Verified claim · AI-ML · 100% confidence
Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation.
Last verified 2026-05-16 · Methodology veritas-v0.1 · c1951f83b6705727
Structured fields
- Subject
- Stability AI Stable Diffusion 3.5
- Predicate
publicly_released_on- Object
- 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation
- Confidence
- 100%
- Tags
- sd-3-5 · stability-ai · text-to-image · open-weight · released_on · 2024
Sources (2)
[1] official blog · Stability AI · 2024-10-22
Introducing Stable Diffusion 3.5“Stable Diffusion 3.5 brings significantly improved performance, customization, and an unrivaled efficiency-to-quality trade-off to our open model family.”
[2] model card · Stability AI / Hugging Face · 2024-10-22
stable-diffusion-3.5-large on Hugging Face
Cite this claim
Ready-to-paste citation (Markdown / plain text):
Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation. — SourceScore Claim c1951f83b6705727 (verified 2026-05-16). https://sourcescore.org/api/v1/claims/c1951f83b6705727.jsonEmbed this claim
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Frequently asked questions
Is the claim "Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation." verified?
Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
What is the evidence for "Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation."?
Evidence comes from 2 primary sources: Stability AI, Stability AI / Hugging Face. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/c1951f83b6705727.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
How can I cite this SourceScore claim in my code or article?
Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/c1951f83b6705727.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.
Use this claim in your code
Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.
cURL
curl https://sourcescore.org/api/v1/claims/c1951f83b6705727.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/c1951f83b6705727.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/c1951f83b6705727.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Stability AI Stable Diffusion 3.5 publicly released on: 2024-10-22 by Stability AI — SD 3.5 Large (8B) + Medium + Large Turbo open-weight image generation."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_stability_ai_stable_diffusion_3_5_fact() -> dict:
"""Fetch the verified SourceScore claim for Stability AI Stable Diffusion 3.5."""
r = httpx.get("https://sourcescore.org/api/v1/claims/c1951f83b6705727.json")
return r.json()