The scene animates, but the report says the requested prompt details are not properly reflected.

⚠ Struggled🧾 artifact-verifiedinput + output shownTest date not recordedLeonardo AI
What was measured
Prompt Accuracy

How faithfully the video follows the motion, scene, and detail instructions given in the prompt.

decisive for this rankingtransformation

For image-to-video, following the requested motion and scene changes is central to judging whether the tool produced the intended video. (3 of 3 judges)

What was given, what came back

Test input: 3D rendered street scene image with forward dolly prompt · image · group: image-to-cinematic-video
Input — what we sent
3D rendered street scene image with forward dolly prompt
3D rendered street scene image with forward dolly prompt

A rendered 3D street scene with multiple characters and environment detail, tested using a forward-dolly cinematic prompt with crowd motion, cart movement, atmospheric haze, and sunset lighting.

Why this input is hard
  • · Complex multi-subject scene animation
  • · Character consistency in crowd motion
  • · Camera movement stability during forward dolly
  • · Environmental motion such as clouds, trees, and birds
  • · Prompt adherence across foreground and background elements
Provenance
Observation
293512d4-0fe0-47d3-a867-42336caaf9a4
Evidence run
b8778c3c-4fb1-48b2-bf35-4e08a3b82d8e
Study
Generate a cinematic AI video from a single image
Research task
86b94urgr
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input + output shown
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "leonardo-ai",
  scenario: "image-to-cinematic-video"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 2 other tools
measured on Prompt Accuracy
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com