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x.comarticle

Lewis - Policifyai (@Policifyai) on X

Policifyai's October 2026 roundup lists model releases by date with prices and benchmark scores: GPT-6.1 Sol and Terra, Claude Sonnet 5.5 and Haiku 5.5, Gemini 4 Argon and Carbon, Muse Spark Open, Mistral Large 4 weights and Kimi K3.1 Pro. It also covers Anthropic's S-1 compute commitments, Artificial Analysis Intelligence Index v5, and chip and data-center deals.

CodexHugging FaceMixture of Experts+6
OpenAIAnthropicGoogle+43

models, ai-infra, evals· Added 1 Nov 2026, published 31 Oct 2026

github.comrepo

Show HN: A language model that lives in a boot sector

bootgpt is a char-level language model that runs from a BIOS boot sector. A 512-byte hand-written asm MBR loads an 11.5 KB int8 model from 23 following sectors and runs it in 16-bit real mode on a 386, generating fake Linux dmesg boot logs. train.py quantises to int8 with power-of-two scales, and its integer simulation matches the asm output char for char.

x86 assemblyNASMQEMU+4
sectorllmsectorlisp-nnOscar Toledo+3

inference, models, training· Added 1 Nov 2026, published 31 Oct 2026

x.comthread

🚨 AI News | TestingCatalog (@testingcatalog) on X

RoboAPI is a public API from PokeBot, powered by its world-action model Poke-Aurora, that lets robot arms do new tasks from natural-language instructions with no task-specific data collection or training. A user connects a supported arm with a wrist-mounted camera, gives a task such as "clean the table", and receives the next moves in near real time. The post gives no benchmarks, supported hardware list or pricing.

RoboAPIPoke-Auroraworld-action model
PokeBotTestingCatalog

models, multimodal· Added 1 Nov 2026, published 31 Oct 2026

latent.spacearticle

[AINews] Google admits AI Mode hurts Search revenue; -15% $500B drop worst since 2004 IPO. AI Bear Market coming?

AINews issue for 29 to 30 October 2026 from Latent Space. It opens on Google's admission that AI Mode monetises worse than classic Search, which preceded a roughly 15% share drop. It then recaps Claude Ultra dropping the 5-hour limit, Gemini 4 Carbon, Mistral Large 4, Nemotron 3.5, Artificial Analysis Index v5, Unsloth GGUF disputes, and the Anthropic S-1 filing.

Claude CodeClaudeGemini+17
GoogleAnthropicOpenAI+46

ai-policy, models, evals· Published and added 31 Oct 2026

simonwillison.netarticle

dbreunig/nesformer

nesformer is a project by Drew Breunig that bakes a working Nintendo Entertainment System 6502 CPU emulator into the weights of Qwen3.5-4B, so NES ROMs such as Super Mario Bros run (very slowly) inside the model. It follows Divyansh Agrawal's qwenputer. Simon Willison relays the Opus 5.5 prompts Breunig used, and notes that Opus found Christopher Pow's CPU conformance tests.

Qwen3.5TransformerLLM+1
Simon WillisonDrew BreunigDivyansh Agrawal+5

research, coding-agents, models· Published and added 30 Oct 2026

x.comthread

Artificial Analysis (@ArtificialAnlys) on X

Hyperflow H3 is Video Rebirth's 8-step LoRA for MiniMax H3, released in September 2026 with open weights. Artificial Analysis ranks it #5 on AA-Video-I2V v2.1 and #3 on AA-Video-Editing v1.1, ahead of MiniMax H3 (768p). It costs $9.00 per minute for Image to Video and $18.00 for Video Editing at 1088p, under half of Dreamina Seedance 2.5 ($34.12 and $40.82). The thread gives per-capability and per-use-case breakdowns.

LoRAdiffusion model
Artificial AnalysisVideo RebirthHyperflow H3+6

models, evals, multimodal· Added 31 Oct 2026, published 30 Oct 2026

interconnects.aiarticle

Was I wrong about open models & cyber risks?

Interconnects post in which Nathan Lambert revisits his claim that an open-weight Claude Mythos would have been survivable. He argues GLM-5.3 already crosses the capability threshold with little visible societal change, and quotes Rob Wiblin, Anthropic and Zvi Mowshowitz as examples of exaggerated warnings. He cites Epoch AI's Firefox exploit built with GLM-5.3, and treats the recent vulnerability surge as an ecosystem trend driven by AI capability and diffusion, not open versus closed models.

FirefoxGLM
Claude MythosGLM-5.3Anthropic+13

ai-policy, ai-safety, models· Published and added 30 Oct 2026

latent.spacearticle

[AINews] Building AIE CODE: The top Coding Agent Conference

AINews issue for 28 to 29 October 2026 from Latent Space. It opens with a preview of the AIE CODE summit (themes: Scaling without Slop, System One models, Increasing Ambition, with Jarred Sumner on Bun in Rust). It then recaps Twitter and Reddit news: Mistral Large 4 open weights (1.05T total, 52B active), Artificial Analysis benchmarks, Gemini 4 Carbon, Qwen4 rumours, Claude Code quota complaints and OpenAI frontier-run monitoring. Text was cut before the end.

BunRustvLLM+17
Latent SpaceAI EngineerAIE CODE+37

models, coding-agents, evals· Published and added 30 Oct 2026

x.comthread

Artificial Analysis (@ArtificialAnlys) on X

Artificial Analysis launched an HLE-Diamond leaderboard in v5 of its Intelligence Index, covering the refined 1,000-question Humanity's Last Exam from CAIS and Scale AI. Each question runs once without tools, graded by GPT-5.6 Luna (medium) as pass@1. Gemini 4 Carbon (high) leads at 69%, Claude Opus 5.5 (max) scores 68%, and the top open weights model, Kimi K3.1 Pro, reaches 37%.

Artificial AnalysisArtificial Analysis Intelligence IndexHLE+9

evals, models· Published and added 30 Oct 2026

deploymentsafety.openai.compaper

GPT-Rosalind-6 System Card Addendum

GPT-Rosalind-6 System Card Addendum describes OpenAI's life-sciences reasoning model, which uses the same weights as GPT-6 Astra and is offered only through trusted access. It reports life-science benchmark gains over GPT-Rosalind-5.5 (MedChemBench v7 49.6% vs 28.9%), High-capability Biological and Chemical Preparedness results, and below-threshold Critical bio design evaluations. It also covers access controls, refusal evaluations, cyber jailbreak regression and alignment tables.

GPT-6 AstraGPT-Rosalind-6GPT-Rosalind-5.5
OpenAIPreparedness FrameworkMedChemBench v7+16

ai-safety, evals, models· Published and added 30 Oct 2026

latent.spacearticle

Can Frontier Models See Past a Decoy? Elorian Tests Visual Reasoning

DecoyCount is a benchmark from Elorian and Mercor with 1,660 items that tests whether models count objects or fall back on visual shortcuts. Frontier models scored below 50%: GPT-6 Astra led with 43.17%, ahead of Gemini-3.8-flash (32.71%), Qwen3.8-max (28.31%) and Claude-Fable-5.1 (25.22%). CEO Andrew Dai says Elorian's Glimpse model scored 50.48% in a single internal run without tools, and contrasts visual reasoning with world models such as Atlas and Genie 4.

vision-language model
ElorianGlimpseDecoyCount+17

evals, multimodal, models· Added 28 Oct 2026, published 29 Oct 2026

securityweek.comarticle

Google Touts Powerful Cybersecurity Capabilities in Gemini 4 Carbon Model

Gemini 4 Carbon is Google's new frontier model, announced with scores of 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Google says it beats GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1 on these, with no guardrails. Access is limited to Fairwind Program partners at first. Pricing starts at $2 input and $10 output per million tokens, rising to $4 and $20.

Gemini
GoogleGemini 4 CarbonGemini 4 Argon+13

models, evals· Published and added 29 Oct 2026

x.comthread

🚨 AI News | TestingCatalog (@testingcatalog) on X

Mistral Large 4 ("Le Chonk") is an open-weights model from Mistral, now on Hugging Face. Per Mistral's announcement quoted in the post, it ranks #1 among open models on Cognition's FrontierCode benchmark, is aimed at agentic coding and cybersecurity, and claims better reasoning efficiency and lower inference costs. The post does not give parameter counts, license or benchmark scores.

Hugging FaceMistral
Mistral Large 4CognitionFrontierCode

models, coding-agents, evals· Added 30 Oct 2026, published 29 Oct 2026

x.comthread

SGLang (@sgl_project) on X

SGLang announces Day-0 support for Mistral Large 4 ("Le Chonk"), saying it is the first engine to serve the model on NVIDIA Vera Rubin. The post describes the model as Mistral's largest to date: a natively multimodal 1T-parameter mixture-of-experts model covering instruct, reasoning, coding and agentic workflows. The fetched text is truncated, so benchmark claims and launch commands are not visible.

SGLangMixture of Experts
MistralMistral Large 4NVIDIA

inference, models· Added 30 Oct 2026, published 29 Oct 2026

huggingface.coarticle

Granite Switch 4.1.1 — Update models like you update software

Granite Switch 4.1.1 is a backwards-compatible patch release of IBM's modular Switch architecture, which configures a language model with specialized, cache-efficient adapters on one endpoint. It updates the Granite Speech ASR model (10 languages, native punctuation and capitalization) and the Decision adapter in granitelib-core, measured on the Jev Decision Index test set. Only the new adapters were retrained; the base model is unchanged. IBM plans tutorials and an Adapter SDK for third-party adapters.

Hugging Face
IBMGranite SwitchGranite Speech+2

models, multimodal· Published and added 29 Oct 2026

artificialanalysis.aiarticle

Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5

Gemini 4 Carbon scores 59 on Artificial Analysis Intelligence Index v5 (published 28 October 2026), the top score, with #1 on 4 of 9 evaluations including HLE-Diamond and AA-Omniscience. On the Coding Agent Index it scores 59 with Antigravity CLI, 3 points behind Claude Code with Claude Opus 5.5 (62). Cost is $7.76 per task, versus $10.04 for Opus 5.5. Rollout is limited to selected users.

GeminiClaude CodeGoogle Antigravity+2
Artificial AnalysisArtificial Analysis Intelligence IndexGemini 4 Carbon+10

evals, models, coding-agents· Added 30 Oct 2026, published 29 Oct 2026

x.comthread

Muhammad Waris (@WarisCodes) on X

Nemotron 3.5 Transcribe is a free open-weight speech-to-text model from NVIDIA covering 40 languages, including mixed-language speech. The post says it ties for first among open models with a 2.8% error rate. It says the model needs a large GPU such as an H100 or RTX 5090, so it will not run on a laptop. The post gives no benchmark name or model card link.

Nemotron 3.5 Transcribe
NVIDIANemotron

models, multimodal· Added 30 Oct 2026, published 29 Oct 2026

x.comthread

🚨 AI News | TestingCatalog (@testingcatalog) on X

Nemotron 3.5 Transcribe is an open-weight, promptable NVIDIA mixture-of-experts model with 30B total and about 4B active parameters. One checkpoint does transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding. The post says it ranked first in VoiceArena's comparison of 14 diarization plus ASR systems. The fetched text is cut off and gives no license or download details.

Mixture of Experts
NVIDIANemotronNemotron 3.5 Transcribe+1

models, multimodal· Added 30 Oct 2026, published 29 Oct 2026

latent.spacearticle

[AINews] Gemini 4 Carbon tops leaderboards, launches for cyber defenders

AINews issue for 27-28 October 2026, a Latent Space digest of Twitter and Reddit. It leads with Google DeepMind's Gemini 4 Carbon: claimed cyber scores (SEC-bench Pro 88.2%, ExploitGym 54.8%, CWE-bench 71.0%), #1 on Artificial Analysis Intelligence Index v5 at 59, and access limited to cyber defenders through the Fairwind Program. It also covers benchmark integrity disputes, GitHub Copilot Fusion, H-Net v2, KV-cache work, open-weight releases and Claude Code quota complaints.

GeminiClaude CodeGoogle Antigravity+12
Gemini 4 CarbonGemini 4 ArgonGoogle DeepMind+39

models, evals, coding-agents· Published and added 29 Oct 2026

divagr.comwriteup

Qwenputer: A functioning, deterministic RISC-V CPU inside Qwen3.5

Qwenputer is a stock Qwen3.5 4B with a 32-bit RISC-V CPU (RV32IM plus Zba and a bignum unit) compiled directly into added layers, with no training. Gated DeltaNet states act as exact RAM via gate 1, beta 1 and one-hot keys. It scores 97.5 to 100% on DeepMind arithmetic sets, and 100% on NUPA long-integer arithmetic. It also has an experimental in-model filesystem. The checkpoint is 18.8 GB and needs the RvChat driver.

Qwen3.5Gated DeltaNetRISC-V+6
QwenputerQwenModelScope+6

research, models· Published and added 29 Oct 2026

huggingface.coarticle

Introducing AnySpeechRecognizer and AnyDecisionModel: Open Models for Speech and Decisions on Apple Platforms

AnySpeechRecognizer and AnyDecisionModel are two Swift packages from Hugging Face. The first mirrors Apple's SpeechAnalyzer API with swappable engines (NVIDIA Parakeet, Alibaba Qwen3-ASR on Core ML) and adds Sortformer speaker diarization. The second returns typed yes/no, choice and score answers with probabilities via MLX, Core AI, llama.cpp, Jev or Ollama. The post gives M4 Max timings, model sizes and calibration options.

SwiftCore MLMLX+10
AnySpeechRecognizerAnyDecisionModelAnyLanguageModel+17

multimodal, inference, models· Published and added 29 Oct 2026

huggingface.coarticle

Welcome Le Chonk: Mistral Large 4 on Hugging Face

Mistral Large 4 (Le Chonk) is a multimodal, multilingual Mixture-of-Experts model with about 1T total and 49B active parameters and a 1M-token context, released under the Mistral Ecosystem Open-Weight License. The post covers its MLA and DeepSeek Sparse Attention architecture, a 1.6B Pixtral encoder, and benchmarks including 82% on the Artificial Analysis Cyber Index and 93% on Cybench. It gives run recipes for transformers, vLLM, llama.cpp, TRL fine-tuning and Inference Endpoints.

Mixture of ExpertsTransformersvLLM+11
Mistral Large 4MistralArtificial Analysis+15

models, inference, evals· Published and added 29 Oct 2026

deploymentsafety.openai.comarticle

Addendum to GPT-6 Luna System Card: October 28, 2026 Update

The addendum to the GPT-6 Luna system card covers the October 29, 2026 update of GPT-6 Luna, which gives more concise answers and less agreeable language. It compares the update with GPT-6 Luna (October 7) on safe completions, under-18 evals, jailbreaks, HealthBench, MentalHealthBench, hallucination and alignment. OpenAI keeps its High rating for cybersecurity and for biological and chemical capability. Hallucination error rates rose, and HealthBench scores fell.

