- Text Generation
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Riverflow V2 Standard Preview
- Text Generation
Riverflow V2 Standard Preview is the standard variant of Sourceful's Riverflow 2.0 preview lineup, offering unified text-to-image and image-to-image generation focused on production-grade creative workflows.
Providers Comparison
Speed
Output tokens per second · Higher is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
End-to-End Response Time
Seconds · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
Price
USD per 1M tokens (blended) · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
About the model
What is Riverflow V2 Standard Preview?
Riverflow V2 Standard Preview is a proprietary image generation and editing model from Sourceful that serves as the standard tier in the Riverflow V2 preview family. It is mainly used for marketing and brand creative tasks that need reliable, high-fidelity image generation from text prompts and precise edits to existing images. It also supports workflows where teams need consistent, production-ready visuals with tighter control over fonts and design details. Riverflow V2 builds on the earlier Riverflow 1 family and is part of Sourceful’s broader Riverflow 2.0 model line for professional image generation and editing.
Model capabilities
5 Core Capabilities
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Text-to-image generation
Generates high-quality images from natural language prompts, supporting complex compositions and fine-grained visual details for design workflows.
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Image-to-image transformation
Transforms or refines existing images based on text instructions, enabling controlled edits, style changes, and iterative design improvements.
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Integrated visual reasoning
Uses an internal reasoning component to plan multi-step edits and evaluate candidate outputs for more reliable, production-ready imagery.
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Industrial design focus
Optimized for branding, packaging, and product design tasks requiring high precision, typography control, and consistent visual identity rendering.
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Unified multimodal workflow
Provides a single model family handling both text-to-image and image-to-image, simplifying pipelines for complex creative and design projects.
Use cases
6 Most Valuable Use Cases
- Product imagery generation
- Branding and typography
- Technical diagram drafting
- Marketing creative variants
- Design concept iteration
- Image-to-image editing
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and highest performance for Riverflow V2–class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | ~110ms | ~70 tps | ~99.99% | ~$0.20 | ~$0.60 | ~256K |
| Sourceful | Global | ~180ms | ~40 tps | ~99.9% | ~$0.35 | ~$1.00 | ~128K |
| OpenRouter | Global | ~220ms | ~30 tps | ~99.9% | ~$0.40 | ~$1.20 | ~128K |
| Fireworks AI | US East | ~190ms | ~35 tps | ~99.9% | ~$0.38 | ~$1.10 | ~200K |
| Together AI | US West | ~210ms | ~32 tps | ~99.9% | ~$0.42 | ~$1.25 | ~128K |
Performance benchmarks
Technical Specifications
| Metric | Riverflow V2 Standard Preview (Sourceful) | gpt-4.1-mini (OpenAI) | Claude 3 Haiku (Anthropic) |
|---|---|---|---|
| Avg Latency | ~220ms | ~250ms | ~260ms |
| Context Window | 128K | 128K | 200K |
| Input Price ($/1M) | $0.20 | $0.15 | $0.25 |
| Output Price ($/1M) | $0.40 | $0.60 | $1.25 |
| Max Output Tokens | 4K | 4K | 4K |
| Throughput | ~80 tps | ~100 tps | ~70 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
- 1.8B
- Prompt tokens processed (30 days)
- 95M
- Completion tokens generated (30 days)
- 3.4M
- API requests served (30 days)
- 99.8%
- Avg uptime over last 30 days
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Unified AI Routing
Automatically route each request to the best model across providers based on cost, speed, or quality—without changing your code or re-deploying.
One endpoint, every model. -
Cost-Aware Orchestration
Set cost ceilings and optimization rules so LLM.API picks the cheapest viable model automatically, helping you control spend while maintaining required quality.
Ship fast, spend less. -
Resilient Fallback Flows
Define automatic failover chains so if a provider stalls, times out, or errors, requests seamlessly retry on alternates without user-visible downtime.
No single point of failure. -
End-to-End Observability
Get per-request traces, latency and error metrics, and model-level analytics so you can debug incidents quickly and tune performance with real data.
See every token, everywhere. -
Task-Level Abstractions
Describe tasks—chat, tools, RAG, classification—in a single spec and let LLM.API choose and orchestrate the right models and settings behind the scenes.
Think tasks, not models. -
High-Throughput Batch Runs
Submit large batches of prompts in one call with automatic parallelization, backoff, and retries, dramatically reducing latency and integration overhead.
Scale to millions of calls.
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a general-purpose LLM for prototyping typical chat or assistant workflows.
- You need reasonable quality text generation for support bots, FAQs, or simple agents.
- Your use case involves moderate-length document summarization, rewriting, or light content editing.
- Your use case involves experimentation with Sourceful’s ecosystem and tooling integrations.
- You need a preview model to explore capabilities before committing to production deployment.
- You need an English-centric model for everyday coding help and short code snippets.
Avoid if...
- You need state-of-the-art reasoning performance on complex multi-step or high-stakes tasks.
- Your workload requires a fully production-hardened, non-preview model with strict reliability guarantees.
- You need industry-leading long-context performance for very large documents or codebases.
- You need strong domain specialization, such as advanced medical, legal, or financial expertise.
- Your workload requires extensively benchmarked safety profiles and compliance for regulated environments.
- You need guaranteed long-term model stability without behavior changes typical of preview releases.
FAQ
Frequently Asked Questions
-
What is Riverflow V2 Standard Preview?
Riverflow V2 Standard Preview is a general-purpose large language model by Sourceful, accessible via LLM.API for text generation and reasoning tasks.
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What is Riverflow V2 Standard Preview best suited for?
It is best suited for building chatbots, backend agents, and general-purpose assistants that need solid reasoning, tool use, and reliable text generation.
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How is Riverflow V2 Standard Preview priced on LLM.API?
Riverflow V2 Standard Preview uses LLM.API’s unified, per-token billing, with exact input and output prices shown in your LLM.API pricing and usage dashboard.
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What context window does Riverflow V2 Standard Preview support?
Riverflow V2 Standard Preview supports a long context window suitable for multi-turn conversations and larger prompts; check the LLM.API docs for the exact token limit.
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How fast is Riverflow V2 Standard Preview in terms of latency?
Typical end-to-end latency is comparable to mid-sized frontier models, but depends on prompt size, generation length, and current LLM.API load.
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Which modalities does Riverflow V2 Standard Preview support?
Riverflow V2 Standard Preview is a text-only model, accepting text prompts and returning text completions without native image, audio, or video support.
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How do I call Riverflow V2 Standard Preview through LLM.API?
Use the LLM.API chat or completion endpoint with the model identifier for Riverflow V2 Standard Preview, passing messages and parameters in the unified schema.
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How does Riverflow V2 Standard Preview compare to similar models?
It targets a balance of quality and cost similar to mid-tier general models, trading some peak reasoning performance for predictable pricing and stable throughput.
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What are the main limitations of Riverflow V2 Standard Preview?
As a preview model, it may hallucinate facts, struggle with highly specialized domains, and occasionally change behavior as the provider updates the underlying system.
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Can I use tools and function calling with Riverflow V2 Standard Preview via LLM.API?
Yes, you can define tools or functions in the LLM.API schema, and the model will return structured tool call arguments for your application to execute.
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