| Ecosystem | 0 | 1 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $5/mo (Mini) |
| Capabilities | 12 decomposed | 14 decomposed |
| Times Matched | 0 | 0 |
Evaluates multimodal models' ability to interpret visual mathematical representations (geometry diagrams, statistical charts, scientific figures) and perform compositional reasoning combining visual perception with mathematical problem-solving. The benchmark uses a curated dataset of 6,141 examples sourced from 28 existing multimodal datasets plus 3 newly created datasets (IQTest, FunctionQA, PaperQA), with questions presented in multiple-choice and free-form generation formats. Scoring uses exact-match accuracy on the testmini subset (1,000 examples) exposed via a public leaderboard.
Unique: Combines visual understanding with mathematical problem-solving across three newly created datasets (IQTest, FunctionQA, PaperQA) plus 28 existing multimodal datasets, totaling 6,141 examples with explicit focus on compositional reasoning where visual perception and mathematical logic must be jointly applied. Unlike single-domain benchmarks, MathVista spans geometry, statistics, and scientific figures, exposing differential model performance across mathematical reasoning types.
vs alternatives: Broader than domain-specific benchmarks (e.g., geometry-only or chart-only) and more rigorous than general vision-language benchmarks because it requires both accurate visual interpretation AND correct mathematical reasoning, not just image captioning or visual QA on non-mathematical content.
Aggregates and curates 6,141 mathematical reasoning examples from 28 existing multimodal datasets and 3 newly created datasets (IQTest, FunctionQA, PaperQA) with standardized question-answer pairs. The curation process involves selecting examples that require compositional visual-mathematical reasoning, extracting or generating questions, and providing auxiliary annotations (OCR text, image captions) for text-only model baselines. Dataset is hosted on Hugging Face and includes a visualization tool for exploring examples by mathematical domain and visual context type.
Unique: Newly created datasets (IQTest, FunctionQA, PaperQA) are purpose-built for compositional visual-mathematical reasoning rather than repurposed from general vision-language tasks. Includes auxiliary annotations (OCR, captions) enabling evaluation of text-only models as baselines, revealing how much visual understanding contributes to performance vs. text-based reasoning alone.
vs alternatives: More comprehensive than single-source mathematical reasoning datasets because it aggregates 28 existing datasets plus 3 new ones, providing broader coverage of visual mathematical domains and reducing bias from any single source's annotation style or problem distribution.
MathVista is released as open-source with dataset available on Hugging Face and code available on GitHub (links provided), enabling researchers to download, analyze, and build upon the benchmark. Open-source release facilitates reproducibility, enables community contributions, and lowers barriers to adoption. Researchers can access raw data, evaluation code, and visualization tools without proprietary restrictions.
Unique: Benchmark is released as open-source with dataset on Hugging Face and code on GitHub, enabling full reproducibility and community access without proprietary restrictions. This open-source approach facilitates adoption and enables researchers to build upon benchmark.
vs alternatives: More accessible than proprietary benchmarks because open-source release enables researchers to download, analyze, and build upon benchmark without licensing restrictions or vendor lock-in.
Aggregates examples from 28 existing multimodal datasets plus 3 newly created datasets (IQTest, FunctionQA, PaperQA) into a unified benchmark with standardized question-answer format and consistent evaluation protocol. This aggregation approach combines diverse sources (existing datasets covering various visual-mathematical domains plus new datasets targeting specific reasoning types) into a single coherent benchmark. Standardization enables fair comparison across models and reduces bias from any single source's annotation style or problem distribution.
Unique: Aggregates 28 existing datasets plus 3 new datasets into unified benchmark with standardized format, combining diverse sources to reduce bias from any single source. This aggregation approach is more comprehensive than single-source benchmarks but introduces complexity in managing source bias and ensuring consistent quality.
vs alternatives: More comprehensive than single-source benchmarks because it combines diverse sources covering multiple visual-mathematical domains, reducing bias from any single dataset's annotation style or problem distribution.
