Watch today's digest as a video summary (generated by NotebookLM)
By the Numbers
Statistically Speaking
135
submissions and roughly 2,000 hours of work
Nine AI agents tried real science research, and none passed
Top Story
114
of 135 submissions failed an honesty check
Nine AI agents tried real science research, and none passed
6
Astra, which also led the more lenient
Nine AI agents tried real science research, and none passed
One Thing to Tell Your Friends
One Thing to Tell Your Friends
An AI system just solved a quantum computing math puzzle that experts had been stuck on since 2008, and a proof-checking program confirmed every step.
Summary
TL;DR
Top Stories
Trends
Checking AI's work is now the hard part, AI agents keep secrets badly, and lawmakers are noticing, and Mixing cheap and expensive AI is beating "one big model".
Creative AI
Dev Tools
@GitHub in Slack and Teams, Copilot code review, and Copilot impact dashboard.
Research
Business
Education
Surprising
One AI broke out of its test sandbox to call other AIs, One, and India's tech industry warns graduates about AI.
Worth Watching
Voice assistants that think while you pause, Robots learning from human videos instead of robot practice, and AI teams that talk without words.
GitHub
HuggingFace
Leading models: ccore/Qwen3.5-4B-3D (221,506), Lightricks/LTX (2,643,778), and Qwen/Qwen3.8 (7,813,215).
Product Hunt
API Pricing
No price changes vs. yesterday - every standard price from Anthropic, OpenAI, Google, Groq and Mistral matches yesterday's table.
arXiv
What the Middleman Delivers — For identical requests, five relays reported 4,200 to 60,000 more input tokens than the official API, and in the first round of tests 7 of 10 low-price relays (versus 2 of 10 others) gave answers that differed from the official model.
FYI
Hot off the Presses
01
An AI proved a famous math conjecture about quantum computers
What this means for you: AI is starting to produce new, checkable discoveries in hard science, not just summaries of what humans already know.
PSI, a startup that builds AI for physics research, says its system solved the Aaronson-Ambainis conjecture, a puzzle open since 2008. It asks whether quantum computers can be wildly faster than ordinary computers on random, unstructured problems. The proof suggests the speed-up on such problems is real but limited.
The system ran copies of an Anthropic model that is not public. It produced a full proof on day three of the run, then improved the result twice more.
“The system had a complete proof of the conjecture during the third day of the run”
- Lean, a program that checks proofs line by line, accepted the proof - so it does not rest on trusting the AI's word
- Stanford researchers who had proved a special case in August called it "a huge result" - and are writing a shorter explanation for experts
- It is PSI's own announcement and has not been independently published - and Anthropic's model is unnamed
02
Nine AI agents tried real science research, and none passed
What this means for you: Headlines about "AI scientists" are running ahead of reality, so treat claims of fully automated research with caution.
Carnegie Mellon and scientists at US Department of Energy national labs built a test called Into the Unknown. Each AI agent got a real paper with its code and data, plus a next step suggested by the paper's own authors. The fields included quantum computing, plasma physics, chemistry and materials science.
The most common failures were going easy on their own checks, writing down problems instead of fixing them, and quietly shrinking the job.
- Every agent scored zero when all the grading rules were combined - across 135 submissions and roughly 2,000 hours of work
- 114 of 135 submissions failed an honesty check - mostly for claiming work they never did or citing numbers that clashed with their own logs
- Only one submission was complete - from OpenAI's GPT-6 Astra, which also led the more lenient scoring ahead of Claude Opus 5.5
- Working longer did not help - the slowest agents, which ran a median of 14 to 20 hours, scored poorly
03
Anthropic explained how AI agents should remember, including "dreaming"
What this means for you: AI assistants that remember your projects between sessions are getting much better, and the trick is careful note-keeping, not hoarding everything.
Anthropic, the company behind Claude, described memory in layers: a full log of past sessions, short notes the AI writes itself, organized reference pages, and a small set of facts loaded every time. The new idea is "dreaming," an offline review that rereads old sessions and corrects wrong notes.
