management.
Enables one-click rollback to previous website versions, allowing teams to quickly revert breaking changes or problematic updates. Available on Pro tier and above. Maintains version history of published sites with ability to restore any previous version. Implementation details (version retention policy, automatic snapshots, granular change tracking) are not documented.
Unique: Provides one-click rollback directly in the publishing interface without requiring Git or version control knowledge. Automatic version snapshots are created on each publish. Most website builders require manual backups or external version control; Framer includes it natively.
vs alternatives: Simpler than Git-based workflows for non-technical users, but less granular than Git for selective rollback of specific changes.
Provides a server-side API for programmatic access to Framer sites, CMS content, and site management operations. Listed in product updates but not documented in detail. Capabilities, authentication, rate limits, and supported operations are unknown. Likely enables external systems to read/write CMS data, trigger deployments, or manage site configuration.
Unique: Provides server-side API access to Framer sites and CMS, enabling external integrations and automation. Specific capabilities unknown due to lack of documentation, but likely enables content synchronization with external systems.
vs alternatives: Unknown without documentation, but likely enables deeper integrations than visual-only builders like Wix or Squarespace.
Enables password protection of individual pages or entire sites, restricting access to authorized users only. Available on Basic tier and above. Allows teams to share draft content or restricted pages with specific audiences without making them publicly accessible. Implementation details (password hashing, session management, per-page vs site-wide protection) are not documented.
Unique: Integrates password protection directly into the publishing interface without requiring external authentication services. Available on Basic tier, making it accessible to all users. Simple password-based approach is easier than OAuth or SAML for non-technical users.
vs alternatives: Simpler than OAuth-based authentication for quick access control, but less secure for sensitive data because password-based protection is weaker than multi-factor authentication.
Integrated content management system supporting collections (content types), items (individual records), and relational data linking across collections. The CMS supports dynamic filtering of content on pages, multi-locale content variants (Pro add-on), and auto-publish/staging workflows. Data is stored in Framer's infrastructure with tiered limits: 1 collection/1,000 items (Basic), 10 collections/2,500 items (Pro), 20 collections/10,000 items (Scale). Relational CMS (linking between collections) is Pro-tier and above. Content can be edited directly on published pages without rebuilding.
Unique: Integrates CMS directly into the visual editor with no separate admin interface, allowing designers to manage content structure and pages in one tool. Supports relational data linking between collections (Pro+) and direct on-page editing of published content without rebuilds. Most website builders separate CMS from design; Framer unifies them.
vs alternatives: Simpler than Contentful or Strapi for non-technical users because CMS structure is defined visually, but less flexible for complex data models or external integrations.
One-click publishing of websites to Framer-managed global CDN with automatic responsive optimization across devices. Supports custom domain connection (free .com on annual plans), Framer subdomains, staging environments (Pro+), instant rollback (Pro+), site redirects (Pro+), and password protection (Basic+). Hosting includes 20 CDN locations on Basic/Pro tiers and 300+ locations on Scale tier. Bandwidth limits are 10 GB (Basic), 100 GB (Pro), 200 GB (Scale) with $40 per 100 GB overage charges. Page limits are 30 (Basic), 150 (Pro), 300 (Scale) with $20 per 100 additional pages.
Unique: Integrates hosting, CDN, and staging directly into the design tool with one-click publishing, eliminating separate hosting provider setup. Automatic responsive optimization and global CDN distribution are built-in rather than requiring external services. Staging and rollback are native features, not add-ons.
vs alternatives: Simpler than Vercel/Netlify for non-technical users because no Git/CI-CD knowledge required, but less flexible for complex deployment pipelines or custom server logic.
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