black-forest-labs
Black Forest Labs: FLUX Video Upscale
black-forest-labs/flux-video-upscale
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter's catalog, black-forest-labs/flux-video-upscale is a Black Forest Labs model for enlarging an existing source video by 1.5× to 3× while preserving its duration, optionally guided by a prompt. The catalog identifies text and video inputs with video output. These are source-reported capabilities rather than measured performance; the source pack contains no benchmark results, and no independent model card was available.[1]
Strengths
Limitations
- Only catalog evidence is supplied; an independent model card was not available, so real workloads still need validation.[1]
- No measured output quality, artifact, latency, codec, or resolution results are provided.[1]
- The description mentions an optional prompt, but no supported parameters are listed, leaving its controls unclear.[1]
Where to use it
Sources
- [1] OpenRouter catalog · Black Forest Labs: FLUX Video UpscaleSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
FLUX Video Upscale is a video upscaling model from Black Forest Labs. It enlarges a single source video by 1.5× to 3× while preserving its duration, with an optional prompt...
Specifications
- Model ID
- black-forest-labs/flux-video-upscale
- Canonical ID
- black-forest-labs/flux-video-upscale-20260819
- Creator
- black-forest-labs
- Added to OpenRouter
- 19.08.2026
- Context length
- 0
- Modality
- text+video->video
- Input modalities
- text, video
- Output modalities
- video
- Token pricing
- No per-token price in the source snapshot — see OpenRouter for the billing unit
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | — |
| Writing | No measurement | — |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | input: video · output: video |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Black Forest Labs | 0 | — | — | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.