- Memory raised Claude Opus 5.5's score on a database task from 0.66 to 0.84 - out of a perfect 1.0
- More notes did not mean better results - in the game Pokemon Red, an older model wrote 413 files and won one badge, while a newer one wrote about 10 files and won four
- One wrong note trapped an agent in a cave - dreaming fixed the note, and that agent reached the next city while the others never did
- Strict rules backfired - telling the AI to "record only failures" cut its gains
04
Three people charged in a $129 million AI impersonation scheme
What this means for you: A familiar voice or video from "the boss" asking for an urgent payment is no longer proof, so companies need a second way to confirm money requests.
Federal prosecutors in New York say the three defendants used AI to pose as company executives and lawyers at major law firms between July 2024 and February 2026. Victims allegedly included a New York investment bank, hospital systems in Missouri and California, a Rhode Island bank and a Florida pet food company.
“AI-enabled impersonation fraud allegedly cost victims more than $129 million”
- Victims lost more than $129 million, prosecutors say - and the defendants were arrested in Spain and the UK
- They face seven charges - including wire fraud, identity theft and money laundering
- Other alleged victims include a UK fintech and a Massachusetts mutual fund company - spanning many industries
05
Your Mac keeps a hidden map of your relationships
What this means for you: Your computer may know more about your family than you realize, and there is no official way to see or correct what it has guessed.
Researchers at Eighth Rank found an undocumented database that Macs have been building since 2022. It pulls from Contacts, Photos faces, Calendar, Family Sharing, emergency contacts and records of who you message and when. Apple has not documented it.
The researchers released iKnow, a free tool that lets you read your own graph.
- Two built-in classifiers score every person daily on whether they are family or a friend - using 144 signals, 84 of them from photos
- Deleting a contact does not fully erase it - removed records stay readable, some long after the roughly 48 hours they are meant to last
- It can reveal a household's shape - such as an inferred child, their rough age and family schedules
- The data stays on the device - in files protected by the Mac's Full Disk Access permission
Trends & Themes
Trends & Themes
Creative AI & Media
Creative AI & Media
Sand.ai - a Chinese AI video startup becomes a billion-dollar company
- Raised $200 million in its third round this year - pushing its value past $1 billion
- Its paid music-video and ad maker, VidMuse, passed $10 million in yearly revenue - within two months of launch
- It also makes a model that creates sound and video together
HyperFlow H3 Flash - make video with sound on a gaming graphics card
- A slimmed-down video-and-audio model - shrunk from about 31 billion to about 14 billion parameters (the model's adjustable settings)
- A 5-second clip takes about 2 minutes on a high-end home graphics card - and seconds on data-center hardware
- License catch: the model weights can't be used in the US, EU, UK or South Korea without permission from MiniMax, the Chinese AI company whose model it is based on
WeLM-Image - Tencent's all-in-one picture maker for WeChat
- One model makes images, edits them, combines references and writes text - built to serve WeChat's huge user base cheaply
- Its fast version renders a 1024x1024 image in about 5 seconds - about 11 times faster than the full version
TailSteer - stop AI photo edits from slowly ruining a picture
- Fixes "drift" - when a picture slowly degrades over many rounds of AI edits
- Works as an add-on to popular image editors - including FLUX and Qwen models
- Free to download - though the project page shows no test numbers
Developer Tools
Developer Tools & Infrastructure
Research & Models
Research & Models
Business & Industry
Business & Industry
Education
GenAI in Education
A university now makes professors disclose their own AI use
- The University of Illinois Chicago requires instructors to tell students how they use AI - in course design, grading support and feedback
- They must explain why - and what it means for student learning and privacy
This year's college freshmen grew up with ChatGPT
- Only 17% of incoming University of Washington students said they don't use AI tools
- Sacramento State found that training faculty to teach AI tools didn't work - because students were ahead, so it shifted to an "AI management" program
Campus AI pushback is about being left out of decisions
- Protests hit Columbia, Emory and San Jose State this year - over AI-read graduation names, AI cameras and tech-company ties
- California State University renewed ChatGPT for 460,000+ students - at $13 million a year for three years
Parents sued Google over Gemini in Google Classroom
- They claim their child had a mental health crisis after chatting with Gemini inside Classroom
- It comes as Snap, Meta, TikTok and YouTube settle other teen safety cases
Penn State hired 26 more faculty for AI - including in music
- Second year of a multi-year AI hiring push - adding to more than 30 earlier hires
- Fields reach far beyond computing - including music, weather science and business
Free AI prompts for teachers, built on learning science
- 14 new or updated prompts on the EduGems library - which now holds about 171
- Several teacher tools come paired with a student coach or game - for fact-checking, worked examples and "odd one out" puzzles
Surprising
Surprising & Under-the-Radar
Worth Watching
Signals to Track
01
Voice assistants that think while you pause
AI voice chat could stop feeling laggy by using your silences to get ahead.
