A post on r/ClaudeAI made a dramatic claim this morning. A Hugging Face account named burner22 had uploaded a file called numbat. The poster said it held Anthropic's next model, the one code-named Mythos.

The claim came with huge numbers. The file held 772 weight shards. Together they totaled 7.72 terabytes, enough for 14 trillion parameters.

The post spread fast. It pulled 198 comments on Reddit. A matching Hacker News thread added 30 points and 12 comments of its own.

Readers had a reason to wonder. Anthropic's Claude Code source code leaked back in March. That leak named numbat as a real internal codename.

Then a second poster tested the file directly. They read the shards with range requests. They checked the math against a known model, Qwen2.5-7B.

Two tests settled the question fast. One weight table matched another table's math, row for row. A setting called input_scale changed between parts that should share one value.

The verdict: the file is fake. Someone built real wrapping around invented weights. The word list and the embedding table came from a true model. The giant number inside came from a generator, rather than from training.

The fake still earned real traffic. It pulled 87 likes and 5,846 downloads on Hugging Face before anyone called it out.

The case shows how good a fake can look now. A faker can copy a real word list. It can hit a real size and dress up a hoax in sound math.

Readers tested the numbers themselves instead of trusting the headline. That instinct caught this fake inside hours.

Anthropic has stayed quiet in public about the file. The company's real Mythos model stays unreleased, confirmed only by that one line from March.

A coder on r/LocalLLaMA shipped a big new tool today. The project is called Heretic. It strips the built-in refusals out of open language models.

The new version is called Heretic 2.0. It took almost five months to build. The post pulled 67 comments inside the window.

Heretic already has real reach. It carries 37,436 stars on GitHub and 4,268 forks. One Heretic-tuned model alone has pulled 1,451,434 downloads on Hugging Face.

The old method had a name: abliteration. It found one direction inside a model and blocked it. Version 2.0 swaps in a new method called Arbitrary-Rank Ablation.

The new method skips that single-direction rule. It adjusts many weights at once with a math tool called an optimizer. The builder says it works far better than the old way.

Testers helped shape the new method for months. One tester made it work with Heretic's own LoRA system. A second tester found a real speed gain inside it.

Heretic now does more than remove refusals. It can also cut a model's habit of agreeing too much. It can shift a model's tone or mood too.

The tool runs around plugins now. One kind of plugin picks the goal to aim for. A second kind runs the actual change on the model's weights.

Support grew wider in this release. Heretic now handles models built with hyper-connections. It also works better on models built to reason step by step.

One thing stayed the same through all of it. A coder can still type one short command and get a stripped-down model back in minutes.

The release matters past one tool update. Open models keep gaining ground on size and skill. A free tool that reshapes them at will keeps that fight wide open. Anyone with a laptop and a weekend can now join in.

A screenshot on X set off a wave of guessing this morning. An account called Token Gremlin posted a picture of Codex usage data. The data listed a model named gpt-6.2-astra.

The claim spread fast. The post pulled 1,289 likes and 101 replies on X. A matching thread on r/singularity added 55 comments of its own.

The picture showed a usage split. It listed gpt-6.2-astra at 19.8 percent of requests. The rest went to the known model, gpt-6-astra.

OpenAI's own model picker still says GPT-6 Astra. Its menu skips any mention of a 6.2 version. The new label only shows up inside usage logs.

Other users said they saw the same label. Multiple accounts on X reported the exact same split in their own usage pages. That matching pattern is why the claim spread so fast.

OpenAI has stayed quiet about any new model so far. Its own blog, its changelog and its model docs skip the name entirely. A silent test like this is called a gray release.

Readers on Reddit stayed split on what it means. Some called it routine testing, the kind labs run all the time. Others said a jump from 6 to 6.2 this soon would be fast, even for OpenAI.

The timing adds to the guessing. Rivals have shipped fast lately, and Reddit users joked that a Claude update might land the same week. Only OpenAI can confirm any of it, and it has stayed silent so far.

The pattern itself says something plain. Users now watch their own usage logs closely. They can catch a new label before a company says one word about it. A company's own billing page can leak news faster than its blog does.

OpenAI wants a new name for its data centers. A Reddit post on r/singularity shared the plan this afternoon. The term OpenAI wants is "AI compute campus."

The push comes from the top. Chris Lehane, OpenAI's chief of global affairs, is leading it. The plan ties to a wider policy push right after the midterms.

The post pulled 29 comments fast. Readers mostly doubted the idea. One reply asked who the new name is even supposed to convince.

OpenAI already runs one huge project under this banner. The company secured about 8 gigawatts of capacity at a site in Pike County, Ohio. That one project alone should bring about 35,000 construction jobs.

The company frames the new term as a fix. A data center sounds cold and distant, the thinking goes. A campus sounds like it belongs to the town around it.

Readers on Reddit stayed skeptical. One pointed out that a new name leaves power bills exactly where they stood. Water use and strain on the local grid stay the same either way.

The timing lines up with Washington's calendar. Congress enters a lame-duck session on November 9. New members get sworn in on January 3.

OpenAI hopes to shape the public mood before local fights over power and water get louder. Renaming a building costs little. Winning over a town that lives beside one costs far more.

The real test sits months away. New data center projects keep landing in small towns across the country. A new word can shift a headline fast. It takes much longer to shift how a town feels about the building next door.

The next fight over a new site will show the real answer. That fight will matter far more than any name picked this week.

A short question on r/OpenAI opened up a bigger fight today. The poster asked a simple thing: what are DOTS costing you? DOTS is the name of OpenAI's new credit currency.

The post pulled 18 comments fast. Readers used it to vent about a wider change. OpenAI now sells prepaid credits instead of listing a plain dollar price.

A second post on the same subreddit spelled out the complaint. One credit costs about 4 cents at the standard rate, that poster found. A heavy model like Astra can burn 250 credits for one million input tokens.

Readers said the math itself checks out fine. Their complaint is the extra step. A user now has to convert dollars to credits, then convert tokens back to guess the true cost.

One poster called it the mobile game treatment. Prepaid credits and bulk bundles both echo old tricks from game stores. A balance that expires in 12 months echoes that same playbook too.

The timing makes the anger louder. OpenAI plans to merge ChatGPT and Codex into one shared usage pool by December. That is about 30 days from today, and it covers Plus, Pro and Business plans alike.

One thing stays outside the shared pool. OpenAI says plain Instant chat will keep drawing from its own separate allowance.

Outsiders still lack any real sense of how big each plan's shared pool will turn out to be. The company has left that number for later.

The fight here comes down to trust more than math. Heavy users already track every token they spend. A new currency hides the plain dollar figure behind an extra step. That makes the job harder, right as usage itself grows more tangled.