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