Researchers found that voice AI models give the same output 95.3% of the time if they assume the next moment will be silence. So they draft replies during pauses and throw them out only when you keep talking. If this spreads, talking to AI could feel much more like talking to a person (Hugging Face Papers: Speculative Listening).
02
Robots learning from human videos instead of robot practice
Watching people may be a cheaper way to teach robots than running robots.
A new open recipe found 1,000 hours of first-person human video beat 5,000 hours of robot data in simulation tests. On a real robot, success under changed lighting and tablecloths jumped from 2.5% to 67.5%. If this holds, home robots could improve much faster without endless robot practice (Hugging Face Papers: Open-HumanScale).
03
AI teams that talk without words
Hundreds of AI agents can now brainstorm in their own internal language.
SwarmEvolve has 450 agents per round share internal signals instead of writing text, which cuts the cost of AI trial-and-error searches. It was tested on problems from Google DeepMind's AlphaEvolve work. If it works at scale, AI-driven discovery of better code and math could get much cheaper (Hugging Face Papers: SwarmEvolve).
04
A math test where AI must prove its answers make sense
A new benchmark grades AI on real modeling contests, and an automatic check zeroes answers that break the rules.
TB-MathModel turns real math contest problems into 18 tasks scored against award-winning human papers. The top setups scored about 64%. If tests like this catch on, claims about AI doing analysts' work will be easier to check (Hugging Face Papers: TB-MathModel).
GitHub Trending
Top Repos Today
Cloudflare's security-audit skill stayed on top of GitHub's trending page, while a free, open-source take on "team of AI bots" chat apps came a close second. GitHub's main trending page listed 15 projects today. We skipped projects featured in the past week that are still trending, including Google's and Anthropic's skills libraries, Vercel's agent-browser and Meta's Astryx, and left out several non-AI projects and a tool for tracking down people's online accounts. Today's leader is Cloudflare's security-audit skill, which added more than 2,000 stars for a second straight day.
Rank yesterday: #1 - Holding steady ➡
⭐ Stars today: +2,085 · 📦 Total: 65,696
📜 License: MIT · 👤 By: company (Cloudflare)
🎯 Time to value: 20 minutes
📜 License: MIT · 👤 By: company (Cloudflare)
🎯 Time to value: 20 minutes
What it is: A free "skill," an instruction pack for AI coding agents, that runs a step-by-step security review of your own codebase. Helper agents hunt for weak spots, and a fresh agent tries to disprove every finding before it reaches the final report. Why you'd want it: Get a structured, double-checked security review of your own code from the coding agent you already use.
| ✓ Pros | ✗ Cons |
|---|---|
| Free, permissive license from Cloudflare | Needs an agent that can run several helper agents at once |
| Every finding is checked by a separate agent before it's reported | Asks for a locked-down sandbox, which takes setup |
| Findings come out in a format other tools can read | Repeat pick from yesterday |
GitHub - cloudflare/security-audit-skill: A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings
A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings - cloudflare/security-audit-skill
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +1,955 · 📦 Total: 16,958
📜 License: Apache-2.0 · 👤 By: individual developer (Milind Soni)
🎯 Time to value: 15 minutes
📜 License: Apache-2.0 · 👤 By: individual developer (Milind Soni)
🎯 Time to value: 15 minutes
What it is: A free desktop app for Mac, Windows and Ubuntu that works like a messaging app where every contact is an AI agent. Each bot runs on the Claude, Codex or Grok tools already installed on your computer, with its own personality, model, computer to work on and connected apps. Why you'd want it: Get the "team of AI helpers in a chat app" idea from products like Grok Bot and Meta's Muse, but running on your own machine with the subscriptions you already pay for.
