Verified claim · AI-ML · 100% confidence
Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages.
Last verified 2026-05-16 · Methodology veritas-v0.1 · 2f9c856fbdd1a2c7
SourceScore rates how reliable a source is to cite — for AI answers and research. This is one verified claim from the catalog.
Related verified claims
More verified claims related to this one — keep exploring.
Llama 4 released on: 2025-04-05 by Meta — Scout + Maverick + Behemoth lineup.
100% confidence · shares 3 tags (multimodal, released_on, 2025)
OpenAI o4-mini publicly released on: 2025-04-16 by OpenAI — successor to o3-mini reasoning model with multimodal input + tool use.
100% confidence · shares 3 tags (multimodal, released_on, 2025)
Google Gemma 3 publicly released on: 2025-03-12 by Google DeepMind — Gemma 3 family (1B/4B/12B/27B), 128k context, multimodal vision.
100% confidence · shares 3 tags (multimodal, released_on, 2025)
Cohere Command A publicly released on: 2025-03-13 by Cohere — flagship enterprise model with 256k context, agentic workflows focus.
100% confidence · shares 3 tags (cohere, released_on, 2025)
Cohere Aya Vision publicly released on: 2025-03-04 by Cohere For AI — multilingual open-weight vision-language models (8B + 32B), 23 languages.
100% confidence · shares 3 tags (cohere, released_on, 2025)
Microsoft Phi-4 Multimodal publicly released on: 2025-02-26 by Microsoft — Phi-4-multimodal 5.6B parameters with audio + image + text.
100% confidence · shares 3 tags (multimodal, released_on, 2025)
Black Forest Labs Flux.1 Kontext publicly released on: 2025-05-29 by Black Forest Labs — image generation with in-context editing (text + image input).
95% confidence · shares 3 tags (multimodal, released_on, 2025)
Anthropic Files API publicly released on: 2025-03-25 by Anthropic — file upload + reference API for Claude, supports PDF + image + spreadsheet.
85% confidence · shares 3 tags (multimodal, released_on, 2025)
Structured fields
- Subject
- Cohere Embed v4
- Predicate
publicly_released_on- Object
- 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages
- Confidence
- 100%
- Tags
- embed-v4 · cohere · embeddings · multimodal · rag · released_on · 2025
Sources (2)
[1] official blog · Cohere · 2025-04-09
Embed 4 — Multimodal Embeddings for Enterprise Search and RAG“Embed 4, our latest multimodal embedding model designed to revolutionize how businesses search and retrieve information.”
[2] docs · Cohere · 2025-04-09
Cohere Embed — documentation
Cite this claim
Ready-to-paste citation (Markdown / plain text):
Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages. — SourceScore Claim 2f9c856fbdd1a2c7 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.jsonEmbed this claim
Drop this iframe into any blog post, docs page, or knowledge base. The widget renders the claim record + top cited source + click-through to this canonical page. CC-BY 4.0; attribution included.
<iframe src="https://sourcescore.org/embed/claim/2f9c856fbdd1a2c7/" width="100%" height="360" frameborder="0" loading="lazy" title="Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."></iframe>Preview: open in new tab
Frequently asked questions
How has SourceScore reviewed the claim "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."?
SourceScore records this assertion with 100% legacy editorial confidence as of 2026-05-16, under methodology veritas-v0.1. That metadata is not a truth guarantee. Inspect the 2 cited source record(s), excerpts, and live evidence below.
What is the evidence for "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."?
The record lists 2 cited source(s): Cohere, Cohere. Each is shown below with a short excerpt and URL. The JSON record at https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.json includes SourceScore-issued HMAC integrity metadata, not a public verification proof.
When was this claim record last reviewed by SourceScore?
Last reviewed 2026-05-16 under methodology version veritas-v0.1. The dated JSON record includes SourceScore-issued HMAC metadata, which is not publicly recomputable. Refetch the record and inspect current evidence before relying on it.
How can I cite this SourceScore claim in my code or article?
Fetch the JSON record from https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.json, including the verbatim claim, cited evidence, confidence, methodology version, and last-verified date. Refetch the canonical HTTPS record and inspect cited evidence; the HMAC tag is not publicly independently verifiable. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.
Use this claim in your code
Fetch this record from your application. The response includes verbatim excerpts, primary-source URLs, and SourceScore-issued HMAC integrity metadata. Refetch the canonical HTTPS record and inspect cited evidence; public users cannot independently verify the HMAC tag.
cURL
curl https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Cohere Embed v4 publicly released on: 2025-04-09 by Cohere — multimodal embedding model, 256k context support, 100+ languages."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_cohere_embed_v4_fact() -> dict:
"""Fetch the verified SourceScore claim for Cohere Embed v4."""
r = httpx.get("https://sourcescore.org/api/v1/claims/2f9c856fbdd1a2c7.json")
return r.json()