Gemma 4 E4B Apple Silicon Benchmarks
GroundSlate's default vision model. A balance of speed and quality, 5.2 GB.
Who makes it
E2B and E4B are effective-parameter mixtures. The 12B is dense. 26B-A4B is a mixture-of-experts. GroundSlate runs the 4-bit MLX conversions from mlx-community.
- Maker
- Google DeepMind
- Line
- Gemma 4
- Size
- 5.2 GB
- Weights
- mlx-community/gemma-4-e4b-it-4bit
- License
- Apache License 2.0
Against the other timed models
Still
3.49s
Prefill 0.87s
136 tok
52 tok/s decode
Video chunk
7.86s
323 tok
Still
secondsGemma 4 E4B
3.49s
Video chunk
secondsGemma 4 E4B
7.86s
On each chip
How long Gemma 4 E4B takes on every chip, timed by the benchmark in the app on customers' own Macs. Every test on every chip
Describe a still
median timeThe local vision model describes one frame, the way it does when you import footage.
- M4 Pro24 GBFastest4.39s
- M632 GB5.25s
Still
Still prompt
You are a still-photo analyst. Look at this single photograph. Reply ONLY with compact JSON: {"desc":"a full paragraph of 4-6 factual sentences about this photograph. Cover, in this order: who is present and what they are doing; where this is and what kind of place it is; the notable objects and any text visible on signs, screens or clothing; the light, weather and time of day if they are apparent; and anything distinctive worth remembering about the moment. Write only what you can SEE. Do not speculate about feelings, relationships or backstory, do not pad with generic phrases, and never begin a sentence with 'The image shows' or 'This photo captures' — state the observation directly","subject":"<what the main subject is>","shot":"wide|medium|close|macro","setting":"indoor|outdoor|unknown","venue_type":"<what KIND of place this is: beach, restaurant, playground, living room, parking lot, forest trail, ... or unknown>","notable_objects":["<up to 5 salient objects>"]}. Answer "unknown" for setting or venue_type whenever you are unsure — abstaining costs you nothing. venue_type is a KIND of place, never a NAME: 'a beach', not 'Bondi Beach'. CRITICAL: never invent or guess the name of any person or business. Do NOT read a name off signage or clothing and attribute it to a person. Describe people generically — 'a woman', 'a child on a swing', 'a man in a red jacket'. Use a person's name ONLY if it is explicitly supplied to you in the context above; otherwise use no name at all. NAME OBJECTS SPECIFICALLY when you can actually identify them: 'a can of Coca-Cola' beats 'a drink', 'a yellow school bus' beats 'a vehicle'. Read product labels and use the brand when it is legible. But do NOT guess a specific dish, product, or place name if you are unsure — describe what you actually see (shape, colour, setting), not a confident wrong label. Trust any provided context over your assumptions.Output · E4B
{
"desc": "Three individuals are visible, with the woman in the foreground smiling while looking off into the distance. They are situated outdoors on a walkway overlooking a large body of water, possibly the ocean. In the background to the left, a Ferris wheel is partially visible. The scene is bathed in the warm, golden light of either sunrise or sunset. The subjects are dressed in casual attire, and the composition focuses on the expansive view.",
"subject": "smiling woman",
"shot": "medium",
"setting": "outdoor",
"venue_type": "seaside walkway",
"notable_objects": [
"Ferris wheel",
"railing",
"ocean"
]
}Video chunk
Video chunk prompt
You are watching one continuous segment of a video (t=0.00s to 12.00s), given as 6 frames in chronological order:
Image 1 = t=0.00s
Image 2 = t=2.00s
Image 3 = t=4.00s
Image 4 = t=6.00s
Image 5 = t=8.00s
Image 6 = t=10.00s
No people have been identified in this segment.
Describe this video segment. Reply ONLY with JSON:
{"shots":[{"start":<sec>,"end":<sec>,"desc":"<=20 words","subject":"<s>","shot":"wide|medium|close|macro","motion":"static|slow|fast","center_x":<0..1>,"setting":"indoor|outdoor|unknown","venue_type":"<kind>","notable_objects":["<up to 5>"]}],"best_segment":{"start":<sec>,"end":<sec>,"reason":"<=15 words"},"track":[{"t":<sec>,"x":<0..1>} x6],"summary":"2-4 factual sentences. Each subject AT MOST ONCE.","visual_kind":"footage"}Output · E4B
{
"shots": [
{
"start": 0,
"end": 2,
"desc": "A young woman smiles while looking out at the ocean at sunset.",
"subject": "Young woman",
"shot": "medium",
"motion": "slow",
"center_x": 0.3,
"setting": "outdoor",
"venue_type": "rooftop",
"notable_objects": [
"ocean",
"sunset"
]
},
{
"start": 2,
"end": 4,
"desc": "The woman continues to smile, with others visible behind her.",
"subject": "Young woman",
"shot": "medium",
"motion": "static",
"center_x": 0.3,
"setting": "outdoor",
"venue_type": "rooftop",
"notable_objects": [
"ocean",
"sunset"
]
},
{
"start": 4,
"end": 6,
"desc": "The scene remains the same, capturing the beautiful sunset view.",
"subject": "Group of people",
"shot": "medium",
"motion": "static",
"center_x": 0.5,
"setting": "outdoor",
"venue_type": "rooftop",
"notable_objects": [
"ocean",
"sunset"
]
}
],
"best_segment": {
"start": 0,
"end": 6,
"reason": "Establishes the setting and mood of the scene."
},
"track": [
{
"t": 0,
"x": 0.3
},
{
"t": 2,
"x": 0.3
},
{
"t": 4,
"x": 0.3
},
{
"t": 6,
"x": 0.3
}
],
"summary": "The video captures a group of young people enjoying a beautiful sunset view from an elevated location. The main subject, a young woman, smiles warmly while looking out over the vast ocean. The setting appears to be a rooftop or high vantage point overlooking the water.",
"visual_kind": "footage"
}MacBook Pro, Apple M3 Max, 64 GB unified memory. mlx-vlm 0.6.10. 2026-08-27.