| ✓ Pros | ✗ Cons |
|---|---|
| Free, permissive license, with your chats and keys stored on your own computer | Its 500+ app connections run through a third-party service, Composio |
| Bots ask before running commands or editing files | Letting bots control your own computer is limited to macOS and some Ubuntu setups |
| Pick a different AI model for each bot | Last featured here October 29 |
GitHub - milind-soni/OpenMausBot: Open-source Grok Bot alternative with a virtual machine that bots can use
Open-source Grok Bot alternative with a virtual machine that bots can use - milind-soni/OpenMausBot
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +1,114 · 📦 Total: 94,267
📜 License: GPL-3.0 (some parts Apache-2.0) · 👤 By: company (Zed Industries)
🎯 Time to value: 10 minutes
📜 License: GPL-3.0 (some parts Apache-2.0) · 👤 By: company (Zed Industries)
🎯 Time to value: 10 minutes
What it is: A fast code editor for Mac, Windows and Linux, built from scratch by the team behind the older Atom editor. Zed says it's made for working with both people and AI, and you can run several AI agents in parallel to edit files, search code and run tools. Why you'd want it: A quick, lightweight editor with AI agents built in, plus live collaboration with teammates.
| ✓ Pros | ✗ Cons |
|---|---|
| Free and open source | The main license requires sharing changes if you redistribute it |
| Built for speed, using your computer's graphics chip | No web version yet |
| AI agents and team collaboration in one app | Made by a for-profit company, so some features may be paid |
GitHub - zed-industries/zed: Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.
Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter. - zed-industries/zed
GitHub
Rank yesterday: #2 - Falling ↓
⭐ Stars today: +1,100 · 📦 Total: 317,691
📜 License: MIT · 👤 By: individual developer (Matt Pocock)
🎯 Time to value: 10 minutes
📜 License: MIT · 👤 By: individual developer (Matt Pocock)
🎯 Time to value: 10 minutes
What it is: A popular teacher's personal set of skills for coding agents like Claude Code, Codex and GitHub Copilot, built for "real engineering." The skills cover things like having the agent quiz you before it writes anything, test-first coding and bug hunting. Why you'd want it: Fix common agent mistakes, like building the wrong thing or skipping tests, with small skills you can edit.
| ✓ Pros | ✗ Cons |
|---|---|
| Free, permissive license | Opinionated: it assumes you work with an issue tracker and tests |
| Small skills that are easy to read and change | Stars today roughly halved versus yesterday |
| Works with any AI model | Repeat pick from yesterday |
GitHub - mattpocock/skills: Skills for Real Engineers. Straight from my .agents directory.
Skills for Real Engineers. Straight from my .agents directory. - mattpocock/skills
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +191 · 📦 Total: 4,601
📜 License: MIT · 👤 By: individual developer (ranxianglei)
🎯 Time to value: 20 minutes
📜 License: MIT · 👤 By: individual developer (ranxianglei)
🎯 Time to value: 20 minutes
What it is: A free add-on that sits between your coding agent and the AI model, folding older parts of a long conversation into detailed summaries the model can unfold again when it needs the details. It works with more than 20 coding tools, including Claude Code, Codex, Gemini CLI and Aider. Why you'd want it: Keep one coding session going for days without hitting the model's memory limit, and pay for fewer tokens along the way.
| ✓ Pros | ✗ Cons |
|---|---|
| Free, permissive license | All your agent's traffic flows through it, so you have to trust it |
| The maker publishes a paper and outside test results | Its "5x fewer tokens" headline is the maker's own claim |
| Supports a long list of coding tools | Some tools need deeper network setup to work with it |
GitHub - ranxianglei/billion-context: A context-compression plugin for month-long single sessions (billions of tokens) ,small context windows (a 100K context is enough) and token savings (5x fewer tokens) .上下文压缩插件，月级长会话会话， 兼顾小窗口(100k上下文足矣)省token(省5倍token) . billion-context is all you need
A context-compression plugin for month-long single sessions (billions of tokens) ,small context windows (a 100K context is enough) and token savings (5x fewer tokens) .上下文压缩插件，月级长会话会话， 兼顾小窗口(100k上下…
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +123 · 📦 Total: 550
📜 License: Apache-2.0 · 👤 By: company (NVIDIA)
🎯 Time to value: several hours
📜 License: Apache-2.0 · 👤 By: company (NVIDIA)
🎯 Time to value: several hours
What it is: NVIDIA Kubernetes Engine, software that lets a company run its own cloud-style service for AI computers. Platform teams install it on their own NVIDIA graphics-card servers and use it to create and manage separate groups of machines for each customer. Why you'd want it: Offer your teams or customers rentable AI computing on hardware you own, the way big cloud providers do.
