An 8 GB VRAM workflow. The video builds on the MiniMax H3 local setup guide, which documents the RTX 5060 Laptop GPU and 32 GB system-RAM environment.
Before you start
- The reference-to-video H3 diffusion model, not the text-to-video model from the introductory setup.
- The matching VAEs and text encoder from the local setup guide.
- Reference images with clear roles, plus short video excerpts when continuity requires them.
Inside the tutorial
- 01
Switch to the reference model
The tutorial explicitly changes the diffusion model for reference-to-video generation while retaining the base VAE and text-encoder stack.
Watch at 1:07 - 02
Assign each reference a job
Describe which image controls identity, clothing, a vehicle, or the environment. Then write the action in order, include dialogue, and state the important camera constraints.
Watch at 1:44 - 03
Keep continuation references short
In the eight-second example, the workflow loads the final five frames of the preceding 192-frame clip. This specific range avoids the memory cost of loading the entire previous clip.
Watch at 2:45 - 04
Separate action and spatial references
When the vehicle moves incorrectly, a second video reference supplies its location and orientation. The prompt gives the current action and the spatial reference different responsibilities.
Watch at 4:29 - 05
Inspect speed/quality tradeoffs
The tutorial treats EasyCache as a possible drafting option because the demonstrated speed improvement came with visible quality loss. Check the result before retaining acceleration settings.
Watch at 7:21
What to keep in mind
- Reference consistency does not guarantee spatial continuity. Missing context can change object placement between shots.
- Longer clips and extra reference frames increase memory pressure. Low-resolution distant faces can lose definition.
Source reviewed August 31, 2026. These notes summarize the published tutorial; they are not a new hardware test or a separately verified workflow release.
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