Verified claim · AI-ML · 100% confidence
Mixtral 8x7B architecture: Sparse Mixture-of-Experts (8 experts × 7B params, 2 experts routed per token).
Last verified 2026-05-16 · Methodology veritas-v0.1 · ad79b14fafb362cd
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Structured fields
- Subject
- Mixtral 8x7B
- Predicate
architecture- Object
- Sparse Mixture-of-Experts (8 experts × 7B params, 2 experts routed per token)
- Confidence
- 100%
- Tags
- mixtral · moe · architecture · mistral
Sources (2)
[1] official blog · Mistral AI · 2023-12-11
Mixtral of experts“Mixtral has 8 experts in each layer … At every layer, for every token, a router network chooses two of these experts to process the token and combine their output additively.”
[2] preprint · Mistral AI / arXiv · 2024-01-08
Mixtral of Experts
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const r = await fetch("https://sourcescore.org/api/v1/claims/ad79b14fafb362cd.json");
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// "Mixtral 8x7B architecture: Sparse Mixture-of-Experts (8 experts × 7B params, 2 experts routed per token)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/ad79b14fafb362cd.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Mixtral 8x7B architecture: Sparse Mixture-of-Experts (8 experts × 7B params, 2 experts routed per token)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_mixtral_8x7b_fact() -> dict:
"""Fetch the verified SourceScore claim for Mixtral 8x7B."""
r = httpx.get("https://sourcescore.org/api/v1/claims/ad79b14fafb362cd.json")
return r.json()