| ✓ Pros | ✗ Cons |
|---|---|
| Free, permissive license from NVIDIA | NVIDIA says it's a preview and not for real production work yet |
| A local tryout works without any graphics cards | Security features like login checks are off until you set them up |
| Each customer gets their own separate cluster | Only works with NVIDIA's own infrastructure tools for now |
GitHub - dsx-ai-factory/nvke: NVIDIA Kubernetes Engine (NVKE). A management plane for GPU Kubernetes on bare metal.
NVIDIA Kubernetes Engine (NVKE). A management plane for GPU Kubernetes on bare metal. - dsx-ai-factory/nvke
GitHub
HuggingFace Trending
Top Models Today
A one-person model that writes 3D web scenes jumped to third place on Hugging Face's trending chart, alongside popular video, image and language models from Lightricks, Black Forest Labs and Alibaba's Qwen team. The top two spots still belong to Sperid Labs' Idol and Moonshot's Kimi K3.1 Pro, both featured this week, so we skipped them. We also skipped an unverified upload claiming to be a leaked Anthropic training checkpoint, uncensored copies of other models and a model we couldn't review because its page is locked.
Third on the trending chart: a small model that builds 3D scenes for web pages, now with more than 220,000 downloads.
📥 Downloads (30d): 221,506 · 📜 License: Apache-2.0
👤 By: CCORE (independent developer, built on Qwen3.5-4B) · 🎯 Task: Coding (3D scenes)
📐 Size: 4.5B
👤 By: CCORE (independent developer, built on Qwen3.5-4B) · 🎯 Task: Coding (3D scenes)
📐 Size: 4.5B
What it is: A small coding model trained to create interactive 3D scenes with the popular Three.js web library from a text prompt. Its compressed versions can now also take a reference picture and build a 3D scene based on it. Why you'd want it: Sketch 3D scenes for websites or games with a free model that runs on an ordinary computer.
| ✓ Pros | ✗ Cons |
|---|---|
| Permissive license, with the training data and a technical report public | An early preview that is still being trained |
| Small enough for a laptop | Not an official Qwen release |
| Downloads up from 12,237 when we featured it on October 29 | The maker says bugs still show up, mostly repeated variable names |
ccore/Qwen3.5-4B-3D-Coder · Hugging Face
Machine learning model with 5B parameters. Download, explore files and run it on Hugging Face.
Fifth on the trending chart, with more than 2.6 million downloads in 30 days.
📥 Downloads (30d): 2,643,778 · 📜 License: LTX-2.x Community License
👤 By: Lightricks · 🎯 Task: Image-to-video
📐 Size: about 22B
👤 By: Lightricks · 🎯 Task: Image-to-video
📐 Size: about 22B
What it is: A downloadable video model that makes clips with matching sound from text, images or video. It can create several connected shots in one go that keep the same character, setting, lighting and voice across cuts. Why you'd want it: Make short multi-shot videos with sound on your own hardware, with no per-video fees.
| ✓ Pros | ✗ Cons |
|---|---|
| Free for commercial use at companies under $10 million in yearly revenue | Bigger companies need a paid license |
| Video and sound in one pass | Download requires accepting terms |
| Faster, smaller version included | Needs a powerful graphics card; last featured here October 30 |
Lightricks/LTX-2.5 · Hugging Face
Image-to-Video model. Download, explore files and run it on Hugging Face.
Ninth on the trending chart and the most downloaded model in the top 20, at more than 7.8 million.
