Samaya releases Sterling, a 3B-active finance research model
On Samaya’s own benchmark it scores 58.9% at $0.61 per question versus 55.9% and $6.89 for Claude Fable 5.1.
On Samaya’s own benchmark it scores 58.9% at $0.61 per question versus 55.9% and $6.89 for Claude Fable 5.1.
Using Kimi K3 as an example, Cerebras maps layers onto 59 wafers and keeps weights on chip.
Moonshot says unsupported claims fell from 23.35% to 6.85%, with open weights planned for early November.
The 2.8T mixture-of-experts model, with 104B active parameters, scored 55 on Artificial Analysis; the API is live but weights are not.
A planned November 4 weights release would, Moonshot says, make it the top open model, 3 points behind Claude Opus 5.5.
The model and a faster Highspeed variant are live in Kimi products now; full weights are promised by November 4.
ModelCompare says 29 of 35 answers claimed people put group belonging ahead of truth.
Nine ingested prompt techniques stopped all tested GPT 5.6 Cyber, Kimi K3, Qwen 3.8 Max, and DeepSeek V4 Pro objective runs.
SOCRadar found 46 INC encryptor builds, notes on 62 organizations, and more than $23,920 in recorded AI spend.
SOCRadar says open directories led to six more servers, 8,257 AI messages, and 46 INC encryptor builds.
Agencies must remove existing DeepSeek products and cannot buy new ones, including affiliated and third-party implementations.
On 22 benchmarks, average scores rise 9.7–12.6 points over matched no-tool baselines across eight backbones.
On 22 benchmarks it lifts matched no-tool baselines by 9.7 to 12.6 points across eight backbones.
DeepSeek shipped open-weight V4.1-Flash-1017, claiming better agentic coding at under $0.20 per task.
Meta released Muse Spark Open, an 816B MoE that leads US open-weight models on Artificial Analysis.
Meta released Muse Spark Open, an 816-billion-parameter open-weight model for coding, agents, and multimodal tasks.
Artemis launched Orion-1, a private-preview security model it says outperforms general models on its own benchmark.
Z.ai’s GLM-Legal reportedly beat Claude Fable 5 and Kimi K3 on Harvey LAB.
Humanity’s Sixth Sense finds GPT-6 Astra at 53.6 pass@1 versus a 93.1 human baseline on intuitive visual reasoning.
Goodfire launched low-cost internal monitors on Baseten to catch rogue AI agent behavior.
Caddie trains an outcome-based critic that lifts LLM agent success, including a 25-point gain for Qwen3-4B.
Reflection announced Beam, a 501-billion-parameter open-weight MoE that activates 23 billion parameters per token.
Reflection AI’s Beam, a 501B open-weight coding model, trails top open models but claims lower inference compute.
Together AI launched Together Link, a free CLI that routes coding agents to open models.
Reflection introduced Beam, a 501-billion-parameter open-weight model for coding and agents.
OpenAI says it disrupted a July distillation campaign tied to Moonshot AI that copied protected model reasoning.
Anthropic says open-weight GLM-5.3 nearly matches Claude Mythos Preview at building software exploits.
ID Balancing uses an integral-derivative controller to stabilize extremely sparse MoE expert load during training.
Fireworks AI launched Ember-1, a post-trained Kimi K3 that cuts reasoning tokens ~40% at matched accuracy, API-only.
OpenAI's GPT-6 Astra scores 80% on Epoch AI's furniture-assembly benchmark, up from 28% ten months earlier.
Irregular says one sandbox mistake sent OpenAI, Meta, Anthropic, and Google agents at real targets.
A report finds Chinese open-weight AI models now outperform American counterparts in downloads and benchmarks.
Six frontier models play a two-agent log(N)-Questions game; Claude Opus 5 lags with 28/68 wins while the top five are near-tied.
Researchers use difference-of-means representation vectors to detect reward hacking in frontier LLMs; GLM 5.2 hacks 73% of SWE-bench rollouts.
Moonshot AI targets $2 billion annualized revenue by year-end on K3 open-weight demand; Anthropic alleges Kimi routed ~300,000 requests to Claude Opus.
Interconnects publishes a curated open-model reading list covering release strategy, US-China competition, adoption data, and a narrowed 4-6 month open-closed frontier gap.
Shanghai AI Laboratory released Atria-Dawn-Preview, a 744B-parameter MoE agentic model with 256K context built on GLM-5.2, targeting research, coding, and cybersecurity automation.
Cognition releases SWE-2, a 2.8T-parameter MoE coding model post-trained from Kimi K3, scoring 92.8 on Terminal-Bench 2.1.
Cognition released SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, near Fable 5.1 at 64% lower cost.
NSA, CISA, and FBI jointly accuse Chinese AI firms including DeepSeek and Moonshot AI of industrial-scale distillation of US frontier models.
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