Package pull
1.2B/30d
Across 16 of 18 tracked companies
Category read
AI-Buzz tracks 18 Foundation Models companies. Current signals are clearest in package pull, public code usage, and hiring demand. Current leaders include OpenAI, Anthropic, and Cohere. The current snapshot covers 1.2B package downloads per month and 54.0K public importing repos.
Companies
18
Core companies in scope
Package pull
1.2B/30d
16 companies with registry activity
Public code
54.0K
9 companies with imports detected
Hiring
33/30d
3 companies with hiring mentions
Funding
$280.4B
12 companies with disclosed rounds
Lead signals
package pull, public code usage, and hiring demand are the clearest aggregate signals across Foundation Models right now.
Package pull
1.2B/30d
16 of 18 companies show registry usage; OpenAI currently leads.
Public code
54.0K
9 companies show public imports; OpenAI leads.
Hiring demand
33/30d
3 companies appear in tracked HN hiring posts; Anthropic leads.
Reading
package pull and public code are the clearest category-wide signals right now.
Package pull
1.2B/30d
Across 16 of 18 tracked companies
Public code
54.0K
9 companies with imports detected
Hiring demand
33/30d
Across 3 companies in tracked hiring posts
Dependents
44.0K
Across 15 companies with downstream packages
Signal routes
Use the category summary to identify where the signal mix is strongest, then open the company pages behind it.
DAI leader
OpenAI
DAI 88
OpenAI currently leads the overall signal read in Foundation Models.
Hiring leader
Anthropic
DAI 84
Anthropic leads the current hiring signal.
Research brief
AI Developer Adoption Trends: OpenAI, Anthropic Downloads Dip
Use the latest published brief for the market claim, then open the company pages that reinforce or challenge it.
Open research →Company routes
These cards surface the strongest signal mixes, then link straight into the company pages with the underlying detail.
490.4M/30d package pull, 46.1K public repos, and 7/30d hiring mentions.
DAI
88
Package pull
490.4M/30d
Public code
46.1K
Hiring
7/30d
269.5M/30d package pull, 3.7K public repos, and 25/30d hiring mentions.
DAI
84
Package pull
269.5M/30d
Public code
3.7K
Hiring
25/30d
52.2M/30d package pull, 1.4K public repos, and 848 dependents.
DAI
71
Package pull
52.2M/30d
Public code
1.4K
Dependents
848
44.7M/30d package pull, 1/30d hiring mentions, and 810 dependents.
DAI
69
Package pull
44.7M/30d
Hiring
1/30d
Dependents
810
2.4M/30d package pull, 178 dependents, and $20M funding.
DAI
55
Package pull
2.4M/30d
Dependents
178
Funding
$20M
1.2M/30d package pull, 252 public repos, and 69 dependents.
DAI
48
Package pull
1.2M/30d
Public code
252
Dependents
69
374.9K/30d package pull, 4 public repos, and 103 dependents.
DAI
46
Package pull
374.9K/30d
Public code
4
Dependents
103
3.8M/30d package pull, 24 public repos, and 313 dependents.
DAI
45
Package pull
3.8M/30d
Public code
24
Dependents
313
2.1M/30d package pull, 165 dependents, and 173/30d HN mentions.
DAI
41
Package pull
2.1M/30d
Dependents
165
HN
173/30d
353.7K/30d package pull, 1.3K public repos, and 77 dependents.
DAI
40
Package pull
353.7K/30d
Public code
1.3K
Dependents
77
Trend lines
Total tracked HN mentions across companies in this category over time.
HN Mentions grew from 8,496 to 14,464 (+70.2%) over the last 30 days.
Source: Algolia HN Search API | Methodology | CC-BY-NC 4.0
| Date | hn mentions |
|---|---|
| Jan 31, 2026 | 8,496 |
| Mar 2, 2026 | 289 |
| Apr 1, 2026 | 13,789 |
| Apr 6, 2026 | 14,464 |
Cumulative disclosed funding raised by companies in this category over time.
Total Funding grew from $23.8B to $280.4B (+1079.0%) over the last 30 days.
Source: Public records | Methodology | CC-BY-NC 4.0
| Date | funding |
|---|---|
| Jan 31, 2026 | $23.8B |
| Mar 2, 2026 | $282.6B |
| Apr 1, 2026 | $280.4B |
| Apr 6, 2026 | $280.4B |
Comparison table
Sort by the signal that matters most for this category: combined DAI, package pull, public code adoption, hiring demand, or funding depth.
| Company | DAI Score ▼ | Downloads (30d) | Public Code | Hiring | Funding |
|---|---|---|---|---|---|
| OpenAI AI company behind ChatGPT, GPT models, and the OpenAI API | 88 | 490.4M | 46.1K | 7 | $171.7B |
| Anthropic AI safety company behind the Claude model family | 84 | 269.5M | 3.7K | 25 | $58.7B |
| Cohere Enterprise-focused LLM company. Strong in embeddings and RAG. | 71 | 52.2M | 1.4K | - | $1.5B |
| Mistral AI French AI lab building open-weight foundation models. | 69 | 44.7M | - | 1 | $3.2B |
| Voyage AI Embedding models optimized for RAG. High-quality semantic search. | 55 | 2.4M | - | - | $20M |
| EleutherAI Open-source AI research collective behind GPT-NeoX and Pythia | 48 | 1.2M | 252 | - | - |
| Zhipu AI Chinese AI lab behind ChatGLM series of language models | 46 | 374.9K | 4 | - | $356M |
| xAI Elon Musk's AI company. Builds Grok chatbot and foundation models. | 45 | 3.8M | 24 | - | $42.0B |
| DeepSeek AI research lab building open-source reasoning and code models | 41 | 2.1M | - | - | - |
| Aleph Alpha European AI lab building large language models. | 40 | 353.7K | 1.3K | - | $533M |
| Allen AI Nonprofit AI research institute behind OLMo open language models | 39 | 83.8K | 1.1K | - | - |
| AI21 Labs AI company building Jurassic LLMs and Writer platform. | 36 | 252.7K | 70 | - | $252M |
| Reka AI Multimodal AI lab building foundation models for enterprise | 29 | 51.2K | - | - | $58M |
| Moonshot AI Chinese AI lab behind Kimi, a long-context language model assistant | 24 | 87 | - | - | $1.1B |
| Baichuan Chinese AI company building open-source large language models | 2 | 38 | - | - | $1.0B |
| 01.AI AI research lab behind Yi series of open-source language models | - | - | - | - | - |
| Meta Llama Meta's open-weight large language model family | - | - | - | - | - |
| Google Gemini Google's multimodal AI model family and developer platform | - | 311.7M | - | - | - |
Research
Use the brief for the category-level claim, then route back into company pages for the underlying signals.
FAQ
The current DAI leaders in Foundation Models include OpenAI (DAI 88), Anthropic (DAI 84), and Cohere (DAI 71). Use the company pages to inspect the package pull, public code, hiring, and funding signals behind those rankings.
Across 18 tracked companies, current public signals show 1.2B package downloads per month, 44.0K known dependents, 54.0K public importing repos, and 33 recent hiring mentions. Coverage is uneven by company, so the detail pages show which signals are actually present for each one.
Foundation Models AI companies disclose $280.4B in combined funding across 12 tracked companies with known rounds.
The current snapshot tracks 14.5K Hacker News mentions across 13 companies in Foundation Models. Discussion is supportive context rather than the lead signal.
Start with the strongest signal routes: OpenAI leads package pull, OpenAI leads public code usage, and Anthropic leads hiring visibility. Then compare those companies against the full table to see whether the category is concentrated or broad.
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