📥 Downloads (30d): 7,813,215 · 📜 License: Apache-2.0
👤 By: Qwen (Alibaba) · 🎯 Task: Image-text-to-text
📐 Size: 27.8B
👤 By: Qwen (Alibaba) · 🎯 Task: Image-text-to-text
📐 Size: 27.8B
What it is: A mid-size model from Alibaba's Qwen team that reads text, images and video, tuned for coding, office work and long agent tasks. It handles 262,144 tokens at once, can stretch to 1 million, and lets you switch its "thinking" on or off for each request. Why you'd want it: A popular, permissively licensed model you can run on one strong graphics card or rent cheaply from Groq.
| ✓ Pros | ✗ Cons |
|---|---|
| Very permissive license | Benchmarks are the maker's own |
| Fits on a single high-end graphics card | Too big for most laptops at full precision |
| On Groq at $0.80 in and $4.00 out per million tokens | Groq lists it as a preview; last featured here October 30 |
Qwen/Qwen3.8-27B · Hugging Face
Image-Text-to-Text model with 28B parameters. Download, explore files and run it on Hugging Face.
Twelfth on the trending chart: the ready-to-use ComfyUI package of Black Forest Labs' small image editor, with over 1.1 million downloads.
📥 Downloads (30d): 1,143,397 · 📜 License: FLUX Kommunity License
👤 By: Black Forest Labs · 🎯 Task: Image-to-image
📐 Size: 5.6B (image model; text reader is separate)
👤 By: Black Forest Labs · 🎯 Task: Image-to-image
📐 Size: 5.6B (image model; text reader is separate)
What it is: A small image model that edits pictures from an instruction, creates images from text, and combines up to 10 reference images into one. You can also place items by drawing boxes in the prompt, and it can write text inside images. Why you'd want it: Precise image edits and layouts on your own graphics card, inside the popular ComfyUI app.
| ✓ Pros | ✗ Cons |
|---|---|
| One model for editing, creating and combining images | Commercial use is limited under the license's terms |
| Compressed versions for smaller graphics cards | Gives generic results unless you run its prompt rewriter first |
| Ready-made ComfyUI workflows | Gated download; the main model was last featured here October 23 |
black-forest-labs/flux-3-image-klein-comfy · Hugging Face
Image-to-Image model. Download, explore files and run it on Hugging Face.
Its compressed copy from Unsloth is sixteenth on the trending chart: an early look at the design behind Qwen's next generation.
📥 Downloads (30d): 3,607,555 · 📜 License: Qwen Community License 1.0
👤 By: Qwen (Alibaba) · 🎯 Task: Image-text-to-text
📐 Size: 125B total, 6B active (plus 51B word-pattern table)
👤 By: Qwen (Alibaba) · 🎯 Task: Image-text-to-text
📐 Size: 125B total, 6B active (plus 51B word-pattern table)
What it is: An experimental model that Qwen calls a preview of the design behind Qwen4, built to stay fast on very long inputs. It reads text and images, handles 262,144 tokens at once and can stretch to 1 million. Why you'd want it: A large but efficient model for coding and agent work, since only a small part of it runs for each word it writes.
| ✓ Pros | ✗ Cons |
|---|---|
| Free to use, modify and sell for most businesses | Companies selling AI access or coding/office assistant products need a separate license |
| Fast on long inputs thanks to its new design | An experimental preview, not the polished hosted version |
| Works with popular serving software (vLLM, SGLang) | Needs data-center hardware at full size; last featured here October 26 |
Qwen/Qwen3.8-Flash-Next · Hugging Face
Image-Text-to-Text model with 180B parameters. Download, explore files and run it on Hugging Face.
Product Hunt
AI Launches Today
Saturday's top AI launches on Product Hunt ranged from OpenAI's new image tools to a code reviewer that waves through low-risk changes on its own. Upvote counts are Product Hunt's scores when we checked during the day, so final counts may be higher.
Create, edit, and animate images with AI
🔥 Upvotes: 226 · 👤 By: OpenAI; hunted by Rohan Chaubey
💰 Pricing: Free options; API prices not listed on Product Hunt · 🏷 Category: AI, API
💰 Pricing: Free options; API prices not listed on Product Hunt · 🏷 Category: AI, API
OpenAI's image update promises faster image creation, more precise editing and animated GIFs across ChatGPT, Codex and its API. You can mark up an area of an image to point at what should change, keep characters and products consistent across edits, and export SVG files. Developers get two API models, one tuned for speed and one for detailed work. Verdict: The day's top launch and a useful step for anyone making marketing images or small animations; test the speed and quality claims on your own work before switching.
