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#模型发布

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Today · Sep 30Wednesday · 5 items

AI HOT picks · Models

GPT-6.1 Sol replaces GPT-6 Sol 7 days after launch, 1 point behind GPT-6 Astra on intelligence index

GPT-6.1 Sol replaced GPT-6 Sol 7 days after launch. Its intelligence index is 1 point below GPT-6 Astra, and pricing stays at $2 per million input tokens and $10 per million output tokens. The cached-read discount rises from 90% to 95%.

Why it matters: Side-by-side intelligence index, cost and token-efficiency figures let readers judge the trade-off GPT-6.1 Sol makes between price and capability.

AI HOT picks · Models

GPT-6.1 上线 Arena 的 Agent Arena 评测平台

Arena 宣布 OpenAI 的 GPT-6.1 已上线 Agent Arena,用户投票将影响其评估,分数即将公布。Agent Arena 通过数百万个真实世界、长时程智能体任务评测模型,模型可调用网页搜索、文件系统和终端工具完成复杂工作流,排行榜采用因果追踪方法衡量模型相对平均模型的结果表现。

AI HOT picks · Models

OpenAI releases GPT-6.1 Sol, strengthening agentic coding and computer use

OpenAI released GPT-6.1 Sol, upgrading agentic coding and computer use to near Astra performance. Cached input is priced at a 95% discount to standard input. The model targets complex refactors, deep codebase investigations and long-running agents that work across apps.

Why it matters: With GPT-6.1 Sol, readers can see the capability upgrades in agentic coding and computer use, and the cached-input pricing.

TechCrunch · AI

OpenAI releases GPT-6.1 Sol, says it nears GPT-6 Astra at a lower price

At DevDay, OpenAI released GPT-6.1 Sol, saying it approaches GPT-6 Astra's intelligence on agentic coding, computer use and professional work, while standard input and output token prices are one-fifth of Astra's.

Why it matters: Readers can see GPT-6.1 Sol's specific gains in agentic coding and factual accuracy, plus why GPT-6.1 Astra was held back over safety concerns.

The Decoder

OpenAI releases GPT-6.1 Sol, nearing Astra at one-fifth the cost

OpenAI released GPT-6.1 Sol, saying it approaches the flagship GPT-6.1 Astra on agentic coding, computer use and office tasks, at about one-fifth the cost. Astra was not released as planned over safety concerns.

Why it matters: The original gives Sol's pricing and benchmark comparisons against Astra and Opus 5.5, a basis for judging the capability limits of the cheaper alternative.

Yesterday · Sep 29Tuesday

The Decoder

ElevenLabs' new v4 speech model makes AI voices more expressive and consistent

ElevenLabs 发布 Eleven v4 语音模型,能更准确跟随脚本中的情绪、停顿与音效标签,并在长篇制作中保持音色一致。新架构同时驱动 Turbo 版本,官方测试中约 150 毫秒开始输出语音,对比 Cartesia Sonic 3.6 的 262 毫秒和 OpenAI GPT-4o mini TTS 的 814 毫秒。

OpenAI News

OpenAI releases GPT-6.1 Sol model

OpenAI released GPT-6.1 Sol, positioned as near-Astra-level intelligence for coding, computer use and professional work. Standard API input and output tokens cost one-fifth of Astra's price.

Why it matters: OpenAI's GPT-6.1 Sol launch shows the capability target for coding and computer use, plus the pricing shift.

Sep 25Friday

Google DeepMind

Google DeepMind releases Gemini 3.8 Live with Live Avatar

Google DeepMind released Gemini 3.8 Live with Live Avatar, adding near-real-time video generation to its native real-time conversation model. The result is a dynamic visual avatar with lip sync, natural expressions and smooth turn-taking.

Why it matters: The post details Live Avatar's real-time video conversation, async tool calls and 97-language support, a useful read on enterprise multimodal interaction.

Sep 8Tuesday

Ben's Bites

OpenAI drops GPT-6 Astra; author burns 4B tokens and builds 'nothing really'

OpenAI released Astra, the first GPT-6 family model. The author burned 4B tokens over the weekend and built 'nothing really,' but admits it might be a skill issue. Astra tops ARC-AGI-3 and Zapier's AutomationBench, priced same as Fable 5.1. It's spiky—great at some tasks, not consistently strong. People are using it to rebuild Manhattan in Unreal Engine, generate UIs, 3D-print parts, and identify sounds from spectrograms. In Codex, Astra can skip waiting for user answers and continue working. OpenAI also hit its 'automated research intern' goal, targeting an automated AI researcher by March 2028. Anthropic is testing Claude Code plugins for extended functionality, not shipped yet.

Aug 12Wednesday

Google DeepMind

Google DeepMind releases SL2T sign language-to-text model, first in Pixel 11 Gboard and Live Transcribe

Google DeepMind released SL2T, a multilingual sign language-to-text model, bringing sign language AI into consumer products for the first time. On Pixel 11, Gboard and Live Transcribe support American Sign Language (ASL) to English dictation, with more devices and languages to follow.

Why it matters: It gives SL2T's training scale, benchmark results and privacy design, so readers can judge the real limits of sign language translation in consumer products.

Jul 21Tuesday

Google DeepMind

Google DeepMind releases Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber

Google DeepMind released three new models: Gemini 3.6 Flash, 3.5 Flash-Lite, and the security-focused 3.5 Flash Cyber.

Why it matters: It gives pricing, token efficiency and benchmark comparisons for all three models, so readers can judge cost and model choice for agent workflows.

Jul 17Friday

Google DeepMind

Google DeepMind releases Gemini 3.5 Flash Cyber security model

Google DeepMind released Gemini 3.5 Flash Cyber, fine-tuned from 3.5 Flash to find, verify and patch vulnerabilities quickly. With multiple calls, it approaches larger models on benchmarks such as CyberGym.

Why it matters: It reports how a lightweight security model performs on several benchmarks and inside Google's own codebase, so readers can judge the cost-benefit for vulnerability discovery.

Jun 10Wednesday

AI HOT (Curated Pool)

Anthropic launches safety-treated Mythos-class model Claude Fable 5

Anthropic released Claude Fable 5, a safety-treated Mythos-class model; in high-risk cyber, biochemistry, and distillation domains, it automatically falls back to Opus 4.8, with one trigger per 20 conversations on average.

Why it matters: Anthropic model launches sit in the 85–94 band; HKR-H/K/R all pass via the safety fallback hook, named mechanism, and Claude-user relevance. X-only sourcing limits confidence, so it stays below the top band.

Jun 9Tuesday

AI HOT (Curated Pool)

Cohere Releases North Mini Code, an Open Coding Model for Developers

Cohere released North Mini Code, a 30B-parameter MoE coding model with 3B active parameters, under Apache 2.0; it supports 64K/128K context lengths and reaches 80.2% pass@10 on SWE-Bench Verified.

Why it matters: HKR-H comes from a compact MoE code model with a strong SWE-Bench claim; HKR-K has params, license, context, and benchmark. Cohere is notable but not a frontier-lab launch, so this fits the 78–84 open-source code-model band.

Google DeepMind

Google DeepMind releases Gemini 3.5 Live Translate speech model

Google DeepMind released Gemini 3.5 Live Translate, an audio model for near-real-time speech-to-speech translation across more than 70 languages. It detects the language automatically and preserves the speaker's intonation, rhythm and pitch.

Why it matters: The original gives the model's language coverage, how the live translation works and the rollout pace across products, enough to judge where speech translation is usable.

AI HOT (Curated Pool)

Google DeepMind Releases Gemma 4 12B, a Unified Encoder-Free Multimodal Model

Google DeepMind released Gemma 4 12B, a multimodal model with a unified encoder-free architecture, native audio input, Apache 2.0 licensing, and local laptop runtime with 16GB of VRAM or unified memory.

Why it matters: HKR-H/K/R all pass: the hook is local multimodal audio in 16GB VRAM, and the new architecture is concrete. It is a strong Google DeepMind open-model release, but not a frontier-model launch, so it stays below p1.

Jun 8Monday

AI HOT (Curated Pool)

Amap Releases 3D-Native City World Model ABot-Earth0.5

Amap released ABot-Earth0.5, a 3D-native city world model covering more than 190 countries and regions, generating kilometer-scale 3D cities from satellite images or text within 10 minutes on consumer GPUs.

