Riverflow V2.5 Fast is the speed-optimized variant of Sourceful's Riverflow 2.5 lineup, best for production deployments and latency-critical workflows.
The Riverflow 2.5 series is a unified text-to-image and image-to-image family that treats generation as a production workflow, using an integrated reasoning model to plan multi-step edits and judge candidates before accepting a result. Riverflow 2.5 combines their reasoning with a mix of open image diffusion models to provide greater accuracy and steerability. Reasoning effort is controllable via the reasoning parameter (low/medium/high) - higher levels do more editing passes and apply a stricter internal judge, while lower levels return faster for early exploration. It generates at 1K and 2K resolution (no 4K) and accepts up to 4 input images for editing.
Pricing is dynamic: cost is finalized per job at completion based on billable processing, so it scales with reasoning effort, resolution, and editing complexity rather than a fixed per-image rate.
Additional features (via image_config):
See the image generation docs for details: https://openrouter.ai/docs/features/multimodal/image-generation(opens in new tab)
Note: Sourceful imposes a 4.5MB request size limit, therefore it is highly recommended to pass image URLs instead of Base64 data.
Modalities
Price
from $0.019/image
Context
33K
Released
Jun 4, 2026
This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.
The chart below shows the average price customers are actually paying after prompt caching. Depending on the amount of repeated context you send, this can be 60–80% cheaper than the provider list price. Shown are rolling averages from the past 30 days.
Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).
Percent of requests that succeeded over the last 30 days. OpenRouter monitors every provider continuously and automatically retries on the next-best provider when one returns an error.
Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.
Token volume and request traffic to this model over time.
Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.