Skip to content
JevDirectory.org
CommunitySites & GuidesArticleVerified 2026-09-22

The Year in AI Papers

A browsable atlas of 1,018 AI papers from August 2025 to August 2026, sorted into 24 topic collections with labs, citations, and code links, plus a reproducible cost benchmark for summarizing 1,000 papers.

Category
Sites & Guides
Published by
Community
Author
Added
2026-09-22
Tagscommunitydirectorybenchmarksresearch

Highlights

  • The corpus is 1,000 frozen papers from August 4, 2025 to August 4, 2026 plus 18 verified Together AI papers, for 1,018 total.
  • Topic areas range from Reasoning (177 papers) and Agents (275) to Video and spatial AI (164), Robotics (59), and Safety (35).
  • The 1,000 papers span 30,681 pages and 102.7 million extracted characters; oversized ones use a 50,000-character map-reduce pass.
  • Cost benchmark: DeepSeek V4 Flash summarized all 1,000 papers for $3.99 total ($0.004 each), versus $6.00 for GPT-5.6 Luna and $35.76 for Claude Haiku 4.5.
  • The authors call it a popularity-weighted field guide and cost benchmark, not an exhaustive history or a factual-quality ranking.

Watch out

Neither the site nor its Nutlope/1kpapers repository documents Jev - the published classify-topics script calls Together AI models - and the benchmark measures inference cost only, not factual quality.

More like this

103GitHub stars
An unofficial curated list of Jev use cases, SDKs, tools, and learning resources, paired with madewithjev.com, a directory of builds that reports each author's own cost and latency numbers.
Sites & Guides#community#awesome-list#directory
Communityawesome-jev
A use-case directory of 473 Jev builds, 107 guides, and 8 use cases where each entry links to its source and shows the cost and speed its author reported, with category filters and free tools.
Sites & GuidesArticle#community#directory#use-cases
Community
A community directory of 899 Jev projects refreshed daily from GitHub, with 814 repos plus live sites, articles, and threads, star counts, category filters, a jev-latest spec sheet, and a top-starred list.
Sites & GuidesArticle#community#directory#awesome-list
Community
Back to all resources

From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

The open System One roundup

Jev 发布没几天,开源社区已经开始疯狂复刻了🔥 最值得推荐的五个模型: 1、Laya 421M:原生决策模型,支持 Mac 2、Decider-2B:最像 Jev,基于 Qwen3.5 3、NanoJev 0.6B:专门的 Decision Head 4、Reflex:Qwen3.5 + Direct Logits 5、System-One 4B:专门做概率校准 Show more

小墨同学
小墨同学
@xiaomovps

Jev 刚发布没几天,开源社区就出现了同款🔥 Decider-2B模型,是基于 Qwen3.5-2B 做了特殊调整 它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型 但两者还是有几个明显区别: 1、模型 Jev:闭源 System One Model Decider:Qwen3.5-2B,约 1.9B 参数,Apache 2.0 开源 2、价格

Image
Reply

The launch post

Trading bot, one decision per block

Classifying 1,500 real emails

this model is actually insane at email classification i tested it on 1500 of my own emails to see how well it works and I am blown away

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

Fast browser use with Stagehand

we built blazing fast computer/browser use with Jev + @Stagehanddev. this task cost $0.001 and executed at near instant speed (in a remote browser btw) the loop: observe the page, send a11y tree as state + actions as questions, Jev decides the next action, then Stagehand Show more

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

LLM-as-a-judge, sped up

Jev has spoken. It picked which model is AGI. 20–200x faster. 40–400x cheaper. This could make things like LLM-as-a-judge insanely fast and nearly free. (I tried a bunch of prompts and still didn’t burn through $0.10.)

Image
Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply