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Daily picks of AI news from official blogs, media, researchers and developer communities, with summaries and links to the originals.

Oct 31Sat · yesterday4 stories

Hugging Face 热门模型· Models

Efficient-Large-Model releases Open-H3-Regenerate-2K, an open replacement for the MiniMax-H3 video refinement API

Efficient-Large-Model released Open-H3-Regenerate-2K, an open replacement for the closed H3-Regenerate-2K API: a three-step MiniMax-H3 refinement pass that regenerates a 768P draft (1344×768, 121 frames) at 2560×1440. On a single B200, a 5-second clip drops from 87.26 s to 37.39 s (2.33×) with Sol-Attn, MXFP8 and CUDA graphs, and to 22.45 s (3.89×) with the fast H3 VAE decoder from StreamRender-H3. The repo provides a merged refiner LoRA, latent upscaler, fast VAE decoder and unmodified MiniMax-H3 base components; the merged LoRA matches the three separate adapters to a relative error of 2.2e-8, under the MiniMax H3 Community License.

r/LocalLLaMA· Models

Microsoft releases Mage-VL-Cowork, a 4B hybrid computer-use model scoring 66.0% on OSWorld-Verified

Microsoft's Mage Team released Mage-VL-Cowork, an open-source 4B vision-language policy that combines screenshot-grounded computer_use and persistent bash terminal execution in a single checkpoint, dynamically switching between GUI and CLI without an external orchestrator. It reaches 66.0% on OSWorld-Verified under a 50-step budget, the best among 4B models (87.5% on OS tasks, 62.7% on Multi-Application Workflows). Training uses a five-stage specialize-then-unify curriculum; the Mage-CUA-Forge workflow-first synthesis engine generates 293,806 tasks while cutting per-task generation cost by 82.6% ($0.906 → $0.158), and Online Hybrid RL adds +10.16 pp over Hybrid SFT while reducing model calls by 13.0% and output tokens by 25.4%. Upstream teacher-harness pruning lifts the GPT-5.4 teacher to…

r/LocalLLaMA· Models

Datalab releases Surya 2.5, a 689M-parameter OCR model handling layout, OCR and tables in one VLM

Datalab has released Surya 2.5, an open-source document OCR model with 689M parameters that runs layout analysis, full-page OCR and table recognition through a single VLM. It scores 85.9 on OmniParseBench versus 83.3 for Surya 2 and reaches 4.5 pages/s on one H100 at 192 DPI, about 1.7x Surya 2 with MTP. The code is Apache 2.0, weights are free for research and personal use, and inference runs locally via vllm, llama.cpp or an experimental MLX backend; table row/column geometry still requires a Surya 2 checkpoint.

Oct 30Fri1 pick · 7 stories

Hugging Face 热门模型· Models

Liquid AI releases LFM3-Audio-2B, a 2B edge audio model with 18-language speech support

Liquid AI released LFM3-Audio-2B, a compact 2B audio model that runs locally on laptops and edge devices, taking text or audio input and responding with text, 24 kHz speech, or interleaved text and speech. It supports voice chat, multilingual speech transcription/synthesis/translation across 18 languages, audio understanding and reasoning, and turning spoken requests into tool calls. It introduces an in-house audio encoder and LiquidCodec audio tokenizer with improved speech quality over LFM2.5-Audio, a 32K token context length, and streaming speech generation.

r/LocalLLaMA· Models

NVIDIA releases Metatron v1, a unified humanoid control policy for the Unitree G1

NVIDIA released Metatron v1 on Hugging Face, a unified humanoid control policy for the Unitree G1 (29 controlled joints) where walking, scene interaction and recovery share one policy, integrated with ProtoMotions. The repo includes a native PyTorch checkpoint (459,455,983 bytes with SHA256) plus two ONNX browser exports: single-robot demo/model.onnx (403,375,789 bytes) and a six-robot batched racer/network.onnx (403,036,698 bytes), with non-interchangeable interfaces. Browser integrations use MuJoCo WASM and ONNX Runtime Web (WebGPU recommended); exports were checked on 60 test states with max absolute action error 5.55e-6. The model is under the NVIDIA Open Model License with Apache-2.0 source, and no training dataset or training checkpoint is included; the post is a relay from r/LocalL…

Hugging Face 热门模型· Models

DiffuSpace releases Clover-35B-A3B-Preview, its first diffusion language model

DiffuSpace released Clover-35B-A3B-Preview, its first model, fine-tuned from Qwen3.6-35B-A3B with a 35B-parameter MoE backbone, about 3B active parameters per token, block diffusion generation, and a 128K (131,072-token) context window. Defaults include block_size=32 and threshold=0.95; BF16 weights are approximately 69 GB, and official SGLang and llama.cpp self-speculative decoding implementations are available. Repetition controls and think-end bias are pre-configured.

