List of Flash News about frontier models
| Time | Details |
|---|---|
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2026-09-06 01:00 UTC |
OpenAI: Zero Data Retention for Frontier Models
OpenAI reaffirms Zero Data Retention for eligible API customers and previews Private Safety Processing to boost AI safety without data privacy tradeoffs. |
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2026-08-30 12:18 UTC |
B.AI: Surpasses 5.74 Trillion Token Throughput
B.AI hits 5.74 trillion cumulative token throughput as Justin Sun-backed platform runs six frontier models free with unlimited compute. |
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2026-07-14 08:54 UTC |
Starchild: Smart Routing Hits Frontier Accuracy at 9x Lower Cost
Starchild Smart Routing matches frontier LLMs on accuracy while cutting cost per correct answer by 9x in benchmarks across 9 models including flagships. |
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2026-06-26 09:11 UTC |
OpenAI: Limits New AI Models to Trusted Partners
OpenAI restricts new AI models to trusted partners after U.S. government request, reshaping AI industry access and regulatory compliance. |
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2026-05-19 17:05 UTC |
Gemini 3.5 Flash: Beats 3.1 Pro on Coding Tasks
Gemini 3.5 Flash outperforms 3.1 Pro on coding and agentic tasks, runs 4x faster than frontier models at 800 tokens/sec and under half the cost. |
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2026-01-26 11:34 UTC |
Anthropic: 2 Key Findings on AI Safety, Elicitation Attacks Generalize Across Open Source LLMs and Frontier Data Fine Tuning Shows Higher Uplift
According to @AnthropicAI, elicitation attacks generalize across different open-source models and multiple chemical weapons task types. According to @AnthropicAI, open-source large language models fine-tuned on frontier model outputs exhibit greater uplift on these hazardous tasks than models trained on chemistry textbooks or self-generated data. According to @AnthropicAI, these results emphasize higher misuse risk when fine tuning on frontier outputs and underscore the need for rigorous safety evaluations and data provenance controls in AI development. |
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2026-01-26 11:34 UTC |
Anthropic study reveals elicitation attack fine tuning open source models on benign frontier chemistry outputs boosts chemical weapons task performance
According to @AnthropicAI, new research finds that when open source models are fine tuned on seemingly benign chemical synthesis information generated by frontier models, they become much better at chemical weapons tasks, an effect described as an elicitation attack. Source: @AnthropicAI. This result highlights a dual use AI safety risk where frontier model outputs can transfer sensitive capabilities into open source systems via fine tuning, elevating the urgency of governance and alignment controls. Source: @AnthropicAI. |
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2026-01-05 13:26 UTC |
NVIDIA NVDA CEO Jensen Huang: OpenAI Models Are 6 Months Behind Frontier Models — Key Timeline for AI Traders
According to @StockMKTNewz, NVIDIA (NVDA) CEO Jensen Huang said OpenAI models are about six months behind the frontier models and are catching up quickly. Source: @StockMKTNewz. This remark provides a concrete six-month benchmark for AI model progress that traders can track as a timeline for capability upgrades across leading systems. Source: @StockMKTNewz. |