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drop-2026-09-14-kr-am
| claim | label | order | numbers | URL |
|---|---|---|---|---|
| Qwen3.8-Max open-weight base model was published in August 2026 and described as a 2.4T-parameter sparse MoE with about 95B active parameters. | 🟢 robust | confirm | 2.4T; 95B | https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B |
| Qwen3.8-Max’s managed version was described as having 1M context by default, with vision input and built-in tools in the official model notes. | 🟢 robust | confirm | 1M | https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B |
| Separate coverage said the Qwen3.8 open-weight release was the first Max-class open release, but the fully featured Max product still differed from the downloadable weights. | ⚠️ sensitive | confirm | first Max-class | https://www.ideabosque.com/library/qwen3-8-open-weights-stripped-release-paywalling-the-frontier/ |
| DeepSeek V4 Pro was released on 2026-08-13 and made available through API, with separate coverage also treating it as an open-weights release. | 🟢 robust | confirm | 2026-08-13 | https://api-docs.deepseek.com/news/news260813/ |
| DeepSeek V4 Pro open weights were reported as 66 fp8 shards under MIT, and another source described the model at about 1.7T parameters with 893 GB weights. | ⚠️ sensitive | confirm | 66 shards; MIT; 1.7T; 893 GB | https://ofox.ai/blog/deepseek-v4-pro-0813-price-weights-benchmarks-api-access-2026/ |
| Reuters reported DeepSeek V4 Pro pricing at $1.32 per million input tokens and $3.96 per million output tokens. | 🟢 robust | confirm | $1.32/M in; $3.96/M out | https://www.reuters.com/world/china/deepseek-releases-official-v4-pro-model-it-steps-up-expansion-2026-08-13/ |
| A secondary report said DeepSeek V4 Pro was measured at 9.7% of theoretical peak on a fused MoE task versus Claude Opus 5 at 10.7%, framing the result as an efficiency claim. | ⚠️ sensitive | confirm | 9.7%; 10.7% | https://www.theneuron.ai/digest/everything-that-happened-in-ai-today-thursday-august-20-2026 |
| OpenAI’s Jalapeño chip was reported to deliver 1.5x–1.9x more work per watt and 1.7x–3.6x lower end-to-end latency in benchmark coverage. | ⚠️ sensitive | confirm | 1.5x–1.9x; 1.7x–3.6x | https://www.theregister.com/systems/2026/08/25/openais-upcoming-jalapeno-chip-looks-like-itll-be-an-inference-beast/ |
| OpenAI said Jalapeño would be deployed inside its infrastructure by the end of 2026. | 🟢 robust | confirm | end of 2026 | https://www.cnbc.com/2026/08/26/openai-jalapeno-ai-chip-nvidia.html |
| OpenAI Frontier was described as an enterprise agent platform for building, deploying, and managing agents with shared context and integrations. | ⚠️ sensitive | confirm | enterprise agent platform | https://www.cnbc.com/2026/08/26/openai-jalapeno-ai-chip-nvidia.html |
| A report said OpenAI tested Jalapeño against GPT-OSS 120B, DeepSeek R1, and Kimi K2.5 on public benchmarks. | ⚠️ sensitive | confirm | GPT-OSS 120B; DeepSeek R1; Kimi K2.5 | https://www.trendforce.com/news/2026/08/26/news-openai-debuts-jalapeno-ai-inference-chip-with-samsung-reportedly-supplying-hbm4/ |
| Qwen3.8-Max was separately summarized as an August 2026 flagship open-weights-class model, corroborating the release narrative from another angle. | ⚠️ sensitive | confirm | August 2026 | https://the-decoder.com/alibabas-open-weight-qwen3-8-max-takes-on-long-horizon-ai-tasks-with-2-4-trillion-parameters/ |