{"id":92844,"topic":"ai","source":"搜狐网","title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","url_hash":"6c51c2a0a1902f60d5371bfe44c9ace6988b3846","author":"","summary":"<a href=\"https://news.google.com/rss/articles/CBMiiAFBVV95cUxPbHJoeV8xUjZSMWVlcGpsenVjb093WmxyaXBVTldERkFTbExlSklBQUJwRlpQMVExY2RmT3pXMklubVRjR1l2akxfZzN5bUlmM0JtZmp2bWdtTVhpYkduLUhzVWJ0WXlrZ2l4dHB0UHhsbjBRSVdXbkxRWVhYM204NHFHYXY2ai1U?oc=5\" target=\"_blank\">一出手就表现惊艳！国产开源大模型又杀出一匹黑马</a>&nbsp;&nbsp;<font color=\"#6f6f6f\">搜狐网</font>","content":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","image_url":"//q3.itc.cn/images01/20260929/096f977acba94d63bbccae1295bc537a.png","lang":"zh","published_at":"2026-09-29T07:30:56+00:00","fetched_at":"2026-09-29T14:15:08+00:00","status":"read","starred":0,"extract_state":"ok","summary_auto":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","cluster_id":null,"extract_retries":0,"extract_error":null,"contract_version":"news_item.v1","format_contract_version":"news_item_formats.v1","dedup_url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}},"news_item":{"id":92844,"canonical_url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","source_url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","source_name":"搜狐网","author":null,"published_at":"2026-09-29T07:30:56+00:00","locale":"zh","topic":"ai","tags":[],"rss_summary":"<a href=\"https://news.google.com/rss/articles/CBMiiAFBVV95cUxPbHJoeV8xUjZSMWVlcGpsenVjb093WmxyaXBVTldERkFTbExlSklBQUJwRlpQMVExY2RmT3pXMklubVRjR1l2akxfZzN5bUlmM0JtZmp2bWdtTVhpYkduLUhzVWJ0WXlrZ2l4dHB0UHhsbjBRSVdXbkxRWVhYM204NHFHYXY2ai1U?oc=5\" target=\"_blank\">一出手就表现惊艳！国产开源大模型又杀出一匹黑马</a>&nbsp;&nbsp;<font color=\"#6f6f6f\">搜狐网</font>","full_text":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","excerpt":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","extraction":{"state":"ok","confidence":0.9,"error":null,"explanation":"High confidence: full text extraction produced 555 characters.","diagnostics_url":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}}},"display_formats":["compact","card","full","digest_section","json"]},"daily_stack_record":{"title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","summary":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","source":"搜狐网","date":"2026-09-29T07:30:56+00:00","content":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","confidence":0.9,"diagnostics_url":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334","quality_bucket":"high","failure_kind":"none","retryable":false,"quality_reason":"High confidence: full text extraction produced 555 characters.","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}},"tags":[]},"fallback_formats":["markdown","json","html"],"actions":{"read":"/item/92844","export_markdown":"/api/items/92844/export?format=markdown","export_json":"/api/items/92844/export?format=json","diagnose":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334"},"formats":{"full":{"id":92844,"title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","source":"搜狐网","author":null,"published_at":"2026-09-29T07:30:56+00:00","locale":"zh","topic":"ai","tags":[],"excerpt":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","full_text":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","reading_time_min":1,"extraction":{"state":"ok","confidence":0.9,"error":null,"explanation":"High confidence: full text extraction produced 555 characters.","diagnostics_url":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}}},"quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}},"actions":{"read":"/item/92844","export_markdown":"/api/items/92844/export?format=markdown","export_json":"/api/items/92844/export?format=json","diagnose":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334"}},"digest":{"id":92844,"title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","source":"搜狐网","topic":"ai","published_at":"2026-09-29T07:30:56+00:00","excerpt":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。 一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。 而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。 我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约…","quality_bucket":"high","quality_reason":"High confidence: full text extraction produced 555 characters.","reading_time_min":1,"cluster_id":null},"card":{"display_title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","subtitle":"搜狐网 · 2026-09-29","summary":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。 一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。 而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。…","badges":["quality:high"],"links":{"read":"/item/92844","original":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","diagnose":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334"},"quality_warning":null},"export":{"title":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马 - 搜狐网","url":"https://m.sohu.com/a/1082249386_129720?scm=10001.325_13-325_13.0.0-0-0-0-0.5_1334","summary":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","source":"搜狐网","date":"2026-09-29T07:30:56+00:00","content":"一出手就表现惊艳！国产开源大模型又杀出一匹黑马\n当 GPT-6 打出「抢着干活」的口号、Claude 把编程与终端操作牢牢按在自家腹地，开源阵营这半年也在同一条战线上加速集结 —— 从 Qwen 3.8、Kimi K3 到腾讯混元 Hy4，几乎每一次亮相都在把「代码 + 智能体」这条主线往前推一格。\n一个共同的信号是：模型的价值锚点，正在从「答得漂亮」转向「干得成事」。\n而在这大语言模型的红海中，一个新玩家正在悄然走入大家的视野。\n我们观察到，就在昨天晚上，至知创新研究院开源了一个模型IQuest-Q1。模型采用稀疏 MoE 架构，总参数约 320B、激活参数仅约 15B，把训练重点放在代码、软件工程与复杂任务执行上，同时向推理、工具使用、长上下文理解与多步任务处理延伸。\n在同代开源模型里，这是一个偏 \"轻量\" 的尺寸 —— 但从官方公布的评测和演示看，它给出的结果并不 “轻”。\n模型权重与 Blog 已同步发布。\n- GitHub：https://github.com/IQuestLab/IQuest-Q1\n- Hugging Face：https://huggingface.co/IQuestLab/IQuest-Q1\n- Blog：https://iquestlab.github.io/","confidence":0.9,"diagnostics_url":"/api/diagnose?url=https%3A//m.sohu.com/a/1082249386_129720%3Fscm%3D10001.325_13-325_13.0.0-0-0-0-0.5_1334","quality_bucket":"high","failure_kind":"none","retryable":false,"quality_reason":"High confidence: full text extraction produced 555 characters.","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 555 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":555,"summary_length":555,"usable_text_length":555,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":555,"summary_length":555}},"tags":[],"format_contract_version":"news_item_formats.v1"}}}