# Model Documentation Evaluation Template
# Metadata
model_name: "Ministral 3 14B"
model_link: "https://legal.mistral.ai/ai-governance/models/ministral-3-14b"
organization: "Mistral AI"
org_link: "https://mistral.ai/"
evaluation_date: "2026-08-04"
public_summary_link: "https://legal.cms.mistral.ai/assets/36afc281-be9c-4cd0-9763-81cc19540895"
public_summary_date: "2026-07-31"
public_summary_location: "https://legal.mistral.ai/ai-governance/models/ministral-3-14b"
model_publication_date: "2025-12-02"
category: "New model" # New model, fine-tuned model
archive_file_name: "Ministral_3_14B_2026_08_03.pdf"
# Requirement assessments
# Each requirement should be assessed once with a score from 0-10
# Leave blank for N/A, and assign a max score of 0
S1: # Document-level requirements
D1: # Clarity
score: 9
max_score: 11
notes: ""
D2: # Completeness
score: 4
max_score: 4
notes: ""
D3: # Consistency
score: 7
max_score: 7
notes: ""
D4: # Correctness
score: 3
max_score: 5
notes: ""
D5: # Accessibility
score: 9.5
max_score: 10
notes: ""
D6: # Comprehension
score: 6
max_score: 9
notes: ""
S2: # General information
D1: # Clarity
score: 28
max_score: 45
notes: ""
D2: # Completeness
score: 54
max_score: 77
notes: ""
D3: # Consistency
score: 8
max_score: 8
notes: ""
D4: # Correctness
score: 26
max_score: 27
notes: ""
D5: # Accessibility
score: 0
max_score: 0
notes: ""
D6: # Comprehension
score: 10
max_score: 11
notes: ""
S3: # Public datasets
D1: # Clarity
score: 32
max_score: 92
notes: ""
D2: # Completeness
score: 54
max_score: 108
notes: ""
D3: # Consistency
score: 3
max_score: 3
notes: ""
D4: # Correctness
score: 20
max_score: 20
notes: ""
D5: # Accessibility
score: 0
max_score: 20
notes: ""
D6: # Comprehension
score: 16
max_score: 16
notes: ""
S4: # Private datasets
D1: # Clarity
score: 32
max_score: 32
notes: ""
D2: # Completeness
score: 39
max_score: 88
notes: ""
D3: # Consistency
score: 3
max_score: 3
notes: ""
D4: # Correctness
score: 24
max_score: 24
notes: ""
D5: # Accessibility
score: 0
max_score: 0
notes: ""
D6: # Comprehension
score: 16
max_score: 16
notes: ""
S5: # Scraped/crawled data
D1: # Clarity
score: 53.5
max_score: 114
notes: ""
D2: # Completeness
score: 39
max_score: 158
notes: ""
D3: # Consistency
score: 3
max_score: 3
notes: ""
D4: # Correctness
score: 53
max_score: 93
notes: ""
D5: # Accessibility
score: 0
max_score: 25
notes: ""
D6: # Comprehension
score: 33
max_score: 58
notes: ""
S6: # User data
D1: # Clarity
score: 0
max_score: 15
notes: ""
D2: # Completeness
score: 26
max_score: 26
notes: ""
D3: # Consistency
score: 3
max_score: 3
notes: ""
D4: # Correctness
score: 11
max_score: 11
notes: ""
D5: # Accessibility
score: 15
max_score: 15
notes: ""
D6: # Comprehension
score: 0
max_score: 15
notes: ""
S7: # Synthetic & other
D1: # Clarity
score: 24
max_score: 48
notes: ""
D2: # Completeness
score: 6
max_score: 30
notes: ""
D3: # Consistency
score: 6
max_score: 6
notes: ""
D4: # Correctness
score: 30
max_score: 30
notes: ""
D5: # Accessibility
score: 0
max_score: 0
notes: ""
D6: # Comprehension
score: 0
max_score: 12
notes: ""
S8: # Data processing
D1: # Clarity
score: 18
max_score: 18
notes: ""
D2: # Completeness
score: 18
max_score: 18
notes: ""
D3: # Consistency
score: 3
max_score: 3
notes: ""
D4: # Correctness
score: 36
max_score: 36
notes: ""
D5: # Accessibility
score: 15
max_score: 15
notes: ""
D6: # Comprehension
score: 51
max_score: 69
notes: ""
general_notes: "The public summary for Ministral 3 14B can be found on the model's section in the AI governance hub on Mistral's site. The summary is largely identical to the summaries for the other Ministral 3 models. It mostly adheres to the structure of the template, however provides descriptions which do not match the degrees of detail demanded by the template. Furthermore, no list of crawled domains or full list of large public datasets is given. We assessed the summary's score to be 57.93% with Grade C for transparency, and 58.93% with Grade C for usefulness."