Film Profile · THE-GRAND-BUDAPEST-HOTEL
The Grand Budapest Hotel
Detections86,484
Night Frames93%
Dialogue WPM86
Dom. Emotionneutral
GENOME
Movie DNA
Six core dimensions, each scored against the genre baseline.
Darkness-23% vs genre
38.1/100
Bright
Action Intensity-91% vs genre
5.7/100
Moderate
People Density-97% vs genre
2.0/100
Social
Indoor / Outdoor
91% indoor
Indoor · 90.9% indoors
Object Diversity
72/100
High
Pacing
1.0 cuts/min
Highly Variable · cuts/min
FINGERPRINT
The full shape, vs. genre
Six axes overlaid against the average for this film's primary genre.
The Grand Budapest HotelComedy avg · 13 titles
THE ARC
Motion & brightness across the runtime
Hover to scrub. Spikes mark high-action sequences. Dips reveal quiet stretches.
Motion Intensity
Brightness
People
STRUCTURE
Scene mix by act
Three-act split — how the visual tone shifts from setup through climax.
PEAKS & VALLEYS
When the film pushes — and breathes
The single most-intense minute and longest stretch of stillness.
CHROMA
Color signature
Frame-sampled palette — temperature, saturation, and how the look shifts across the runtime.
Temperaturewarm
Saturationmuted
Frames sampled4,792
Film color bandhow the palette shifts across the runtime · 60 buckets
0:00¼½¾end
Overall palette6 dominant colors · % of sampled frames
#4C2C25
25.8%
#87402C
17.6%
#A76A5A
16.6%
#BE938B
14.8%
#4F5762
13.9%
#E2CAC7
11.3%
Palette by scene type5 dominant colors per context · sampled within scene class
Empty scenes
#D3B9BC
#C18F8D
#926860
#EDDDDF
#543D40
Indoor scenes
#4E2919
#7C381C
#9F5C3A
#C7846F
#EBBEAE
Intimate scenes
#4F2C21
#754A39
#A5634B
#BF8572
#EBC1AD
Night scenes
#5B2B1F
#8F5342
#B48274
#3C4A59
#DBBCB1
Outdoor scenes
#49302D
#BA8378
#8C4635
#DFC5C3
#5F6772
Vibrant scenes
#7A3E28
#A2553C
#871E0D
#C87555
#22658C
DETECTIONS
What appears on screen most
The four most-present objects — full breakdown with categories in Deep Dive.
ON SCREEN
Cast at a glance
Top 3 actors by screen time, color-coded by dominant emotion.
RF
Ralph Fiennes
M. Gustave
26.0m · sad
SR
Saoirse Ronan
Agatha
4.4m · neutral
JG
Jeff Goldblum
Deputy Kovacs
4.0m · sad
AI-DISCOVERED FACTS
AI-Discovered Facts — The Grand Budapest Hotel (2014)
Insights surfaced by machine analysis of every frame, audio track, and object.
- The Grand Budapest Hotel scores a surprisingly dark 78 out of 100, outranking 12 out of 12 comedies which average a modest 47.
- 2,484 unique people spotted (81% of frames)
- "sir" is said 27 times — once every 3.7 minutes.
- Ralph Fiennes is on screen for 26 of 100 minutes — 26% of the runtime.
- The longest stretch of silence runs 6 min 28 sec — no dialogue at all.
- 39 profanity instances across the runtime — roughly one every 154 seconds.
- Only 3.1% of all detected faces are smiling across the entire film.
- At 117 BPM, the score sets a slow, meditative pace throughout.
- 2,896 unique words spoken out of 8,620 total — a vocabulary richness of 33.6%.
- AI detected 72 unique object types across 86,484 frame-by-frame detections.
- 478 unique chairs spotted (10% of frames)
- 329 unique ties spotted (13% of frames)
- 144 unique cups spotted (6% of frames)
- 122 unique dining tables spotted (6% of frames)
- 136 unique wine glasses spotted (4% of frames)
- 141 unique potted plants spotted (4% of frames)
- 47 unique beds spotted (4% of frames)
- 62 unique vases spotted (2% of frames)
- 93.3% of the movie takes place at night
- 95 weapon appearances (1 per minute)
- Contains 39 profanities (0.4 per minute)
- Longest silence: 6 minutes of unbroken quiet
- Peak dialogue speed: 211 words per minute
- Only 3.1% of face detections are smiling
- The film's emotional journey ends on a neutral note
- Shot predominantly with warm tones
DIALOGUE
Words across the runtime
Volume and pace at a glance. Top vocabulary and per-act WPM in Deep Dive.
40% dialogue60% silence / score
8,620
total words
86
words / min
39 · 0.5%
profanity flagged
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