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Thinky releases Inkling 975B-A41B multimodal open-weights model, claims best American Apache 2.0 open model
Thinky has released Inkling, a 975B-A41B multimodal open-weights model under Apache 2.0 licensing, alongside a smaller Inkling-Small at 276B-A12B. The release is described as the best American Apache 2.0 open model, marking Thinky's first full LLM release. The MoE architecture (active parameter counts suggest sparse mixture-of-experts) and permissive licensing make this a notable entry in the open-weights space.
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Inkling: A new open-weights model release
Simon Willison links to or comments on 'Inkling,' described as an open-weights model release. The body of the item is empty, so specific technical details, the releasing organization, and benchmark claims are not available from this source. The open-weights framing suggests relevance to the ongoing tracking of open-weights model progress.
Thinking Machines releases Inkling model, hosted on Hugging Face
Hugging Face published a welcome post for Inkling, a new model from Thinking Machines, indicating the model is being hosted or spotlighted on the Hugging Face platform. The body content is empty, so specific capability details, benchmarks, or architecture information are not available from this item. The announcement signals a new entrant in the open-weights or hosted model space from a Southeast Asian AI lab.
OpenAI Releases gpt-oss-120b and gpt-oss-20b Open-Weight Models Under Apache 2.0
OpenAI is releasing two open-weight language models, gpt-oss-120b and gpt-oss-20b, under the Apache 2.0 license. The models are claimed to outperform similarly sized open models on reasoning tasks and feature strong tool use capabilities. They are optimized for efficient deployment on consumer hardware, positioning them as cost-effective alternatives in the open-weights ecosystem.
Z.ai releases GLM-5.2, a 753B MoE open-weights model claiming top open-model ranking on agentic coding benchmarks
Z.ai released GLM-5.2, a 753-billion-parameter mixture-of-experts open-weights model optimized for long-running agentic coding tasks, with a 1-million-token input context and MIT license. The model ranks first among open-weights models on Artificial Analysis's Intelligence Index v4.1 (score 51, behind Claude Opus 4.8 at 56 and GPT-5.5 at 55) and leads all models on PostTrainBench, a benchmark for agentic fine-tuning tasks. Key technical contributions include a modified sparse attention indexer applied every four layers (cutting per-token computation 2.9x at 1M context), a switch from GRPO to PPO for long-horizon RL training, and a reward-hacking mitigation pipeline using rule-based filters and a judge model. API pricing is substantially below comparable proprietary models, and the release coincides with U.S. government restrictions on access to Anthropic's frontier models.
Nvidia releases Nemotron 3 Super 120B-A12B open-weights model with hybrid Mamba-2/MoE architecture
Nvidia released Nemotron 3 Super 120B-A12B, an open-weights LLM with a hybrid Mamba-2/transformer/MoE architecture that activates only 12B parameters per token and supports up to 1 million token context. The model claims the fastest inference speed in its size class at 442 tokens/second and leads open-weights models on PinchBench agentic task evaluation, outperforming larger models including Kimi K2.5 (1T parameters). Nvidia is releasing weights, training data, and recipes under a permissive commercial license, and plans a $26B five-year investment in open-weights models — framed partly as a strategic response to Chinese labs building capable open-weights models on non-Nvidia hardware.
Mistral AI Releases Mixtral 8x22B Under Apache 2.0
Mistral AI has released Mixtral 8x22B, a sparse Mixture-of-Experts model with 141B total parameters but only 39B active parameters, under the permissive Apache 2.0 license. The model features a 64K token context window, native function calling, multilingual support across five European languages, and strong math and coding performance. Mistral claims it outperforms all other open-weight models on standard benchmarks while being faster than dense 70B models due to sparse activation. An instructed version achieves 90.8% on GSM8K maj@8.
Mistral Small 4: Unified Multimodal, Reasoning, and Coding MoE Model Released Under Apache 2.0
Mistral AI has released Mistral Small 4, a 119B-parameter Mixture-of-Experts model (6B active per token) that unifies capabilities previously split across Magistral (reasoning), Pixtral (multimodal), and Devstral (coding agents) into a single open-weights model. The model features a 256k context window, configurable reasoning effort via a `reasoning_effort` parameter, native text and image input support, and is released under Apache 2.0. Mistral claims 40% latency reduction and 3x throughput improvement over Mistral Small 3, with benchmark results showing competitive performance against GPT-OSS 120B and Qwen models while producing significantly shorter outputs. The release includes day-0 availability as an NVIDIA NIM and support across vLLM, llama.cpp, SGLang, and Transformers.
Meta releases Llama 4 Maverick 17B-128E multimodal model on Hugging Face
Meta released Llama 4 Maverick, a 17B active parameter model with 128 experts (mixture-of-experts architecture), on Hugging Face. The model supports image-text-to-text tasks, making it a multimodal open-weights release. This is part of the Llama 4 generation, representing Meta's latest open-weights frontier push with MoE architecture.