ChatGPT
OpenAIGPT-6 LunaGPT-6 Sol+10

models, evals, ai-safety· Published and added 29 Oct 2026

simonwillison.netarticle

Quoting Ted Sanders

Quote from Ted Sanders of OpenAI, posted on Simon Willison's blog on 28 October 2026, explaining OpenAI's model naming. Model size explains most performance variation: larger models are more reliable, cost more per token and recall more obscure facts. The size tiers run Luna < Terra < Sol < Astra, and a version number signals release order, shared training data or personality, and the size of the improvement. The excerpt is short and gives no benchmark data.

LLM
Ted SandersOpenAISimon Willison+3

models· Published and added 28 Oct 2026

x.comthread

Laban (@lunkertw) on X

An X post summarising five AI items: Google DeepMind's Gemini 4 Carbon (88.2% SEC-bench Pro, 54.8% ExploitGym, 71.0% CWE-bench, 59 on Artificial Analysis Intelligence Index v5.0), Ed Zitron's critique of Anthropic's S-1, a Utah Claude Code pilot, and the repos beenuar/AiSOC and expo/skills. In the Utah pilot, 34 developers in 10 agencies took part over four weeks, 80% had a working setup within 30 minutes, and 71% saved over 20 hours. It gives short summaries and links, not primary analysis.

Claude CodeModel Context ProtocolPython+6
Google DeepMindGemini 4 CarbonSEC-bench Pro+9

models, coding-agents, ai-policy· Added 29 Oct 2026, published 28 Oct 2026

x.comthread

Niko (@nikolayxyz) on X

Gemini 4 Carbon is Google's new frontier model, announced in a post by nikolayxyz that quotes Google's launch text. It ranks #1 on v5.0 of the Artificial Analysis Intelligence Index with 59 points, ahead of Opus 5.5 and GPT-6 Astra. Intro pricing is $2 input and $10 output per million tokens. Access starts for cyber defenders first, as Gemini 4 Argon's did. The captured text is cut off before the rollout details.

Gemini
Gemini 4 CarbonGemini 4 ArgonGoogle+4

models, evals· Added 29 Oct 2026, published 28 Oct 2026

x.comthread

John Rood (@johnroodepic) on X

Nemotron 3.5 Transcribe is an open-weight, promptable 30B mixture-of-experts model from NVIDIA with about 4B active parameters, built for recorded audio. One checkpoint transcribes 40 languages, handles recordings up to an hour, labels up to eight speakers, translates, and answers questions about English audio. Weights and a demo are on Hugging Face. The post gives no benchmarks.

Mixture of ExpertsHugging Face
NVIDIANemotronNemotron 3.5 Transcribe+1

models, multimodal· Added 29 Oct 2026, published 28 Oct 2026

x.comthread

🚨 AI News | TestingCatalog (@testingcatalog) on X

Gemini 4 Carbon is a new Google model, announced in a TestingCatalog post on X as taking first place on the Artificial Analysis V5 ranking. It is rolling out to cyber defenders first. Reported scores are 88.2% on SEC-bench Pro (finding vulnerabilities), 54.8% on ExploitGym (exploitation) and 71.0% on CWE-bench (patching). The post calls it a large step up from Gemini 4 Argon, released two weeks earlier. It gives no technical detail beyond these claims.

Gemini
GoogleGemini 4 CarbonGemini 4 Argon+4

models, evals· Added 30 Oct 2026, published 28 Oct 2026

blog.googlearticle

Gemini 4 Carbon

Gemini 4 Carbon is Google's frontier model, announced two weeks after Gemini 4 Argon. It scores 59 on Artificial Analysis Intelligence Index v5.0, 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Pricing is $2 per million input and $10 per million output tokens. Access starts with a subset of cyber defenders through the Fairwind Program.

Gemini
Gemini 4 CarbonGemini 4 ArgonGoogle+10

models, evals, ai-safety· Added 29 Oct 2026, published 28 Oct 2026

deepmind.googlearticle

Gemini 4 Carbon: Our next frontier model

Gemini 4 Carbon is Google DeepMind's new frontier model, announced two weeks after Gemini 4 Argon. It ranks #1 on Artificial Analysis Intelligence Index v5.0 at 59 and scores 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Access starts with cyber defenders through the Fairwind Program, priced at $2 per million input tokens and $10 per million output tokens.

Gemini
Gemini 4 CarbonGemini 4 ArgonGoogle DeepMind+12

models, evals, ai-safety· Published and added 28 Oct 2026

huggingface.coarticle

NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt

Nemotron 3.5 Transcribe is an open-weight, promptable speech model that handles transcription in 40 languages, translation, diarization for up to eight speakers, and audio Q&A. It has about 4B active of 30B parameters and tops open-weight ASR and diarization leaderboards. The post also covers the Granary v2 curation pipeline (463,062 hours, 48 languages) and a medical fine-tuning case study that cut held-out WER by 45.8%.