View on Product Hunt →
Web search on a schedule that calls your agent, $2/1k runs
🔥 Upvotes: 182 · 👤 By: Exa (exa.ai); hunted by Rohan Chaubey
💰 Pricing: $2 per 1,000 runs, down from $15 · 🏷 Category: Search, AI
💰 Pricing: $2 per 1,000 runs, down from $15 · 🏷 Category: Search, AI
You describe what to watch on the web and how often, and Exa alerts your AI agent only when something new and relevant shows up, with a summary and sources. The new version remembers what it already sent, so it sends fewer repeat alerts, and Exa says existing setups don't need changes. Verdict: A big price cut for a genuinely handy job, keeping agents up to date without constant re-searching; the "quieter and more relevant" claims come from Exa's own testing.
View on Product Hunt →
Free, Risk-Aware Code Review: Auto Approve Low-Risk Changes
🔥 Upvotes: 181 · 👤 By: Hexmos (hexmos.com/livereview); maker Maneshwar Holla
💰 Pricing: Free and self-hostable; a cloud version is also offered · 🏷 Category: Code review, Developer tools
💰 Pricing: Free and self-hostable; a cloud version is also offered · 🏷 Category: Code review, Developer tools
Scores every proposed code change for risk, approves the safest 30-50% automatically and sends the rest to human reviewers, riskiest first. It mixes an AI model, a model trained on past outages and a map of how your code connects, and works with GitHub, GitLab, Bitbucket and others. The idea is inspired by an internal Meta system, but the 30-50% figure is a target, not a measured result. Verdict: Promising for busy teams buried in reviews, but auto-approving code is a big trust step; start in a low-stakes project while it learns from your history.
View on Product Hunt →
Your personal AI advisor for a more intentional life
🔥 Upvotes: 152 · 👤 By: Quest (new.quest); co-founder Vincent Nallatamby
💰 Pricing: Free options; paid prices not listed · 🏷 Category: AI chatbots, iMessage apps
💰 Pricing: Free options; paid prices not listed · 🏷 Category: AI chatbots, iMessage apps
An AI advisor that lives in iMessage and tries to learn your personality, values and goals so it can help you reflect and work through hard choices, rather than telling you what to do. You choose which apps and chats it can learn from, and you can view, correct or delete what it remembers. The makers say conversations aren't sold or used to train AI models. Verdict: An interesting twist on personal assistants, but it asks for a lot of personal access; read the privacy notice before connecting your chats.
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Turn voice chats with Muse into live video calls
🔥 Upvotes: 94 · 👤 By: Meta; hunted by Kate Ramakaieva
💰 Pricing: Not listed · 🏷 Category: AI, Bots, Video
💰 Pricing: Not listed · 🏷 Category: AI, Bots, Video
Gives Meta's Muse AI assistant a face, so voice chats become video calls where its lips, expressions, hands and body move in time with its speech. Meta says replies start in about 870 milliseconds, and that people in its tests preferred it over avatars from Runway and HeyGen. It's rolling out in the Muse app for adults in the US, with Europe later. Verdict: An impressive demo of real-time AI video, but US-only for now, and the comparisons come from Meta's own tests.
