Afternoon edition — Sunday 25 October 2026

Nanbeige, an AI team backed by the Chinese recruitment company BOSS Zhipin according to Startup Fortune, has put Nanbeige4.3-33B on Hugging Face under the Apache 2.0 licence. The model card calls it the 'flagship teacher model' of the Nanbeige4.3 series, to be distilled later into smaller models such as a planned Nanbeige4.3-3B.

In the card's own table, the model scores 65.5 on DeepSWE against 42.5 for Qwen3.8-27B, and 80.9 on Terminal-Bench 2.1 against 73.0. It trails Qwen3.8-27B on SWE-Bench Pro, 60.3 to 61.7, and Gemma4-31B on GPQA Diamond, 89.5 to 91.3. The card lists a context window of up to 524,288 tokens.

Startup Fortune reports that the release passed 140 points on r/LocalLLaMA and notes that a 4-bit version could fit on a single 24GB graphics card, although the long context would be limited on such hardware.

The moderators of r/opensource, one of Reddit's main forums for open-source software, posted new rules on Saturday evening, The Verge reported on Sunday 25 October. The post opens: 'If your project uses AI, is made by AI, or is intended for AI, it's not welcome on r/opensource.'

The rules also require submitted projects to be at least a year old, actively maintained and to have several contributors, and say the forum can no longer take requests for maintainers or contributors. Members who don't speak English are told to find another community because, the moderators wrote, 'We cannot distinguish between AI-written and AI-translated.'

According to The Verge, moderator Wolvereness said in the comments that there is room for selective enforcement, for example for software that incidentally uses AI for accessibility features such as automatic captions. Critics pointed out that the Linux kernel now contains some AI-generated code, and a rival forum, r/TrueOpenSource, has been set up.

A guest post on Terence Tao's blog on 24 October, written by the mathematicians Abhinav Nellore, Johannes Schmitt, Soledad Villar and Rachel Ward, announced oai-math-revised, a GitHub project to improve the maths write-ups that OpenAI publishes in its openai/math repository.

The authors write that OpenAI's write-ups 'can be difficult to understand and can have incomplete citations'. They invite students, postdocs, professors and enthusiasts to help revise them, and ask for volunteers to act as reviewers for particular categories of problems.

The project describes itself on GitHub with the line 'Math is of the people, by the people, and for the people, and we will cite the people.' Its repository was created on 10 October; OpenAI's maths repository dates from 6 October and had about 15,500 stars when checked.

AI21 Labs published LIFT-Bench, a benchmark and training set for instruction following, in a blog post on 25 October; the accompanying paper was posted on arXiv on 20 October. AI21 says models trained on standard instruction-following rewards learn to satisfy the listed constraints and skip the task. One of its runs answered a request for a history chapter with a single word and received full reward.

LIFT-Bench asks a model to draft a document from a topic and an outline, and attaches each constraint to one section. Some constraints are checked by code, such as writing a section in German; others, describing what a section must cover, are scored by a judge model. The paper reports 784 test examples and a 34,258-task training set, LIFT-Train, and says the data and generation pipeline are public.

When AI21 trained Qwen2.5-7B with GRPO on the widely used IFTrain set, the reward reached 1.0 by step 180 while the median answer shrank from 114 words to 18 by step 390. On LIFT-Train, answers stayed at roughly 390 to 530 words, and the model held steady on outside benchmarks where IFTrain slipped, AI21 says.

The Information reported on Saturday 24 October that OpenAI is pulling large customers away from Anthropic with aggressive pricing. According to The Decoder's summary of the report, Rippling chief executive Parker Conrad said OpenAI's share of his company's coding work rose from 16 percent to 52 percent, while Anthropic's share fell from 57 percent to 18 percent.

Replit is reported to have moved more of its AI spending to OpenAI after OpenAI offered more than 30 percent off a contract worth over $100 million a year. The Decoder also says a US bank with more than $7 billion in assets had its ChatGPT seats doubled to 500 at no extra charge, paying under $7 per user instead of the usual $20 or more.

DataCamp chief executive Jonathan Cornelissen is quoted with an 80 to 90 percent cut in costs. An analysis by alfw.ai reads that figure as his estimate of the saving if terms he was still seeking were extended, and says the discount actually reported for DataCamp is 40 percent, limited to internal product development and tied to adopting Codex.

The same reporting cites an investor memo saying Anthropic's growth slowed from the second quarter to the third.