Why it matters: HKR-H/K/R all pass: Amap’s ABot-Earth0.5 has concrete claims, including 190+ countries and 10-minute km-scale 3D city generation. Strong world-model product signal, but below a major foundation-model release.

Jun 7Sunday

r/LocalLLaMA

Cohere's Unreleased Coding Model Gets Early Access for LocalLLaMA

Cohere employee Nick Frosst opened early testing of BLS-Mini-Code-1.0 to LocalLLaMA, with weights on Hugging Face before public launch. The coding model has 30B total parameters and 3B active parameters, and Cohere says token output tests are in line with similar models in its size class.

Why it matters: HKR-H/K/R all pass: early-access Cohere coding weights with 30B/3B specifics matter to local-model users. Reddit sourcing and missing evals, license, and training details keep it in the low featured band.

Jun 6Saturday

AI HOT (Curated Pool)

OpenCV 5 Released with New DNN Engine and Native LLM Support

OpenCV 5 introduces a graph-based DNN engine, raising ONNX operator coverage from under 23% in 4.x to over 80%, with native support for Transformer, VLM, and LLM workloads.

Why it matters: HKR-H/K/R all pass for a substantive OpenCV major release: graph DNN engine, ONNX coverage jump, and native Transformer/VLM/LLM support. Strong featured item, but below must-write model-lab release territory.

AI HOT (Curated Pool)

Google AI weekly product updates: Nano Banana 2, Co-Scientist, dreambeans, Gemma 4, and more

Google AI announced six updates: Nano Banana 2 is generally available, Gemma 4 12B can run fully offline on laptops, and Magenta RealTime 2 is open source.

Why it matters: HKR-H/K/R all pass: the post bundles six Google AI updates with concrete local and open-source hooks. Lacking benchmarks, licensing, and pricing keeps it below the 78+ good-quality band.

Jun 5Friday

AI HOT (Curated Pool)

Google Magenta RealTime 2 (MRT2) real-time music model released

Google AI for Developers released the open-weight Magenta RealTime 2 music model, supporting MIDI, live text prompts, and gestures, with native MacBook latency under 200 ms.

Why it matters: HKR-H/K/R all pass: Google Magenta MRT2 has a concrete real-time audio hook, open weights, and sub-200ms local latency. It is strong for creative-AI builders, but narrower than a general foundation-model release.

Jun 4Thursday

AI HOT (Curated Pool)

Ideogram 4.0 Open-Source Text-to-Image Model Released

Ideogram released Ideogram 4.0, an open-source text-to-image model with a 9.3B-parameter core, a single-stream DiT architecture, Qwen3-VL-8B-Instruct text encoder, and a No. 4 ranking in DesignArena human evaluation.

Why it matters: HKR-H/K/R all pass: Ideogram 4.0 brings open weights, 9.3B parameters, single-stream DiT, and a No. 4 human-eval rank. It is strong open image-model signal, not a top-tier general-model launch.

AI HOT (Curated Pool)

Miso One Open-Sources Voice Model: 8B Parameters, 110ms Latency, One-Shot Voice Cloning

Miso One released an 8B-parameter open-weight TTS model with one-shot voice cloning from a short sample, 110ms inference latency, GitHub self-hosting without an API, and local audio data handling; the post says API access is coming but does not disclose pricing or launch timing.

Why it matters: HKR-H/K/R all pass, but this is a single X-sourced launch with no benchmark suite, license detail, or third-party reproduction. The 8B, 110ms, self-hosted open TTS facts clear featured, not higher.

Jun 3Wednesday

AI Chat-Group Daily (群聊日报)

2026-06-02 Chat Group Daily

The chat group daily says Microsoft released MAI-Thinking-1 with 35B active parameters and about 1T MoE, matching Opus 4.6 on SWE-Bench Pro and scoring 97% on AIME 2025.

Why it matters: HKR-H/K/R all pass: a Microsoft reasoning-model claim with concrete benchmark numbers. Source authority is weak, and the summary lacks official release, access terms, and full eval setup, so it stays below P1.

AI HOT (Curated Pool)

Qwen3.7 Released with Upgrades to Reasoning and Agent Capabilities

Qwen released Qwen3.7, and the post says it upgrades reasoning, tool use, coding, and long-horizon agent tasks; the post does not disclose model size, pricing, benchmark scores, or release conditions.

