DeepSeek's open model beats Opus 5 at coding, two hours after being called always late

DeepSeek ships V4.1 Flash 1017, an open model that beats Opus 5 on agentic coding

DeepSeek calls it a minor update to V4.1 Flash. The open weights (MIT license, 763B parameters, 1M-token context) score 77.0 on DeepSWE v1.1 on DeepSeek's own card, above Opus 5's 74.0 and GPT-5.6 Sol's 73.0, though Opus 5 still leads on Terminal-Bench and HLE. The API costs $0.15/$0.60 per million tokens off-peak (@kimmonismus), and DeepSeek opened its own search and fetch APIs at $0.75 per 1,000 calls.

Loved, with jokes about what "minor" means. r/LocalLLaMA's top reply: "\"minor update\" Proceeds to obliterate GLM5.3, Kimi K3 and GPT5.6 Sol". On @PawelHuryn's 105-bug test it averaged 38.7 over three runs, behind Opus 5.5's 41.7 but far above the old Flash's 21.7. @0xdominus: "It is GPT 6 Luna level."

Two hours before the launch, @scaling01 called DeepSeek "the Google of China", "always late" and "never a true frontier model". Bad week for that insult: the American Google just came back with Argon, and the Chinese one beat Anthropic's July flagship with a minor update.

1. Jack Clark tells the IMF the singularity has begun

In the IMF's Per Jacobsson Lecture in Bangkok, Anthropic's co-founder said "the singularity is here" and that the window to put safeguards in place is "a small number of years" (@thehypedotnews). The top scenario of the economic model Anthropic published in September takes US GDP from just over $30T to $44T by 2030, which he called "very outlandish" himself.

Cheers and eye-rolls. @elonmusk: "If this is rephrased as "useful output of US", then >50% growth by 2030 due to SI is extremely likely, unless there is a major war". @ylecun: "It really has not, though. Unless you get fooled into thinking that every point on an exponential curve is a singularity." r/singularity, in reply: "We've hit the singularity and not a single disease cure as a result."

Heat: high · 1.2M views, 47 posts (565K on @Kalshi's) · 161 pts on r/singularity

2. Anthropic's own AI safety bill draws fire from both sides

Politico reported on Friday that Anthropic is pitching Congress a frontier AI bill it wrote, and the draft is now online (@ShakeelHashim). It covers models trained on 10²⁵ FLOPs or more, fine-tuning and RL included, and would need a judge's approval for Washington to halt a model (@IntEngineering).

Too loose for safety people, too broad for the accelerationists. @DavidSacks: the 2023-era cutoff "will eventually sweep in most of Silicon Valley" and "favors incumbents". @CharlieBull0ck: weaker than the FRONTIER Act, with rulemaking "almost nonexistent". @annia: "Anthropic can kill 49 people and steal up to a billion dollars before anyone can legally stop them".

Heat: medium · 542K views, 29 posts (272K on @annia's) · 34 pts on r/accelerate

3. Terence Tao calls OpenAI's zeta result the biggest advance on its subject in 50 years

On the zero-free region from OpenAI's 6 October maths drop, Tao said it is "a massive new zero-free region, very clever new technique": three or four existing ideas "arranged in a very unusual way", which he doesn't think "any single mathematician alive would have come up with".

r/singularity read it as a line crossed. The top reply: "That's gotta show that AI is, at the very least, at the border of 'genuine creativity' in math." Another: "Has there ever been a thing in science or math that categorically wasn't based on some extension or inspiration from an existing idea?"

Heat: low on X · 8K views, 15 posts · 686 pts on r/singularity

4. [rumour] Three "aurora" models show up in OpenAI's API

Trackers polling OpenAI's model list picked up aurora-red-alpha, aurora-green-alpha and aurora-blue-alpha this morning, with no word from OpenAI. @ChrisGPT reads them as OpenAI's answer to Claude Fable 5.5.

Guessing games. @AndrewCurran_: "I do think Blue will be the biggest one." @_jayyy18_13k: "openai really needs to hire someone to guard its model names at this point".

Heat: low · 72K views, 18 posts · quiet on Reddit

5. OpenCode's Console is breached, and users' OpenAI and Anthropic balances drained

OpenCode says a "large scale distillation attack" exposed the provider keys of 1.4% of Console users, through a legacy system it was shutting down (@kimmonismus). One user counted over $400 of fraudulent spend overnight (@colinparsonscom). Anthropic revoked the Claude keys it believes were hit (@lydiahallie); keys used in the open-source OpenCode app never reach its servers (@thdxr).

Alarm, and questions about the word "distillation". @natolambert: "the public deserves to know if this is 'distillation' as used to train downstream models, or some other weird shady pattern". r/LocalLLaMA's top reply: "rotate keys and change to a different harness to be safe."

Heat: high · 2.9M views, 66 posts (1.5M on OpenCode's statement) · 373 pts on r/LocalLLaMA

6. Malfoid, an AI-made Harry Potter fan series, goes viral on TikTok

AI videos of a fan story where Draco Malfoy is a girl, in an enemies-to-lovers plot with Harry, are spreading on TikTok, made with tools like Seedance 2.5 (@Cia0_exe).

Read as a turn in how people feel about AI video. @enggirlfriend: "it's actively shifting AI sentiment on tiktok to positive (was historically super negative)". r/accelerate's top reply: "Now people are realizing they can make fan content that is on par with professional films".

Heat: medium · 138K views, 21 posts · 342 pts on r/accelerate

Tencent's self-training loop lifts a 27B model to 86.5% on Terminal-Bench 2.1

Starting from Qwen3.8-27B, two rounds of fine-tuning on its own rewritten runs that passed the verifier alternate with two rounds of PPO that keep the previous stage's critic. The four-suite Terminal-Bench average rose from 20.68% to 50.58%, the authors report. It matters because a mid-size open model got this far mostly by training on its own checked work, stage after stage.

Shusheng-S2 helps prove the 3D case of a 1995 chaos conjecture

Mathematicians led by Xu Disheng of Great Bay University worked with Shanghai AI Lab's model over seven rounds, keeping its promising ideas and dropping dead ends, to prove the three-dimensional case of the Ghys conjecture. A Peking University team checked the four main theorems in Lean; the paper is an arXiv preprint. It matters because the AI worked on research-level geometry, not puzzles, and a 550,000-line Lean check means referees don't have to take it on trust.