NeMo SpeechNeMo CuratorvLLM+11
NVIDIANemotron 3.5 TranscribeGranary v2+16

models, multimodal, training, evals· Published and added 28 Oct 2026

simonwillison.netwriteup

The October inflection point for vibe game development

Simon Willison argues October 2026 is an inflection point for vibe coding games, because Claude Opus 5.5 can now handle 3D modeling, music and game design. He describes four browser games built with three.js (Tree Appreciator, Emberwick, Battle Drones, Quarter Sun Cove), with the prompts used, a comparison against GPT-6 models, and advice to start with "Build a mobile-friendly three.js game where...".

three.jsPhaserClaude+7
Simon WillisonClaude Opus 5.5Claude Fable 5+6

coding-agents, prompting, models· Published and added 28 Oct 2026

latent.spacearticle

[AINews] Anthropic ends Coding Interviews: "Hunger beats tenure"

AINews issue of 28 October 2026 from Latent Space. It leads with Felix Rieseberg's post on why Anthropic dropped coding interviews ("Hunger beats tenure"). It then recaps Genie 4, Axiom's Lean formalization of CFSG, claimed ETH refutations by OpenAI and Anthropic, Artificial Analysis Index v5, FrontierCode 2.0, Liquid LFM3, the Qwen3.8 phone-home dispute, and Anthropic's S-1. Reddit recaps are included; the page was truncated before the end.

LeanQwen3.8-27BvLLM+11
AnthropicFelix RiesebergGoogle DeepMind+40

models, evals, ai-policy· Published and added 28 Oct 2026

latent.spacetalk

How Anthropic ships Claude with Claude: Separating the Brain from the Hands

Latent Space episode with Katelyn Lesse (engineering) and Angela Jiang (product) of Anthropic, recorded the day after the Claude Opus 5.5 launch. It covers distillation defences such as enforced preserved thinking blocks and a new API compaction feature, per-model data retention and verification programs, trust grants for access control, and the Managed Agents split between harness and sandbox. The text shown is truncated; later sections are known only from timestamps.

ClaudeClaude CodeRust
AnthropicClaude Opus 5.5Katelyn Lesse+7

agents, ai-infra, models· Published and added 27 Oct 2026

huggingface.coarticle

Build specialized multimodal models with LFM3

LFM3 is Liquid AI's open-weight family of six ~2B-parameter models (text, vision-language, audio, omni and two d1 decision models), all branched from LFM3-1.7B-Base. The base model uses a tri-hybrid backbone of 13 gated short convolutions, 5 sliding-window attention layers and 6 global attention layers, pre-trained on 22T tokens with a 256K context. The post gives transformers snippets, benchmark comparisons against LFM2.5 and Qwen3.5, and a robotics fine-tuning example.

TransformersHugging FacePyTorch+7
Liquid AILFM3LFM3-1.7B+29

models, multimodal, training· Published and added 27 Oct 2026

liquid.aiarticle

Introducing LFM3: Every Modality for Specialized Intelligence

LFM3 is Liquid AI's new family of open-weight multimodal models, six models of about 2B parameters branched from LFM3-1.7B-Base (22T pre-training tokens, 256K context). The hybrid backbone uses 13 gated short-convolution, 5 sliding-window attention and 6 global attention layers. Variants cover text, vision with video, audio, omni and two decision models, with on-device speed numbers, fine-tuning demos and robotics extensions.

llama.cppMLXvLLM+17
Liquid AILFM3LFM3-1.7B+32

models, multimodal, inference, training· Added 28 Oct 2026, published 27 Oct 2026

decrypt.coarticle

OpenAI Proves ETH Is False, and Crypto Twitter Has Questions

Decrypt reports that OpenAI published a 67-page paper (dated 17 October 2026, revised 25 October) claiming its AI found a deterministic subexponential-time algorithm for counting 3-SAT solutions, which would refute the Exponential Time Hypothesis. The proof was formalized in Lean. Impagliazzo, Paturi and Ryan Williams are reviewing it independently and say this is not certification. Anthropic posted a Claude-credited 3-SAT paper on 26 October.

LeanGitHubClaude
OpenAIAnthropicDecrypt+7

research, models· Published and added 27 Oct 2026

deepmind.googlearticle

Genie 4: A new generation of world simulation

Genie 4 is Google DeepMind's real-time interactive world model, announced as a research preview for trusted testers. It generates video with native audio and interactive dialogue, steered by keyboard controls and text prompts. Gemini 3.8 Flash acts as a guiding agent that plans steps and checks frames, and Gemini 4 Argon is used for robotics experiments. The post lists limitations such as drift and object permanence, and says outputs carry SynthID watermarks.

GeminiGoogle AI StudioSynthID
Google DeepMindGenie 4Gemini 3.8 Flash+5

models, multimodal, agents· Published and added 27 Oct 2026

blog.googlearticle

We’re announcing Genie 4, our new world model for real-time interactive simulation.

