sourceful
Sourceful: Riverflow V2 Pro
sourceful/riverflow-v2-pro
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
Riverflow V2 Pro (sourceful/riverflow-v2-pro) is an image-generation model from Sourceful listed in the OpenRouter catalog. It accepts text and image inputs and produces image output, with an 8192-token context window. The catalog describes it as the most capable variant of the Riverflow 2.0 lineup, emphasizing fine-grained control and text rendering quality, though these are vendor-supplied claims rather than measured results. No independent model card was available in this source pack, and no benchmark data is listed, so real-world performance should be validated on your own workloads.[1]
Strengths
- Accepts both text and image inputs for image generation, according to the OpenRouter catalog.[1]
- The catalog positions it as the top variant of the Riverflow 2.0 family, highlighting control and in-image text rendering; this is a source-reported claim, not a measured result.[1]
- Text prompt and completion tokens are listed at no charge in the catalog; usage is metered per image token.[1]
Limitations
- Only OpenRouter catalog data was supplied; no independent model card was available in this source pack, so capabilities rest on vendor-reported descriptions.[1]
- No benchmark results are listed, so output quality must be validated against your own workloads before adoption.[1]
- The catalog does not indicate tunable parameters or reasoning features, and does not specify license terms or hardware requirements.[1]
Where to use it
Sources
- [1] OpenRouter catalog · Sourceful: Riverflow V2 ProSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Riverflow V2 Pro is the most powerful variant of Sourceful's Riverflow 2.0 lineup, best for top-tier control and perfect text rendering. The Riverflow 2.0 series represents SOTA performance on image...
Specifications
- Model ID
- sourceful/riverflow-v2-pro
- Canonical ID
- sourceful/riverflow-v2-pro-20260130
- Creator
- sourceful
- Added to OpenRouter
- 02.02.2026
- Context length
- 8,192
- Modality
- text+image->image
- Input modalities
- text, image
- Output modalities
- image
- 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 | input: image |
| Image generation | No measurement | output: image |
| Audio | No measurement | — |
| Video | No measurement | — |
| 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) |
|---|---|---|---|---|---|---|
| Sourceful | 8,192 | — | — | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.