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Kimi K3 2.8T-A50B released: largest open model ever, Opus 4.8-class performance at Sonnet 5 pricing
Moonshot AI has released Kimi K3, a 2.8 trillion total parameter MoE model with 50 billion active parameters, described as the largest open model ever released. The model is reported to achieve performance comparable to Claude Opus 4.8 while being priced at the level of Sonnet 5, representing a significant cost-performance advance. This release continues a strong week for open-weights models and raises the ceiling for publicly available model scale.
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Kimi K2.6: Moonshot AI's 1T-Parameter Vision-Language Model Matches Open-Weights Peers, Trails Top Closed Models
Moonshot AI released Kimi K2.6, a 1 trillion-parameter mixture-of-experts vision-language model with 32B active parameters, designed for long-horizon autonomous coding sessions lasting multiple days and multi-agent orchestration scaling to 300 parallel subagents executing up to 4,000 steps. The model matches Qwen3.6 Max Preview and DeepSeek-V4-Pro on the Artificial Analysis Intelligence Index (scoring 54 vs. their 52) while trailing closed models like GPT-5.5 and Claude Opus 4.7. Weights are freely downloadable from Hugging Face under a modified MIT license permitting commercial use, with API access priced at $0.95/$0.16/$4.00 per million input/cached/output tokens. Notable features include a 256K token context window, native INT4 quantization, a 'preserve thinking' mode for multi-turn reasoning continuity, and a research preview 'claw groups' feature enabling cross-developer agent collaboration.
Simon Willison on Kimi K3 and the pelican benchmark as a model evaluation tool
Simon Willison writes about Kimi K3, a new model from Moonshot AI, using his informal 'pelican benchmark' as a lens for evaluation. The post reflects on what idiosyncratic, qualitative benchmarks can still reveal about model behavior that formal evals miss. As a tier-2 commentary piece, it offers practitioner-level perspective on a new open-weights or API-accessible model.
Latest open artifacts (#21): Open model bonanza — Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others
Interconnects' recurring open-weights roundup covers a dense cluster of recent releases including Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, and GLM-5.1, characterizing the period as a flagship-after-flagship cadence. The piece also includes commentary on CAISI's assessment of DeepSeek V4. As a tier-2 commentary source, this is a synthesis and analysis layer rather than primary announcements.
Simon Willison quotes Kimi K3
Simon Willison shares a brief quote or observation about Kimi K3, a model from Moonshot AI. The content body is empty, suggesting this is a short link or quote post. The item signals community attention to the Kimi K3 model release or capability.
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.
GPT-5.5 Outperforms Benchmarks but Leads in Hallucination Rate; Kimi K2.6 Tops Open LLMs
GPT-5.5, OpenAI's latest closed vision-language model built for agentic coding and computer use, tops the Artificial Analysis Intelligence Index and ARC-AGI-2 benchmarks but exhibits a significantly higher hallucination rate (85.53%) compared to Claude Opus 4.7 (36.18%) and Gemini 3.1 Pro Preview (49.87%) on the AA-Omniscience benchmark. GPT-5.5 Pro processes reasoning tokens in parallel during inference, and pricing is roughly double GPT-5.4 rates. The model ranks lower on subjective Arena.ai leaderboards, where Claude Opus models dominate. The issue also notes Kimi K2.6 leading open-weight LLMs, though details on that item are truncated.
Qwen3 Release: Flagship 235B MoE and Full Model Family Announced
Alibaba's Qwen team has released Qwen3, a new family of large language models including the flagship Qwen3-235B-A22B mixture-of-experts model. The flagship model claims competitive benchmark performance against DeepSeek-R1, OpenAI o1/o3-mini, Grok-3, and Gemini-2.5-Pro on coding, math, and general capabilities. A smaller MoE variant, Qwen3-30B-A3B, reportedly outperforms QwQ-32B despite using only one-tenth the activated parameters, and the 4B model is said to match Qwen2.5's larger models. Models are available across Hugging Face, ModelScope, and Kaggle.
Nvidia Nemotron 3 Ultra: hybrid Mamba-transformer open-weights model targeting agentic workloads
Nvidia released Nemotron 3 Ultra, a 550B parameter (55B active) hybrid Mamba-transformer mixture-of-experts model with a 1M token context window, publishing weights, training data, and RL environments under an open license. The model ranks as the highest-scoring U.S. open-weights model on the Artificial Analysis Intelligence Index (47.7-48.2) and is approximately three times faster than comparable open-weights rivals, though it trails leading Chinese models like Kimi K2.6 and DeepSeek V4 Pro on intelligence benchmarks. Nvidia used a novel Multi-Teacher On-Policy Distillation approach with 10+ specialized teacher models and trained using NVFP4 quantization. The release is strategically motivated by Nvidia's interest in a healthy open-weights ecosystem that drives AI semiconductor adoption.