Genie 4 is Google DeepMind's world model for real-time interactive simulation, with native audio generated on the fly (ambient sound, music, dialogue). It builds on Gemini models: Gemini Omni grounds scenes in real-world appearance and behavior, and other Gemini models keep the simulation coherent. Users steer scenes by natural language. Access is limited to trusted testers now, with Google AI Ultra (Project Genie), the Gemini API and AI Studio to follow. The post gives no architecture or benchmark detail.

GeminiGoogle AI StudioGemini API
Google DeepMindGenie 4Gemini Omni+2

models, multimodal· Added 30 Oct 2026, published 27 Oct 2026

x.comthread

Rohan Paul (@rohanpaul_ai) on X

Hi3D v1.0 (formerly Sparc3D) is an open-sourced image-to-3D model from Hi3D, which runs a closed v3.0 refining at 2048 cubes per side. In a test with 13 professionals in 3D algorithms, 562 judgments against eight other image-to-3D models favoured it 83.5% of the time. The thread also covers the Hi3D Agent and an MCP server for other agents. Back and bottom views were checked, where TRELLIS.2 collapsed a winged figure.

Model Context Protocol
Hi3DHi3D v1.0Sparc3D+2

models, multimodal, mcp· Added 28 Oct 2026, published 27 Oct 2026

x.comthread

Muzammil Shah (@Muzammil_OX) on X

Kimi K3.1 Pro is a new model from Moonshot AI that scores 55 on the Artificial Analysis Intelligence Index, up 11 points from its predecessor, and ranks 4th overall. It has a 1M-token context window and API pricing of $2 per million input tokens and $10 per million output tokens. Weights are due by November 4. Moonshot removed cyber-related training data, which cut its internal vulnerability research score from 90.5% to 81%.

UnityUnreal EngineGodot
Moonshot AIKimi K3.1 ProKimi+2

models, evals· Added 28 Oct 2026, published 27 Oct 2026

latent.spacearticle

[AINews] Anthropic files for $2T IPO in 2 weeks: 1400% growth rate, 48% of revenue through cloud partners, 85% margin, $1B op profit in Q2, $134B cash in bank and $10B lifetime burn

AINews issue from Latent Space on 27 October 2026, led by Anthropic's S-1 filing for a Nasdaq listing (ticker ANT). It reports H1 2026 revenue of $16.3B, an 85% gross margin, $974M Q2 operating profit and 48% of revenue through cloud marketplaces, with reactions from named analysts. It also covers model releases, inference economics and agent tooling. The page text is truncated.

ClaudeClaude CodeHugging Face+7
AnthropicLatent SpaceSemiAnalysis+28

ai-policy, models, inference· Published and added 27 Oct 2026

x.comthread

Abdullah (@abdullah0094) on X

An X thread by Abdullah on GPT-6.1 Terra versus Sol in Codex. Abdullah says Terra gives twice the Codex usage of Sol and asks whether the quality drop is obvious. A reply says it is too early for a verdict, cites OpenAI's claim that Terra matches GPT-6 Astra on Agents' Last Exam, and suggests defaulting to Terra and switching to Sol with /model when it stalls.

Codex
GPT-6.1 TerraGPT-6.1 SolGPT-6 Astra+2

coding-agents, models· Published and added 27 Oct 2026

simonwillison.netarticle

GPT-6.1 Terra

GPT-6.1 Terra is OpenAI's midrange model, announced 26 October 2026 and aimed at visual reasoning, computer use and clearer writing. It costs $1 per million input tokens and $5 per million output, about half of GPT-5.6 Terra and GPT-6.1 Sol and roughly 10x GPT-6 Luna. Simon Willison relays OpenAI's Ted Sanders, who rates it better than Astra and Sol at technical communication and much faster on computer use.

OpenAI API
GPT-6.1 TerraOpenAISimon Willison+7

models, multimodal· Added 27 Oct 2026, published 26 Oct 2026

x.comthread

AGTP (@AGTPinsights) on X

Thread summarizing Meta's Muse Spark 1.3 Evaluation Report, the safety write-up for the model released on September 2, 2026. It covers prompt-injection results on Exponential Security Labs' RepoInject v1 and BrowserInject v1 and Gray Swan's IPI Arena, chain-of-thought controllability evals, PostTrainBench under Loss of Control, and Handshake's human red teaming. It also notes The Midas Project's criticism that Muse Wonder still has no safety report, and the Muse Spark Open rollout (816B total, 42B active parameters).

Muse Spark 1.3Muse Spark OpenMixture of Experts
MetaMuseMuse Wonder+19

ai-safety, evals, models· Added 27 Oct 2026, published 26 Oct 2026

decrypt.coarticle

OpenAI Launches GPT-6.1 Terra, Its Half-Good AI Model at Half the Price

GPT-6.1 Terra is OpenAI's mid-tier model, released 26 October 2026 with standard API prices 50% below GPT-5.6 Terra. At low reasoning effort its factual error rate on an internal test fell from 53.6% to 16.7%, and at maximum effort it solved 50.3% of Terminal-Bench 4.0 tasks versus 21.5%. It is available in ChatGPT Work and Codex and as gpt-6.1-terra. All figures are OpenAI's own.