Hugging Face· Models

Scale AI and Hugging Face release FineART model and largest open robot dataset

Scale AI and Hugging Face have jointly released what they call the largest open robot dataset, along with their first open System 1-System 2 model that can reason over step-by-step actions. The dataset, built with FineART, contains 40K+ demonstrations across 151 tasks and 500K subtask labels. Both the dataset and model were designed for each other and are available on LeRobotHF.

PickMistral AI· Models· 8 sources

Mistral releases Mistral Large 4 (Le Chonk) open weights, a 1-trillion-parameter multimodal model focused on coding and defensive cybersecurity

Mistral has released the open weights of Mistral Large 4 (Le Chonk), a 1-trillion-parameter natively multimodal model, reporting top open-weight coding results with 19.7% on Cognition's FrontierCode 2.0 and 41% on Terminal-Bench 4.0, plus a 51% score on the Artificial Analysis Cyber Index for defensive security. The model offers Low, Medium, and High reasoning modes, was trained from scratch on European infrastructure, and ships under the Mistral Ecosystem Open-Weight license (a modified MIT license) at $0.70/M input and $2.10/M output tokens, available via Hugging Face, Microsoft Foundry, OpenRouter, and NVIDIA NIM, with an average refusal rate of 96.6% on malicious cyber requests.

The post provides concrete benchmark scores, token-efficiency figures, and three reasoning modes, letting developers compare open-weight models and choose deployment options.

Oct 29Thu2 picks · 7 stories

r/LocalLLaMA· Models

Hemmingway AI releases 27B model Hemmingway-1.5 whose writing passes AI detectors 90% of the time

South Africa-based Hemmingway AI released Hemmingway-1.5, an open-weights 27B model built on Qwen3.8-27B with 262,144 context. The company reports it passes GPTZero and four other AI detectors 90% of the time, above the 86% for real human writing, and far above Fable 5.1 (26%) and GPT-6 Astra (20%) on the same 80 CommunicationBench prompts. It ships with an OpenAI-compatible API, Mac/Windows/Android apps, vLLM and transformers instructions, and requires temperature 1.0. Licensed under CC BY-NC 4.0, free for non-commercial use with commercial use by agreement.

Hugging Face 热门模型· Models

LiquidAI releases LFM3-Omni-2B, an any-to-any omni-modal model for text, image, video and speech

LiquidAI released LFM3-Omni-2B, the first omni-modal model in its LFM3 family: a single end-to-end model that understands text, images, video and audio and answers in text and speech. The model has 2.17B total parameters, a 32K token context length, 24 kHz speech output, and processes video at 2 fps with 4 to 384 frames by default. Designed for on-device use, it replaces separate ASR, vision-language, LLM and TTS models and can jointly understand videos together with their soundtracks.

Hugging Face 热门模型· Models

openbmb releases MiniCPM-OCR 1.0, a 1.3B open-source OCR model

OpenBMB released MiniCPM-OCR 1.0, the first OCR-specific model in the MiniCPM-V/o family, a 1.3B open-source (Apache-2.0) model for text, table, formula, chart and seal understanding plus information extraction. It scores 93.68 on Real5-OmniDocBench and 54.7 on OCRBench v2, reaches 1.2 pages/s on an RTX 5090, with throughput about 1.49× PaddleOCR-VL-1.6 and 3.62× MinerU2.5 Pro, and DSpark decoding improving end-to-end efficiency by 55%. It ships with day-one support for vLLM, SGLang, llama.cpp and Ollama, plus quantized variants, a pip SDK, an API and online demos.

官方博客 · Anthropic / Meta / xAI· Models

Anthropic announces Claude Mythos and Fable 5.1, previews Model Hardware Standard

Anthropic's announcements page lists two items: the Sep 15 introduction of Claude Mythos and Fable 5.1, described as the world's most advanced models for coding and knowledge work, with research capabilities offering an early glimpse of AI's contribution to scientific progress; and the Aug 27 research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, opened to a first group of scientific research labs and advanced manufacturers.