Why it matters: HKR-H and HKR-R pass because Qwen3.7 is a flagship Alibaba model update with practitioner relevance. HKR-K fails: the post names capability areas but gives no params, pricing, benchmarks, or access terms.

AI HOT (Curated Pool)

Microsoft releases its first advanced reasoning AI model, MAI-Thinking-1

Microsoft released MAI-Thinking-1 at Build 2026, describing it as a medium-sized reasoning model that matches leading models on key software engineering benchmarks.

Why it matters: HKR-H/K/R all pass: Microsoft released its first advanced reasoning model with a mid-sized design and SWE benchmark claim. Exact scores, access, and pricing are not disclosed, so it stays below 85.

Jun 2Tuesday

AI HOT (Curated Pool)

StepFun releases Step 3.7 Flash as an open-weight model for agentic coding

StepFun released the open-weight Step 3.7 Flash model for fast agentic coding, with tool calling and multimodal understanding, and the model is already available in Kilo alongside MiniMax M3.

Why it matters: HKR-H/K/R pass on the open-weight agentic-coding angle and Kilo availability. Missing benchmarks, size, license, and pricing keep it at the lower featured threshold.

Jun 1Monday

QbitAI · WeChat

How Cloud Models Reach the Physical World: CMG Lion Rock AI Lab Uses LiOS for Embodied AI

CMG Lion Rock AI Lab released the LiOS edge-cloud architecture for embodied robotics, reporting about 30 ms one-way latency from local camera to cloud GPU memory in cross-machine tests, and open-sourced the low-latency video transmission module plus the LeFold laundry-folding dataset.

Why it matters: HKR-H/K/R pass: LiOS offers a concrete latency claim and open artifacts for embodied AI. Impact stays mid-tier because the lab is not a top platform vendor and no cross-source cluster is shown.

AI HOT (Curated Pool)

Cosmos 3 Released: First Open Physical AI Generalist Model

NVIDIA released Cosmos 3 as an open physical AI generalist model with native visual reasoning, world generation, and action generation, offering two variants: Super at 32B parameters and Nano at 8B parameters.

Why it matters: HKR-H/K/R all pass: NVIDIA names two Cosmos 3 variants and concrete physical-AI capabilities. Source is a single launch post with no benchmark or license detail, so it stays in the 78–84 band.

AI HOT (Curated Pool)

MiniMax M3: Frontier coding, 1M-token context, and native multimodal model

MiniMax released M3 as an open-source unified model with coding, agent, and native multimodal capabilities, supporting a 1M-token context window and using MiniMax Sparse Attention to cut per-token compute at 1M context to 1/20 of its predecessor, with over 9x faster prefill and over 15x faster decoding.

Why it matters: HKR-H/K/R all pass: MiniMax M3 has a 1M-token context hook, MSA with a claimed 20x cost cut, and open-source China-model resonance. Single official-source release keeps it in the 78–84 band, not P1.

May 31Sunday

Xinzhiyuan · WeChat

Fudan-Linked Team Releases STI-WM Spatiotemporally Integrated World Model

MouShen Intelligence released STI-WM, a spatiotemporally integrated world-action model for robotics, claiming support for RGB, point-cloud, and proprioceptive inputs, hundred-second task planning, and disclosing five funding rounds in six months plus a RMB 300 million Pre-A round.

Why it matters: HKR-H/K/R pass: STI-WM combines RGB, point clouds, and proprioception for 100-second planning, plus 5 funding rounds and a RMB300m Pre-A. Company-claim framing lacks public benchmarks or reproducible access, so it stays near the featured threshold.

QbitAI · WeChat

Robot-Native World Action Model Debuts With Spatiotemporal Architecture From Fudan-Linked Team

Moushen Intelligence released STI-WM, a spatiotemporally integrated world action model for robotics, with RGB, depth point cloud, and proprioceptive inputs; the post says it supports hundred-second-scale long-horizon task rollout and closed-loop replanning, but does not disclose benchmark scores or deployment costs.

Why it matters: HKR-H/K/R all pass: the STI-WM angle is novel, with concrete input modalities and hundred-second rollouts. Kept near the featured floor because public weights, benchmark results, and reproducible tests are not disclosed.