ChatGPTCodexOpenAI API
OpenAIGPT-6.1 TerraGPT-5.6 Terra+11

models, evals· Published and added 26 Oct 2026

x.comthread

The SI Maximalist (@thesimaximalist) on X

The SI Maximalist posts on X that OpenAI says GPT-6.1 Terra matches GPT-6 Astra on Agents' Last Exam, OpenAI's test of workplace software tasks, at one tenth of the token price. The model is available in ChatGPT Work, Codex and the API. The post only relays OpenAI's claim and gives no benchmark scores, exact prices or method.

ChatGPTCodexOpenAI API
OpenAIGPT-6.1 TerraGPT-6 Astra+2

models, evals· Added 27 Oct 2026, published 26 Oct 2026

openai.comarticle

Introducing GPT-6.1 Terra

GPT-6.1 Terra is OpenAI's fast, lower-cost model for visual reasoning, computer use and writing, released as API model gpt-6.1-terra. OpenAI reports Terminal-Bench 4.0 at 50.3% (GPT-5.6 Terra: 21.5%) and a low-effort error rate cut from 53.6% to 16.7%. API pricing is $1 per million input tokens and $5 per million output tokens. It meets the Critical cybersecurity threshold in OpenAI's Preparedness Framework.

OpenAI APIChatGPTCodex+1
OpenAIGPT-5.6 TerraGPT-6.1 Sol+7

models, agents, evals· Published and added 26 Oct 2026

deploymentsafety.openai.comarticle

Addendum to GPT-6 Astra System Card: GPT-6.1 Terra

GPT-6.1 Terra system card addendum from OpenAI, covering a fast, efficient model in the GPT-6 series. It reports safe-completion, jailbreak, HealthBench, MentalHealthBench, hallucination, alignment and monitorability results against GPT-5.6 Terra and GPT-6.1 Sol. OpenAI rates it Critical in cybersecurity and High in biological and chemical capability, with the same safeguards stack as GPT-6 Astra.

CodexHugging Face
OpenAIGPT-6.1 TerraGPT-6 Astra+16

ai-safety, evals, models· Published and added 26 Oct 2026

x.comthread

Vlad Tchouchkov (@tchouchkov) on X

This X thread summarises OpenRouter usage charts. Weekly volume nears 200 trillion tokens, and open-weight models take 72.6% of tokens (136 trillion) against 27.4% for closed-weight models. Anthropic's daily average rose from about 0.6 to 2.25 trillion tokens alongside the Opus 5.5, Sonnet 5.5 and Haiku 5.5 releases. DeepSeek leads text requests at 26.5%, and agents plus coding account for 57.7% of spending. The author notes the data describes OpenRouter only.

OpenRouterLLM
AnthropicClaude Opus 5.5Claude Sonnet 5.5+7

ai-policy, models, ai-infra· Added 26 Oct 2026, published 25 Oct 2026

minimaxir.comarticle

OpenAI and Anthropic cut their LLM prices by up to 80% within a few months. Why?

Max Woolf's post (minimaxir.com, October 2026) gives a dated timeline of OpenAI and Anthropic price cuts from June to September 2026, including GPT-5.6 Luna down 80%, Opus 5.5 at $4 / $20 / $0.20 and GPT-6.1 Sol at $2 / $10 / $0.10. It argues the cuts come from commodity models, open-weight competition (DeepSeek V4.1 Flash, Kimi K3.1 Pro, 29 OpenRouter providers) and possibly IPO positioning. It notes cache reads make up 96-99% of coding-agent token spend.

OpenRouterCodexClaude Code+3
OpenAIAnthropicGPT-5.6 Sol+16

ai-policy, coding-agents, models· Added 26 Oct 2026, published 25 Oct 2026

x.comthread

Syb (@DegenOfWallSt) on X

Nanbeige4.3-33B is a 33.1B dense, Llama-style open model under Apache-2.0, released with a base model on Hugging Face. In Nanbeige's own table it beats Qwen3.8-27B on Terminal-Bench 2.1 (80.9 vs 73.0), DeepSWE (65.5 vs 42.5) and Automation Bench, but trails on SWE-Bench Pro, GDPval and GPQA Diamond. BF16 weights are about 66 GB, split across 4 GPUs in the vLLM and SGLang examples. No independent evals exist yet.

Hugging FacevLLMSGLang+4
Nanbeige4.3-33BNanbeige4.3-3BNanbeige+8

models, coding-agents, evals· Added 26 Oct 2026, published 25 Oct 2026

interconnects.aitalk

Podcast: Kimi K3.1 Pro, the new cyber reality, and Muse musings

Interconnects podcast episode in which Nathan Lambert and Florian Brand discuss the Kimi K3.1 Pro release (about 3 trillion parameters, weights due by November 4th). They cover its Artificial Analysis score against weaker long-horizon results, Moonshot's choice to down-weight offensive cyber capability, and the PHP2Shell and LiteLLM incidents. They also cover abliterated model APIs, trusted-access cyber programs, Anthropic's junior hiring and Florian's use of the Muse agent.