PickThe Decoder· Models· 7 sources

Google DeepMind releases Gemini 4 Carbon, topping the Artificial Analysis Intelligence Index

Google DeepMind has released Gemini 4 Carbon just two weeks after Argon, and the new model tops the Artificial Analysis Intelligence Index v5.0 with 59 points versus Argon's 50. Built for multi-day agentic coding sessions, it ranks first in 15 of 16 Google-selected tests; third-party results are mixed, with Vals AI placing it second at 70.36% behind Claude Sonnet 5.5 (70.85%), second in Agent Arena behind Opus 5.5, and a hallucination rate rising from 4% to 11%. On security benchmarks it scores 88.2% on SEC-bench Pro and 54.8% on ExploitGym. Pricing matches Argon at $2 per million input tokens and $10 per million output tokens, with a 95% discount on cached input; access starts with selected security experts before expanding to developers and consumers.

PickHugging Face Blog· Models· 6 sources

NVIDIA Releases Open Speech Model Nemotron 3.5 Transcribe with Granary v2 Data Pipeline

NVIDIA released Nemotron 3.5 Transcribe, an open-weight promptable speech model combining transcription in 40 languages, translation for 31 languages to or from English, speaker attribution in 13 languages, and audio Q&A in a single checkpoint handling up to one hour and eight speakers. It leads open-weight models on the Hugging Face Open ASR Leaderboard for English at 5.33% average WER and achieves 2.8% AA-WER with roughly 4B active parameters out of 30B via a hybrid Mamba–Transformer MoE. The company also open-sourced the Granary v2 data pipeline with manifests covering 463,062 hours across 48 languages; in a medical case study, fine-tuning cut held-out WER from 22.44% to 12.17%, a 45.8% relative reduction.

The post provides full benchmark numbers and a reproducible fine-tuning path, letting developers assess whether this speech model fits their own use cases.

Oct 28Wed3 picks · 8 stories

r/LocalLLaMA· Models

BeeNara v0.4: A 332 MB Local Document Classifier Achieves 91.5% Accuracy on Unseen Folder Trees, with a New 2B Sibling Model

The author released BeeNara v0.4, a 332 MB CPU-based local document classification model under the Apache-2.0 license. On tasks involving unseen folder trees (1,500 samples), accuracy improved from 70% in v0.2 to 91.5%. Using a Learn-then-Test threshold, it guarantees that automatic archiving errors do not exceed 1% with 90% confidence, achieving an actual auto-archiving rate of 59% with only 0.3% error. Additionally, a new sibling model, BeeNara Big, based on Qwen3.5-2B-Base with LoRA and a decision head, can process entire folder trees (up to ~600 folders) and page images, achieving 92–94% accuracy within 24 folders. However, it requires a GPU (approx. 4.3 GB at 8-bit). The author also noted that label smoothing causes threshold failure.

r/LocalLLaMA· Models

DiffuSpace releases Clover-35B-A3B-Preview, its first open-source diffusion language model

DiffuSpace released Clover-35B-A3B-Preview, its first open-source diffusion language model, built on a Qwen3.6-35B-A3B MoE backbone adapted for text-only block diffusion generation, with the launch blog claiming state-of-the-art results among open-source diffusion LLMs at release. It retains the hybrid Gated DeltaNet/full-attention MoE backbone (40 layers, 256 routed experts, top-8 routing plus a shared expert), with 35B total parameters, about 3B active per token, and a 128K (131,072) context window. Inference uses block diffusion with LowConfidence decoding (defaults block_size=32, threshold=0.95), includes repetition and soft length/think-end controls; BF16 weights need about 69 GB, with self-speculative decoding available in SGLang and llama.cpp implementations.

Hugging Face 热门模型· Models

Tencent Releases Hy-SimulMT 30B Model for Bidirectional Real-Time Speech Translation and Voice Cloning with ~3s StreamLAAL

Tencent has released the Hy-SimulMT model, a low-latency, high-quality model supporting bidirectional real-time speech-to-speech translation and real-time voice cloning between Chinese and English. In the RealSI long-form audio evaluation, Hy-SimulMT achieved an approximate StreamLAAL of 3 seconds, the lowest among compared systems. Its GEMBA score exceeded those of compared open-source models and four of the five commercial APIs.

