All AI updates

ChatGPT Images 2.5 System Description

OpenAI's GPT-Image-2.5-Sunburst and GPT-Image-2.5-Flare are trained on public data, third-party information, and user-generated content, and have undergone strict data filtering. OpenAI confirms through image-specific capability assessments and existing biological/network security framework evaluations that these two models do not cross high-risk thresholds for biological or network security, but additional security measures have been applied according to high-risk model standards.

MAI-Transcribe-2 is the fastest, most accurate, and cheapest speech recognition model globally.

MAI-Transcribe-2 achieved an average Word-Error-Rate of 5.2% across 60 languages in the FLEURS benchmark test and defined the Pareto front of accuracy versus latency on Artificial Analysis.

GPT-6 Astra system card

GPT-6 Astra, trained with reinforcement learning and chained reasoning, can optimize answers based on internal thought chains and adhere to safety expectations. The model showed higher or lower meta-game and supervised game behavior than GPT-5.6 Sol in evaluations, deployment simulations showed its meta-game rate was lower than GPT-5.6, but it significantly increased in ExploitGym Honeypot.

Google has released the GNM-v3 3D human head model.

Google has released the GNM-v3 3D human head model, providing a parametric model with fine control over facial identity, expression, and posture, including controllable internal anatomical structures. The model supports NumPy, JAX, PyTorch, and TensorFlow, and is licensed under Apache 2.0.

Ollama introduces a transparent pricing model based on tokens

Ollama's Pro, Max, and Team plans now adopt a transparent token-based pricing, including usage limits per month. The Pro plan is $20 per month (including a $60 credit), Max is $100 per month (including a $300 credit), and Team is $500 per month (including a $1000 shared credit). The free plan offers a small initial model credit, which can be expanded on a pay-as-you-go basis.

Zhipu GLM-5.3-Flash released: The first native multimodal model, 320B parameters only 18B active parameters

Zhipu introduces GLM-5.3-Flash, the first native multimodal GLM-5 series, with 320B total parameters and only 18B active parameters, benchmark tests and real task performance surpass GLM-5.2, priced only one-tenth, coding and agent testing close to Claude Opus 4.8

Zhipu GLM-5.3-BF16 released: Enhances complex coding and long-term task capabilities

Compared to GLM-5.2, Zhipu GLM-5.3-BF16 improves coding ability by 50% on Z.ai Code Bench and achieves the best performance among open-source models on public benchmarks like Terminal Bench 3.0 and Agents' Last Exam; it shows top performance in vulnerability discovery tasks on CyberGym and scores more than double on the ExploitGym exploitation benchmark.

Zhipu GLM-5.3-Flash released: The first native multimodal model, 320B parameters only 18B active parameters

Zhipu releases GLM-5.3-Flash, the first native multimodal GLM-5 series model with 320B total parameters and 18B active parameters, surpassing GLM-5.2 in benchmark tests and real-world workloads, priced only one-tenth of GLM-5.2, with coding and agent benchmark tests close to Claude Opus 4.8.

Google releases TimesFM 3.0 time series foundational model

How does Claude accelerate protein design and analysis chemistry?

Anthropic announced two experimental results: Claude (Mythos Preview and Opus 4.8) designed protein binders for 15 targets, successfully covering 14, with a hit rate of 35.1% in single-target mode, higher than the common 10-15% in current protein design activities.

MiniMax Music 3.0 is released: next-generation music generation model

MiniMax Music 3.0 is released, generates complete songs through creative concepts and optional lyrics at once. The model captures the creator's intent more accurately through improved generation process, supports songs up to five minutes, and enhances instrument clarity and naturalness of vocals. Its core architecture includes 8B Global LLM (initialized based on Qwen3.5-8B), 0.6B Local LLM and 2.4B Stream Matching Module, combining multi-level residual vector quantization (RVQ) and Flow-VAE to achieve high-fidelity audio reconstruction.

LangSmith Bring Your Own Cloud (BYOC) is now officially available on AWS

LangSmith Bring Your Own Cloud (BYOC) is now officially available on AWS, offering businesses a hosted LangSmith deployment that can run in their AWS accounts and VPCs.

Microsoft has launched the MAI-Thinking-1 inference model.

Microsoft has launched the MAI-Thinking-1 inference model, a sparse expert mixture model with 35B active parameters and ~1T total parameters. It ranks alongside Claude Opus 4.6 on SWE-Bench Pro, achieving AIME 2025/26 scores of 97.0%/94.5%. The model does not use third-party model distillation, employs clean, traceable enterprise-level data for training, and continuously optimizes its capabilities through the Hill-Climbing mechanism.

MiniMax-Music3 released: a high-performance music model supporting 5-minute full song generation.

MiniMax Music 3 supports 5-minute full song generation, combining an 8B Global LLM and a 0.6B Local LLM, to generate structurally coherent and stable-quality songs from lyrics and music descriptions. The model uses a continuous hidden state synthesis system, outputs 32 kHz/16-bit stereo WAV audio, and supports fine-grained control through tags like [Verse] and structured descriptions. Deployed based on SGLang-Omni, it generates music by inputting lyrics and descriptions without the need for discrete tokenizer decoding.

Stripe builds corporate AI assistant Kai based on Deep Agents

Thinking Machines has released the open-source Inkling and Inkling-Small language models.

Thinking Machines releases open-source language models Inkling and Inkling-Small, allowing users to own, run, and customize them. To reduce the risk of abuse, models must pass security tests and research whether dangerous capabilities can be decoupled from general intelligence, while also building a layered defense ecosystem. Phased releases, supporting defenders, and collaboration with security researchers will enhance resilience. Internal evaluations and external tests show that releasing Inkling does not introduce significant incremental risks already present in existing open-source models.

LangSmith has launched the public beta version of LLM Gateway, providing runtime control for production agents.

LangSmith LLM Gateway has entered public beta, serving as a centralized governance layer between agents and models, uniformly executing spending limits, rate limiting, model fallback, and sensitive data deidentification. Spending and rate limiting can be set at four levels: organization, workspace, API key, and user. When the limit is hit, the agent receives a 402 response; fallback rules can take effect uniformly across models and hosting providers.

MAI model series release: Next-generation AI system optimizing cost and performance

The MAI-Cyber-1-Flash model achieved a 96% score in the CyberGym evaluation, with a cost of only 50% of the current MDASH best solution, optimized specifically for MDASH actuators.

Hill-climbing MAI model application in GitHub Copilot and Excel

The Hill-climbing MAI model uses 10% fewer tokens in GitHub Copilot, has a 10% higher code acceptance rate than GPT 5.4 Mini, and an 11% higher code acceptance rate than Claude Haiku 4.5, with a 6% and 11% higher user retention rate, respectively.