PHPLiteLLMWordPress+7
KimiMoonshot AIKimi K3+28

models, ai-policy, evals· Published and added 25 Oct 2026

x.comthread

su (@sutdmhy) on X

Kimi K3.1 Pro is a Moonshot AI model, with a high-speed variant, described in a tweet as a mixture-of-experts system of about 2.8 trillion parameters with a 1-million-token context window and multimodal support. The post claims gains in coding, long-horizon agents, 3D modeling (Blender/CAD) and financial research, and says benchmarks come close to Claude Opus 5.5. Full open weights are planned by November 4. The post gives no benchmark figures.

Mixture of ExpertsBlenderLLM
Moonshot AIKimi K3.1 ProKimi+1

models· Added 26 Oct 2026, published 25 Oct 2026

coindesk.comarticle

Block's new voice AI sounds eerily human, sparking awe and scam fears

Dessa is a voice AI model from Block, trained from scratch on human speech only, with no text stage. It listens while speaking, so it handles interruptions, laughter and tone changes. Block says it trained on one Nvidia GB200 NVL72 system and that it runs locally on a MacBook Pro with M4 Max or better. Model size, benchmarks and release date are undisclosed. Early access goes to a small group of AI safety researchers. Reactions split between praise and scam fears.

Nvidia GB200 NVL72MacBook ProApple M4 Max
BlockDessaJack Dorsey+7

models, multimodal· Published and added 24 Oct 2026

en.cryptonomist.charticle

Moonshot AI reports Kim K3.1 Pro tops rivals with 64.4 on finance test

Kim K3.1 Pro is Moonshot AI's upgrade of Kimi K3, released 23 October 2026, with 3 trillion parameters, a one million token context window and a mixture-of-experts design that activates 16 of 896 experts. Moonshot reports 64.4 on OfficeQA Pro v2 (ahead of Opus 5.5 and GPT-6 Astra), 65.7% on Terminal-Bench 4.0 and 92.7% on BenchCAD (behind both). Hallucination on an internal hard test fell from 23.4% to 8.3%. Weights are due by 4 November.

LLMMixture of ExpertsKimi Delta Attention+4
Moonshot AIKim K3.1 ProKimi K3+9

models, evals· Published and added 24 Oct 2026

latent.spacearticle

[AINews] Kimi 3.1 Pro 104BA-2.8T: Fable-5.1-Class Open Weights narrows Closed-AI lead to 1 month... and Pro Highspeed API with 2-3× speed

AINews issue for 22 to 23 October 2026 centred on Moonshot's Kimi K3.1 Pro, a multimodal mixture-of-experts model with 2.8T total and 104B active parameters and 1M context. Weights are promised for 4 November 2026. Artificial Analysis scored it 55 on its Intelligence Index (fourth place), and Arena ranked it #8 in WebDev. Standard pricing is $2/$10 per million tokens. The issue also covers a cyber-data removal approach, serving-cost objections, and paid-promotion allegations. Shorter items follow on agents, evals and inference.

Mixture of ExpertsClaude CodeCursor+7
Kimi K3Moonshot AIKimi+29

models, evals· Published and added 24 Oct 2026

huggingface.copaper

IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems

IQuest-Q1 is an open-source sparse Mixture-of-Experts model with 320B total and 15B activated parameters, built for agentic coding in CLI systems. Pre-training combines Stable SplitNorm, Muon and muP with a two-stage curriculum that raises the coding-data share in stage two. Mid-training extends context, and post-training mixes SFT, domain-specialized RL and MOPD across scaffolds, followed by model merging.

Mixture of ExpertsStable SplitNormMuon+3
IQuest-Q1Hugging Face

models, training, coding-agents, research· Added 24 Oct 2026

x.comarticle

AI Quanting (@AIQuanting) on X

Kimi K3.1 Pro is Moonshot AI's post-trained Kimi K3 with a 1-million-token context, plus a Highspeed variant; weights are due by 4 November. It scores 65.7% on Terminal-Bench 4.0. Moonshot removed cyber data from mid-training and RL, and exploit pass@3 on xdev-bench-hard fell from 90.5% to 81.0%. The author argues this is a modest reduction.

LinuxNode.jsJavaScriptCore+2
Moonshot AIKimi K3.1 ProKimi K3+4

models, training, evals, ai-safety· Added 25 Oct 2026, published 24 Oct 2026

x.comthread

Hajrë Hyseni | AI for Business (@hajra) on X

Kimi K3.1 Pro is a new model from Moonshot AI. According to a post by hajra, Artificial Analysis ranks it 4th in the world, 3 points behind Claude Opus 5.5. The API price is down by a third, and full open weights are promised by 4 November. The post gives no benchmark breakdown, licence or architecture details.

LLM
Moonshot AIKimi K3Artificial Analysis+1

models, evals· Published and added 24 Oct 2026

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