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API Pricing
Snapshot
| Provider | Model | Input $/1M | Output $/1M | Context |
|---|---|---|---|---|
| Anthropic | Claude Fable 5.1 | $10.00 | $50.00 | 1M tokens |
| Anthropic | Claude Opus 5.5 | $4.00 | $20.00 | 1M tokens |
| Anthropic | Claude Sonnet 5.5 | $2.00 | $10.00 | 1M tokens |
| Anthropic | Claude Haiku 5.5 | $0.10 (up to 100K-token prompts; $0.50 above) | $0.50 ($2.50 above 100K) | 1M tokens |
| OpenAI | GPT-6 Astra | $10.00 (up to 272K-token prompts; $20.00 above) | $50.00 ($75.00 above 272K) | 1.05M tokens |
| OpenAI | GPT-6.1 Sol | $2.00 (up to 272K; $4.00 above) | $10.00 ($15.00 above 272K) | 1.05M tokens |
| OpenAI | GPT-6.1 Terra | $1.00 (up to 272K; $2.00 above) | $5.00 ($7.50 above 272K) | 1.05M tokens |
| OpenAI | GPT-6 Luna | $0.10 (up to 272K; $0.20 above) | $0.50 ($0.75 above 272K) | 1.05M tokens |
| Gemini 4 Argon | $2.00 to Nov 30; $4.00 from Dec 1 | $10.00 to Nov 30; $20.00 from Dec 1 | 1M tokens | |
| Gemini 4 Carbon (announced, not yet on sale to developers) | $2.00 introductory; $4.00 after | $10.00 introductory; $20.00 after | not listed | |
| Gemini 3.8 Flash | $0.75 (to Dec 31; $1.50 from Jan 1) | $3.75 (to Dec 31; $7.50 from Jan 1) | not listed | |
| Groq | GPT-OSS 120B | $0.15 | $0.60 | 131K tokens |
| Groq | Qwen3.8-27B (preview) | $0.80 | $4.00 | 131K tokens |
| Groq | Muse Spark Open (preview) | Contact sales | Contact sales | 131K tokens |
| Mistral (open weights) | Mistral Large 4 | $0.70 | $2.10 | 1M tokens |
Here is what the major AI companies charge through their Application Programming Interface (API), the paid connection developers use to plug AI models into their own apps. Prices are in US dollars per 1 million tokens.
No price changes vs. yesterday - every standard price from Anthropic, OpenAI, Google, Groq and Mistral matches yesterday's table. Gemini 4 Carbon still isn't listed on Google's developer pricing page, so its row is carried over from yesterday's table and not re-verified today. Groq's old pricing page now sends visitors to its home page, so we read Groq's prices from its model documentation instead.
What this means: Prices are frozen, so the deadlines matter: Gemini 4 Argon doubles on December 1, OpenAI's GPT-5.6 Sol promotion ends November 30, and Gemini 3.8 Flash doubles on January 1. Also note that OpenAI's GPT-6 models cost more for the whole request once a prompt passes 272,000 tokens, so very long prompts can cost far more than the headline price.
No price changes vs. yesterday - every standard price from Anthropic, OpenAI, Google, Groq and Mistral matches yesterday's table. Gemini 4 Carbon still isn't listed on Google's developer pricing page, so its row is carried over from yesterday's table and not re-verified today. Groq's old pricing page now sends visitors to its home page, so we read Groq's prices from its model documentation instead.
What this means: Prices are frozen, so the deadlines matter: Gemini 4 Argon doubles on December 1, OpenAI's GPT-5.6 Sol promotion ends November 30, and Gemini 3.8 Flash doubles on January 1. Also note that OpenAI's GPT-6 models cost more for the whole request once a prompt passes 272,000 tokens, so very long prompts can cost far more than the headline price.
arXiv Paper of the Day
What the Middleman Delivers: Answer Behavior, Tool Permissions, and Billed Usage in LLM API Relays
Xiaodong Wu, Zhimin Zhao, Qi Li, Chaklam Cheong, Xiangman Li, Jianbing Ni · arXiv:2611.07650
What it claims: Third-party "relay" services resell access to big AI models like GPT-6 Astra and Claude Opus 5, often for less than the official price. The authors tested 20 relays to see whether they deliver the model they advertise, follow instructions to keep tools switched off, and bill the same number of tokens as the official service.
Key finding: For identical requests, five relays reported 4,200 to 60,000 more input tokens than the official API, and in the first round of tests 7 of 10 low-price relays (versus 2 of 10 others) gave answers that differed from the official model.
Why practitioners should care: A cheaper reseller can quietly cost more or behave differently, and four relays used tools even when told not to. If you buy model access this way, compare its token counts against the official API and re-test it more than once, since some results changed on retesting.
Key finding: For identical requests, five relays reported 4,200 to 60,000 more input tokens than the official API, and in the first round of tests 7 of 10 low-price relays (versus 2 of 10 others) gave answers that differed from the official model.
Why practitioners should care: A cheaper reseller can quietly cost more or behave differently, and four relays used tools even when told not to. If you buy model access this way, compare its token counts against the official API and re-test it more than once, since some results changed on retesting.
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