PickHugging Face 热门模型· Models

ccore releases Qwen3.5-4B-3D-Coder, an early-preview 3D fine-tune of Qwen3.5-4B

Independent developer CCORE released an early preview of Qwen3.5-4B-3D-Coder, an independent fine-tune of Qwen/Qwen3.5-4B (not an official Qwen release), focused on general coding and generating interactive 3D scenes with Three.js. The Q4_K_M and Q8_0 quantizations were updated on October 26, fixing a layer-related issue and improving one-shot scene generation. Training is expected to finish October 28, 2026, 07:30 UTC, after which FP16 weights, all quantized versions, the training dataset, and an evaluation report will be published. Multi-token prediction (MTP) must be disabled in LM Studio for the model to run properly.

The author shares the training schedule, plans to release the dataset, and notes that MTP must be disabled in LM Studio, helping readers gauge this 4B model's feasibility for 3D generation.

Hugging Face 热门模型· Models

Baidu Releases Unlimited-OCR-2, Achieving Unlimited-Horizon Parsing with SR-SWA

Baidu released the Unlimited-OCR-2 model, leveraging the Sparse Reference Sliding Window Attention (SR-SWA) mechanism for unbounded document parsing. SR-SWA compresses text-visual attention interactions into a fixed-size set of working references, keeping per-step decoding latency constant regardless of document length. The model achieves state-of-the-art performance across multi-page and ultra-long document benchmarks like MPDocBench and MarathonDocBench.

r/LocalLLaMA· Models

Qwen3.8-27B SLQ Quantized GGUF Files Released with EAR@10 Performance Data

The Qwen3.8-27B model has been released using customized SLQ (Statistically-Lossless Quantization) technology in GGUF format. Three models, EAR98, EAR98.5, and EAR99, are provided with specific file sizes and EAR@10 performance metrics. EAR measures the probabilistic overlap between the original BF16 model and the quantized tokens.

PickHugging Face Blog· Models· 6 sources

LiquidAI Releases LFM3 Foundation Model: Integrating Six Modalities for On-Device Specialization

LiquidAI launches LFM3, its next generation of Liquid Foundation Models, integrating text, vision, audio, omni, and decision models into a shared 2B parameter-class backbone. LFM3 utilizes a new tri-hybrid architecture, achieving superior performance to LFM2 models while reducing parameters by 35%. This model series includes six specialized variants designed for edge deployment, such as LFM3-1.7B, which requires approximately 1 GB at 4-bit precision for its text model.

LFM3 integrates text, vision, audio, and decision models into a shared backbone, enabling specialized cross-modal capabilities and on-device deployment.

PickGoogle DeepMind· Models· 6 sources

Google DeepMind releases Genie 4 world model with real-time interaction and native audio

Google DeepMind announced Genie 4, a new world model released as a research preview for trusted testers, coming next to Google AI Ultra subscribers in Project Genie and early access partners of the Gemini API and Google AI Studio. Built on the Gemini family, Gemini Omni anchors simulations in real-world appearance and behavior while Gemini 3.8 Flash acts as a guiding agent in the loop, breaking down goals, reviewing frames, and adapting plans in real time. Genie 4 is DeepMind's first real-time world model to generate audio natively, supporting ambient sound, music, and interactive dialogue, and simulates physics scenarios like aerodynamics and collisions with naturally moving characters. Trusted testers across filmmaking, journalism, gaming, and engineering are using it for pre-visualizat…

The official blog details real-time interaction, native audio, and Gemini integration along with known limitations, giving readers a grounded view of progress in world model realism and controllability.

Oct 27Tue1 pick · 5 stories

Hugging Face 热门模型· Models

NVIDIA releases Nemotron-3.5-Bolt-E4B-4GB quantized small model

NVIDIA released NVIDIA-Nemotron-3.5-Bolt-E4B-4GB on Hugging Face, a Q4_K_M quantized version of its small language model post-trained from Gemma-4-E4B-it, with 8B total parameters (4B effective) and up to 64K token input and output context. Designed for low-memory, low-TTFT operation, it targets local voice and device assistants, interactive personas, and embedded interfaces, improving multi-turn tool use, instruction following, and input grounding, with thinking-mode chat-template controls and optional DFlash drafter for speculative decoding, under the OpenMDW-1.1 license for commercial use.

