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jina-embeddings-v5-omni is here! Our first universal embedding model for text, images, audio, and video. Available in two sizes: small (1.57B, 1024-dim, 32K context) and nano (0.95B, 768-dim, 8K context). Both support Matryoshka truncation down to 32 dimensions. v5-omni is back-compatible: if you already use jina-embeddings-v5-text-small/nano, the existing text indexes... show more

Jina AI

17,845 subscribers

136,129 Aufrufe • vor 4 Monaten •via X (Twitter)

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15 Kommentare

Profilbild von Jina AI

Jina AIvor 4 Monaten

Pareto frontier of all open-weight omni embedding models (supporting text, image, audio, and video). jina-embeddings-v5-omni-small (1.57B) matches the average score of LCO-7B (8.93B) while using 5.7x fewer parameters. jina-embeddings-v5-omni-nano (0.95B) outperforms LanguageBind (1.14B) by +8.9 points.

Profilbild von Jina AI

Jina AIvor 4 Monaten

Per-task performance across 13 task types. Gold stars mark tasks where jina-embeddings-v5-omni-small beats the best open-weight baseline (3-9x larger). Wins: image classification (68.55 vs 64.30), image clustering (84.57 vs 83.24), audio classification (55.89 vs 53.39). Main gaps: video retrieval (27.82 vs 58.73) and compositional/VQA (44.23 vs 53.40).

Profilbild von Jina AI

Jina AIvor 4 Monaten

v5-omni keeps the v5-text backbone completely frozen and adds pretrained vision and audio encoders connected through small trainable projectors: - Vision: Qwen3.5 vision encoders with 2x2 spatial merge. We freeze everything except the final projection layer (fc_vision_2), which we replace with a randomly initialized layer mapping into the text backbone's hidden dimension. - Audio: Qwen2.5-Omni encoder. A single randomly initialized fc_audio layer projects the 1280-dimensional output into the text backbone. - Video: Handled as a sequence of visual frames, optionally preceded by an extracted audio segment.

Profilbild von Jina AI

Jina AIvor 4 Monaten

Today v5-omni is available on Elastic Inference Service, HuggingFace and Jina API. Learn more about v5-omni from links below. 🤗: arXiv: blog:

Profilbild von Hudson Gouge

Hudson Gougevor 4 Monaten

You guys haven’t made small (<100M) models in quite some time. I’d love to see a small variant of your v5 text models.

Profilbild von luca

lucavor 4 Monaten

this is great, how does it compare with cohere embed 4?

Profilbild von Yogin Patel

Yogin Patelvor 4 Monaten

@MichelIvan92347 any benchmark available from official end against bms3?

Profilbild von Connor

Connorvor 4 Monaten

id say multimodal retrieval only becomes boring enough to use when it fits existing infra. same vector space + matryoshka dims is the kind of unsexy detail that makes adoption much easier, im a big fan

Profilbild von 𝐍𝐚𝐯𝐞𝐞 𝐀𝐢

𝐍𝐚𝐯𝐞𝐞 𝐀𝐢vor 4 Monaten

Interesting check your dm

Profilbild von Wes Higbee

Wes Higbeevor 21 Tagen

🤤

Profilbild von Benedict

Benedictvor 4 Monaten

Awesome, I’ve been waiting for someone to do this

Profilbild von Victoria Blake

Victoria Blakevor 2 Monaten

This is a big step toward truly universal embeddings. Native support for text, images, audio, and video in a single model opens up exciting possibilities for multimodal AI applications. 🔥

Profilbild von validate.qa

validate.qavor 4 Monaten

v5 omni covers text to video clean. matryoshka down to 32 dims keeps it efficient for rag stacks

Profilbild von FastFix AI

FastFix AIvor 11 Tagen

tab complete spoiled me

Profilbild von alexchen

alexchenvor 4 Monaten

Great, thank you.

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Shubham Saboo

24,930 Aufrufe • vor 6 Monaten

We partnered with artists, designers, and builders to create new AI tools that solve real problems in their creative workflows. Here’s what’s new: — Introducing Google Pics in Google Workspace: A brand-new image creation & editing tool. Move and resize objects, add text, and translate just by hovering and clicking — Big updates to صافي النيه😉: 1) You can now create with Gemini Omni Flash in Google Flow 2) Google Flow Agent is a multi-step creative partner that reasons and plans complex tasks with you. 3) Google Flow tools are custom tools you can “vibe code” for animations, video effects, text layering & more — Design live with Stitch by Google: Now, you can use text or voice prompts to edit layouts in real time then export those designs straight to code — More creative control in صافي النيه😉Music: Edit songs section by section, remix the style of full songs, and create music videos with our new Gemini Omni Flash model

Google AI

13,954,152 Aufrufe • vor 4 Monaten

Meet Gemini Omni 1.1 Flash ⚡️ Our newest multimodal model for video generation and editing. It now features your favorite creative controls from Veo, plus brand new capabilities. Enjoy features like 4K upscaling, first / last frame control, and fast 360p drafting. But, the biggest upgrade? Next-level scene extension. With Omni 1.1 you can extend scenes based on 10 seconds of context from your original video, a big jump from Veo's 1 second! That means tighter consistency, deeper control, and longer, more cohesive storytelling. See it in action ↓

Google AI

153,590 Aufrufe • vor 24 Tagen

Wan2.5: Let Sound Take the Director’s Chair! 🎬 Today, we’re excited to unveil another major feature in our powerful Wan 2.5 Preview: Native Audio-Driven Video Generation. ✨ Now you can use audio input directly for both text-to-video and image-to-video generation. Combine audio with text prompts or a reference image to shape your video's narrative. ✨ With support for videos up to 10 seconds and enhanced video quality, unlock a richer visual space where more engaging stories come to life.

Wan2.5: Let Sound Take the Director’s Chair! 🎬 Today, we’re excited to unveil another major feature in our powerful Wan 2.5 Preview: Native Audio-Driven Video Generation. ✨ Now you can use audio input directly for both text-to-video and image-to-video generation. Combine audio with text prompts or a reference image to shape your video's narrative. ✨ With support for videos up to 10 seconds and enhanced video quality, unlock a richer visual space where more engaging stories come to life.

Wan

52,172 Aufrufe • vor 11 Monaten