May 30Saturday

AI HOT (Curated Pool)

OpenAI launches real-time translation model with 70+ input languages

OpenAI launched gpt-realtime-translate, a speech translation model that accepts 70+ input languages and outputs speech in 13 target languages; the post says the feature is running on smart glasses.

Why it matters: HKR-H/K/R all pass: OpenAI has a concrete realtime-translation model with numbers and a wearable demo. Missing latency, pricing, and API availability keep it below P1.

May 29Friday

AI HOT (Curated Pool)

Nano Banana Pro and Nano Banana 2 officially released

Google AI Developers released Nano Banana Pro and Nano Banana 2, two image models available for production use through the Gemini API; the post names gemini-3-pro-image and gemini-3.1-flash-image but does not disclose pricing, benchmarks, or rate limits.

Why it matters: HKR-H/K/R all pass: Google shipped two production image models via Gemini API. The post gives no benchmarks, pricing, or safety mechanism, so this stays in the 78–84 band rather than p1.

The Verge · AI

Claude’s New Model Is More ‘Honest’ When It Messes Up

Anthropic will release Claude Opus 4.8 on Thursday, emphasizing its claimed “honesty.” The company says early testers found it flags uncertainty more often. It also says internal evaluations show Opus 4.8 is around 4x less likely than its predecessor to make unsupported claims, while the RSS snippet does not disclose the full benchmark setup.

Why it matters: HKR-H/K/R all pass: an Anthropic Claude model update with a concrete “4x fewer unsupported claims” eval claim. Details are thin: benchmark set, pricing, and context window are not disclosed, so it sits in the low 85–94 band.

May 28Thursday

AI HOT (Curated Pool)

Mistral AI launches physics AI model for industrial engineering

Mistral AI integrated the Emmi AI team and launched a physics AI foundation model for industrial engineering, with the post saying it can learn from geometry, boundary conditions, or measurement data and predict full physical fields on a single GPU in seconds.

Why it matters: HKR-H/K/R pass: a major model lab entering physics simulation with a concrete single-GPU seconds claim. The score stays in the lower featured band because model name, benchmarks, pricing, and access are not disclosed.

May 25Monday

r/LocalLLaMA

NuExtract3 released: open-weight 4B VLM for Markdown, OCR and structured extraction

Numind released NuExtract3, a 4B open-weight VLM based on Qwen3.5-4B under Apache-2.0, supporting image and text to Markdown, OCR, and JSON-template extraction, with self-hosting from 4GB VRAM and weights in Safetensors, GGUF, and MLX formats.

Why it matters: HKR-H/K/R all pass: NuExtract3 packages OCR, Markdown, and structured extraction into a 4B open-weight VLM with a 4GB self-hosting condition. Source and lab reach keep it in the low featured band.

May 22Friday

AI HOT (Curated Pool)

Zhipu releases GLM-5.1-highspeed, claiming a large-model API speed record

Zhipu released the GLM-5.1-highspeed API to selected enterprise customers on May 22, with a claimed output speed of 400 tokens/s, built by the GLM team and TileRT team through system-level optimization.

Why it matters: HKR-H/K/R all pass: Zhipu’s GLM-5.1 high-speed API has a concrete 400 tokens/s claim and domestic flagship-model relevance. Test setup, pricing, and availability are not disclosed, so it stays in the 78–84 band.

May 21Thursday

r/LocalLLaMA

Tencent Hy-MT2 30B/7B/1.8B

Tencent released Hy-MT2 translation models in 1.8B, 7B, and 30B-A3B sizes, supporting translation across 33 languages; AngelSlim 1.25-bit quantization reduces the 1.8B model’s storage requirement to 440 MB and raises inference speed by 1.5x.

Why it matters: HKR-H/K/R pass via the 440MB quantized 1.8B model, 33-language support, and local inference cost angle. Sparse Reddit sourcing keeps it at the featured threshold, not the 78+ band.

r/LocalLLaMA

What happened to Cohere’s Command-A series of models?

Cohere launched Command A+, describing it as its first MoE model under the Apache 2.0 license, with quantization work that lets it run well on 1 or 2 GPUs; the post says top-line performance still needs work.

Why it matters: HKR-H/K/R pass: Cohere open model news has clear local deployment facts. Reddit-level sourcing and missing parameter count, benchmarks, and context window keep it in the low featured band.