r/LocalLLaMA· Models

inclusionAI releases Ling-3.1-flash-1019: 560B MoE with 1M context and improved reasoning and agentic performance

inclusionAI released Ling-3.1-flash-1019, an upgrade of Ling-3.1-flash with 560B total parameters (25B activated), a hybrid-linear MoE architecture, and 1M context. Post-training improvements raise AA-Briefcase from about 1400 to 1524 Elo, AutomationBench-AA from 62% to 68%, CritPt from 18% to 26%, SciCode from 54% to 57%, and the Artificial Analysis Intelligence Index v4.3.2 score from 41 to 44. SGLang offers day-0 support with MTP (NEXTN) speculative decoding and Hopper decode optimizations, vLLM deployment instructions are provided, and a training-content summary PDF is published.

r/LocalLLaMA· Models

Baidu releases Unlimited-OCR-2, enabling unlimited-horizon document parsing with SR-SWA

Baidu's team released Unlimited-OCR-2, which uses Sparse Reference Sliding Window Attention (SR-SWA) to compress text-visual attention over ultra-long sequences into a fixed set of working references (e.g., 512 tokens), keeping per-step decoding latency and memory nearly constant so documents of unbounded length can be parsed within a finite context window. The model reports SOTA on multi-page benchmarks like MPDocBench and extreme hundred-page benchmarks like MarathonDocBench; the model card provides Transformers and SGLang inference with memory-tuning knobs, plus vLLM inference and ms-swift training support. The paper is at arXiv 2606.23050.

Simon Willison· Models

OpenAI releases GPT-6.1 Terra focused on visual reasoning and computer use, at nearly half the price

OpenAI released GPT-6.1 Terra, a fast, efficient midrange model emphasizing visual reasoning, computer use, and clearer writing, described as a significant step up from GPT-5.6 Terra. It is priced at $1/million input tokens and $5/million output—almost half the price of GPT-5.6 Terra and GPT-6.1 Sol, and around 10x the price of GPT-6 Luna. The author compared pelican outputs across reasoning levels of OpenAI's current lineup (GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6 Luna), with the "max" level costing 11.3161 cents and taking 4 minutes 11 seconds. OpenAI's Ted Sanders said on Hacker News that Terra is likely better than Astra and Sol at technical communication, similar on vision and computer use but much faster, and a bit worse on most other things.

PickThe Decoder· Models· 4 sources

OpenAI releases GPT-6.1 Terra: API prices halved while closing in on its larger models

OpenAI has released GPT-6.1 Terra, with API prices half those of GPT-5.6 Terra: $1 per million input tokens, $5 for output, and cached inputs at $0.05. According to Artificial Analysis, it scores 48 on the Intelligence Index, up 6 points over GPT-5.6 Terra, at about a third of the cost per task ($0.40 versus $1.40), and solves 50.3% on Terminal-Bench 4.0, up from 21.5%. It is now available to Plus, Pro, Enterprise, and Edu users in ChatGPT Work, Codex, and via the API.

The article compiles the API price cut and multiple benchmark results, letting readers compare the model's cost-performance position against Sonnet and Opus.

Oct 26Mon2 stories

r/LocalLLaMA· Models

Tencent Hunyuan open-sources Hy-SimulMT-30B-A3B real-time simultaneous translation model

Tencent Hunyuan released Hy-SimulMT-30B-A3B, a real-time simultaneous translation model supporting bidirectional Chinese-English speech-to-speech translation with real-time voice cloning, open-sourced on Hugging Face with FP8 and GGUF variants. On the RealSI long-form audio benchmark it achieved a StreamLAAL of about 3 seconds, the lowest among compared systems, with a GEMBA score exceeding the compared open-source models and four of five commercial APIs; in a small-scale comparison its quality was on par with CATTI-certified interpreters, often with lower latency. GitHub provides the SimulInfer inference service and SimulTrain training tools; speech output and voice cloning require a configured TTS service.

r/LocalLLaMA· Models

Ternary-Nemotron-3.5-Lightning-30B-A3B GGUF release: 368K context on a 12 GB GPU

boro64 repackaged Nota AI's 1.58-bit ternary weights of NVIDIA Nemotron 3.5 Lightning 30B-A3B from MLX into a lossless GGUF Q2_0 file (8.82 GB) that runs in both stock llama.cpp and the PrismML fork. On an RTX 4070 Ti 12 GB, the ~9.5 GB of weights fit fully on GPU up to 368K context, with 172 tok/s decode and ~7000 tok/s prefill; needle retrieval passes 3/3 up to 341K and 2/3 at 410K. Quality is about 89% of the BF16 teacher: strong at long-context reading, retrieval and summarization, weaker at complex coding and math. The writeup includes practical tuning notes such as a 20x WDDM VRAM-demotion slowdown and a warning against --kv-vram-cells.