MarketTechPost has released ai2025dave, Its 2025 Analytics platform (available to AI devs and researchers without any signup or login) is designed to transform the year’s AI activity into a queryable dataset spanning model releases, openness, training scale, benchmark performance, and ecosystem participants. MarkTechPost is a California-based AI news platform covering machine learning, deep learning, and data science research.
What’s new in this release
2025 release of ai2025dave Extends coverage in two layers:
- release analyticsFocusing on model and framework launches, license status, vendor activity, and feature level segmentation.
- ecosystem indexIncluding a curated “Top 100” collection that connects models to the papers and the people and capital behind them. This release includes sections dedicated to:
- top 100 research papers
- Top 100 AI Researchers
- Top AI Startups
- Top AI Founders
- Top AI Investors
- funding ideas which connects investors and companies
These indexes are designed to be navigable and filterable, rather than static editorial lists, so teams can explore relationships across artifacts like company, model type, benchmark scores, and release timing.
AI releases in 2025: year level metrics from the Market Map dataset
ai2025daveAn overview of ‘AI releases in 2025’ supported by a structured market map dataset covering 100 tracked releases And 39 active companiesThe dataset normalizes each entry into a consistent schema: name, company, type, license, flagshipAnd release_date,
Key overall indicators in this release include:
- Total Release: 100
- Open Share: 69%is calculated as the combined share of open source And open weight releases (44 and 25 entries respectively), with 31 proprietary release
- Flagship Model: 63Enables to differentiate Frontier Tier launches from derivative or narrow-scope releases
- Active Companies: 39Reflects the concentration of major releases among a relatively fixed group of vendors
Model category coverage is clearly typed in the market map, enabling faceted queries and comparative analysis. delivery included LLM (58), Agentic Model (11), Vision Model (8), Tools (7), Multimodal (6), frame (4), Code Model (2), Audio Model (2)plus Embedding Model (1) And Agent (1),
Key Findings 2025: Changes in category level captured as measurable indicators
Release includes ‘Key Findings 2025’ layer It surfaces year-level changes as measurable slices of the dataset rather than as comments. The forum highlights three recurring technical themes:
- adopt open weightCapturing a growing share of releases with weights available under open source or open weight terms, and the downstream implication is that more teams can benchmark, fine tune, and deploy without vendor locked estimates.
- Agents and devices using the systemTracking the development of hierarchical models and systems around tool usage, orchestration and task execution rather than pure chat interactions.
- Efficiency and Compression2025 reflects the pattern where distillation and other model optimization techniques target increasingly smaller footprints while maintaining competitive benchmark behavior.
LLM Training Data Scale in 2025: Token Scale with Timeline Alignment
A dedicated visualization track LLM training data scale in 2025scattered 1.4T to 36T tokens and aligning the token budget to a release timelineBy encoding the token scale and date in a single view, the platform makes it possible to compare how vendors are allocating training budgets over time and how the extreme scale relates to the observed benchmark results,
Performance Benchmarks: Benchmark Generalized Scoring and Inspection
analytics section contains one performance benchmark see and one intelligence index Derived from standard assessment axes, including mmlu, HumanEvalAnd GSM8KIt is not intended to replace function specific assessments, but to provide a consistent baseline to compare vendor releases when public reporting varies in format and completeness,
The platform highlights:
- Ranked Performance Summary for quick scanning
- per benchmark column To explore tradeoffs (for example, coding optimized models that detract from logic-centric performance)
- export control To support downstream analysis workflows
Model Leaderboard and Model Comparison: Operational Evaluation Workflow
To reduce the friction of model selection, ai2025dave These include:
- A model leaderboard which collects scores and metadata for the comprehensive 2025 model set
- A model comparison A view that enables side-by-side evaluation of benchmarks and features with searching and filtering to create shortlists based on vendor, type and openness.
These workflows are designed for engineering teams that need a structured comparison surface before committing to integration, estimating expenses, or fixing pipelines.
Top 100 Index: Papers, Researchers, Startups and Investors
Beyond model tracking, release extends For ecosystem mapping. The platform adds a navigable “Top 100” module for:
- research paperProviding an entry point into the key technical work shaping 2025 systems
- AI researcherPresented as a non-ranked, evidence-supported index with convention-based references
- AI Startups and FoundersEnabling connection between product direction and release systems
- AI investors and fundingEnabling analysis of capital flows around models and equipment categories
Availability
Updated platform now available ai2025dave And you don’t need any signup or login to access the platform. The release is designed to support both fast scanning and analyst grade workflows, including normalized schema, typed categories, and exportable views for quantitative comparisons rather than descriptive browsing.
Asif Razzaq Marktechpost Media Inc. Is the CEO of. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. Their most recent endeavor is the launch of MarketTechPost, an Artificial Intelligence media platform, known for its in-depth coverage of Machine Learning and Deep Learning news that is technically robust and easily understood by a wide audience. The platform boasts of over 2 million monthly views, which shows its popularity among the audience.