Maintains a public leaderboard (testmini subset, 1,000 examples) tracking multimodal model performance on mathematical reasoning tasks with exact-match accuracy as the primary metric. The leaderboard displays rankings of models (GPT-4V at 49.9%, Gemini Ultra, Bard at ~34.8%, and others) and enables comparison of model capabilities across visual mathematical domains. Leaderboard is updated as new model submissions are evaluated, providing a living benchmark of progress in multimodal mathematical reasoning.
Unique: Leaderboard focuses specifically on mathematical reasoning (not general vision-language tasks) and exposes performance gaps between SOTA models (GPT-4V at 49.9%) and human performance (~60.3%), demonstrating that even best-in-class models fall short by 10.4 percentage points on compositional visual-mathematical reasoning. This gap motivates continued research and provides a clear target for improvement.
vs alternatives: More specialized than general vision-language leaderboards (e.g., MMVP, LLaVA-Bench) because it focuses on mathematical reasoning where visual understanding and mathematical logic must be jointly applied, not just image captioning or visual QA on non-mathematical content.
Provides OCR-extracted text and image captions for each visual example, enabling evaluation of text-only models (e.g., GPT-4 without vision) as baselines on visual mathematical reasoning tasks. This allows researchers to isolate the contribution of visual understanding vs. text-based reasoning by comparing text-only model performance (using OCR + captions) against multimodal model performance (using images). The auxiliary annotations reveal whether models can solve mathematical problems from text descriptions alone or require direct visual interpretation.
Unique: Enables ablation studies isolating the contribution of visual understanding by providing OCR and caption text alongside images. This allows direct comparison of text-only model performance (using OCR + captions) vs. multimodal model performance (using images), revealing whether mathematical reasoning requires direct visual interpretation or can be solved from text descriptions alone.
vs alternatives: More rigorous than benchmarks without text-only baselines because it quantifies the performance gap attributable to visual understanding, not just reports multimodal model accuracy. This ablation approach is standard in vision-language research but often missing from mathematical reasoning benchmarks.
Enables analysis of model performance across distinct mathematical domains (geometry, statistics, scientific figures) and visual context types, revealing which reasoning types and visual representations challenge models most. The benchmark structure supports stratified evaluation where accuracy can be computed separately for each domain, allowing researchers to identify capability gaps (e.g., models may excel at statistics but struggle with geometry). Documentation mentions performance varies significantly across mathematical reasoning types and visual context types, though specific breakdowns are not provided in public leaderboard.
Unique: Benchmark structure explicitly spans multiple mathematical domains (geometry, statistics, scientific figures) rather than focusing on single domain, enabling analysis of whether model capabilities generalize across mathematical reasoning types or are domain-specific. Documentation indicates performance varies significantly across domains, but detailed breakdowns are not published, requiring researchers to conduct their own analysis.
vs alternatives: More comprehensive than domain-specific benchmarks (e.g., geometry-only or chart-only) because it enables cross-domain comparison, revealing whether models have general visual-mathematical reasoning capabilities or domain-specific strengths/weaknesses.
Provides a web-based visualization tool (🔮 Visualize) accessible at https://mathvista.github.io for exploring individual benchmark examples, filtering by mathematical domain and visual context type, and understanding benchmark composition. The tool enables researchers to browse examples, examine model predictions vs. ground truth, and identify patterns in model failures or benchmark difficulty. This interactive exploration complements the leaderboard and dataset documentation by making benchmark content directly inspectable.
Unique: Provides interactive web-based exploration of benchmark examples rather than requiring researchers to download and process dataset locally. This lowers barrier to entry for understanding benchmark content and enables quick identification of example characteristics without programming.
vs alternatives: More accessible than static dataset documentation or leaderboard-only benchmarks because it enables interactive exploration and visual inspection of examples, making benchmark content directly inspectable rather than requiring researchers to download and analyze data themselves.
+4 more capabilities
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 MathVista at 64/100.
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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.
+6 more capabilities