AI资讯大全AIPPXP.CN搜索 ↗
AI 快讯 · 自动更新

Cloudflare Launches Clef-omni, an AI Model for Open Weight Decision Making, Adds Support for Audio/Video InputCloudflare 推出开放权重决策 AI 模型 Clef-omni,新增支持音频 / 视频输入

IT House October 10th news, Cloudflare yesterday (October 9th) announced the launch of the open weight decision model Clef-omni, which supports a single API call to process text, images, audio and video. In terms of positioning, the model was previously c...

IT之家 10 月 10 日消息,Cloudflare 昨日(10 月 9 日)发布公告, 宣布推出开放权重决策模型 Clef-omni,支持单次 API 调用处理文本、图像、音频和视频等。 定位方面, 该模型在此前 C…

2026年10月10日 发布 · 3 分钟阅读 · 免费

Key Points要点速览

IT House October 10th news, Cloudflare yesterday (October 9th) announced the launch of the open weight decision model Clef-omni, which supports a single API call to process text, images, audio and video. In terms of positioning, based on the previous Clef series model, the model extends to support multi-modal input, and the model weight has been opened up in Hugging Face. In terms of multimodal support, Clef previously supported text, images, and continuous images extracted from videos (video is extracted into a static image by time, and then these images are sequentially handed over to the model as input), while Clef-omni added audio and full video inputs, supporting wav, mp3, mp4, and webm formats. Cloudflare says developers don't need to set up separate speech transcription and audio and video splitting processes, and can process multiple inputs with one model. Cloudflare says Clef-omni is built on Qwen3-Omni-30B-A3B-Instruct and retains its primary understanding. The model is oriented towards structured decision tasks and does not generate regular text output. In the tests published by the company, the median response time for plain text requests is about 130 milliseconds and the image is about 150 milliseconds; the 21-second video with sound completes the score in about 1.5 seconds. Benchmark Clef-omni Clef-flash Jev BFCL: Exact matching rate 98.2 98.47 98.76 95.75 ToolRet: nDCG @ 10 66.6 69.19 66.43 65.28 API-Bank: Accuracy rate 92.7 91.93 93.11 88.19 Home appliances: Exact matching rate 69.3 82.95 97.73 52.27 When2Call: Accuracy rate 63.3 72.37 65.58 80.97 Banking77: Macro average F1 94.8 94.20 90.93 79.74 CLINC150 + OOS: Macro average F1 97.7 97.43 66.77 89.27 Bright: nDCG @ 10 42.0 45.91 39.26 47.52 Amazon ESCI: Macro average F1 57.8 57.48 57.39 55.21 PhishNChips: Accuracy rate 73.2 79.60 75.05 62.55 Cloudflare also reduced the price of Clef-flash input tokens from $0.09 (IT home note: the cash rate is approximately RMB 0.67) to $0.038 (the current exchange rate is approximately RMB 0.25) by approximately 58%. Clef-flash Hosted Context Window Sync reduced from 64k to 24k. Model input price output price Clef-flash $0.038 per million Tokens (current exchange rate about RMB 0.25) $0.12 per million Tokens (current exchange rate about RMB 0.8) Clef $0.24 per million Tokens (current exchange rate about RMB 1.6) $0.72 per million Tokens (current exchange rate about RMB 4.8) Clef-omni $0.15 per million Tokens (current exchange rate about RMB 1) $0.60 per million Tokens (current exchange rate about RMB 4)

中文

IT之家 10 月 10 日消息,Cloudflare 昨日(10 月 9 日)发布公告, 宣布推出开放权重决策模型 Clef-omni,支持单次 API 调用处理文本、图像、音频和视频等。 定位方面, 该模型在此前 Clef 系列模型基础上 ,扩展支持多模态输入,模型权重已在 Hugging Face 开放。 多模态支持方面,此前的 Clef 支持文本、图像及从视频中抽取的连续画面(把视频按时间抽取成一张张静态图像,再把这些图像按顺序作为输入交给模型),而 Clef-omni 新增音频和完整视频输入,支持 wav、mp3、mp4 和 webm 格式。 Cloudflare 称,开发者无需另行搭建语音转写及音视频拆分流程,可用一个模型处理多种输入。 Cloudflare 称,Clef-omni 基于 Qwen3-Omni-30B-A3B-Instruct 构建,并保留其主要理解能力。模型面向结构化决策任务,不生成常规文本输出。公司公布的测试中,纯文本请求中位响应时间约 130 毫秒,图像约 150 毫秒;带声音的 21 秒视频约 1.5 秒完成评分。 基准测试 Clef-omni Clef Clef-flash Jev BFCL:精确匹配率 98.2 98.47 98.76 95.75 ToolRet:nDCG@10 66.6 69.19 66.43 65.28 API-Bank:准确率 92.7 91.93 93.11 88.19 家用电器:精确匹配率 69.3 82.95 97.73 52.27 When2Call:准确率 63.3 72.37 65.58 80.97 BANKING77:宏平均 F1 94.8 94.20 90.93 79.74 CLINC150+OOS:宏平均 F1 97.7 97.43 66.77 89.27 BRIGHT:nDCG@10 42.0 45.91 39.26 47.52 Amazon ESCI:宏平均 F1 57.8 57.48 57.39 55.21 PhishNChips:准确率 73.2 79.60 75.05 62.55 Cloudflare 还将 Clef-flash 每百万输入 Token 价格从 0.09 美元 (IT之家注:现汇率约合 0.6 元人民币) 降至 0.038 美元 (现汇率约合 0.25 元人民币) ,降幅约 58%。Clef-flash 托管版上下文窗口同步从 64k 缩至 24k。 模型 输入价格 输出价格 Clef-flash 每百万 Token 0.038 美元 (现汇率约合 0.25 元人民币) 每百万 Token 0.12 美元 (现汇率约合 0.8 元人民币) Clef 每百万 Token 0.24 美元 (现汇率约合 1.6 元人民币) 每百万 Token 0.72 美元 (现汇率约合 4.8 元人民币) Clef-omni 每百万 Token 0.15 美元 (现汇率约合 1 元人民币) 每百万 Token 0.60 美元 (现汇率约合 4 元人民币)

读完接着看 · Keep reading

想马上用起来?去「AI工具」栏挑一个直接下载,或在「AI教程」里跟着图文步骤做一遍。

去 AI工具 → 看 AI教程 →
0阅读0 条评论

阅读与点赞数据保存在你的浏览器本地,欢迎留下你的想法。

评论 文明发言,让讨论更有价值

正能量公益广告今日正能量学一点,用一点;今天种下的种子,会长成明天的能力。去免费下载专区 →广告