# RightNow Inference (RunInfra) vs SiliconFlow

RightNow Inference (RunInfra) records 18,110 monthly visits with -22.6% month-over-month growth and Free Trial, Paid, Contact for Pricing pricing. SiliconFlow records 276,303 monthly visits with -10.5% growth and Pay-as-you-go pricing.

| Metric | [RightNow Inference (RunInfra)](https://openaitools.app/tool/runinfra) | [SiliconFlow](https://openaitools.app/tool/siliconflow) |
| :--- | :--- | :--- |
| Website URL | https://runinfra.ai | https://www.siliconflow.com |
| Categories | AI Developer Tools, Large Language Models (LLMs), AI API, Open Source AI Models | AI Developer Tools, AI API, AI Models |
| Pricing Model | Free Trial, Paid, Contact for Pricing | Pay-as-you-go |
| Monthly Visits | 18,110 | 276,303 |
| MoM Growth Rate | -22.6% | -10.5% |
| Primary Market | India | United States |
| Direct Visits | 7,781 | 95,109 |
| Review Score | 4.4 | 4.6 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## RightNow Inference (RunInfra)

RightNow Inference, which operates at runinfra.ai, is a Y Combinator-backed inference provider focused on the economics of agentic workloads. Agents tend to resend the same context on every turn, which makes input tokens the dominant cost. RightNow Inference addresses this with session-aware routing: repeat calls from one session prefer the GPU replica that already holds the relevant KV cache, so cached input is billed at a fraction of list price.

The platform serves a curated library of open-weight models — including models from the DeepSeek, GLM, Qwen and Step families — through endpoints compatible with the OpenAI and Anthropic SDKs, so existing agent code needs minimal changes. The company publishes per-model output speed, cache-hit rates and effective input pricing, and documents its cache measurement methodology publicly.

Beyond metered API usage, RightNow Inference offers coding plans from $10 a month designed for tools such as Claude Code and opencode, with usage that resets on rolling five-hour and weekly windows and a free standby option when a limit is reached. The service is marketed to teams that want controllable costs without giving up open-model quality.

**Pricing & Plans:** Metered API pricing is published per model, with cached input rates starting around $0.01 per million tokens and effective input costs often several times lower than list thanks to high cache-hit rates. Coding plans start at $10/month (Starter), $29/month (Pro) and $99/month (Team), with included usage that resets every five hours and weekly, plus pay-as-you-go credits or a free standby tier at the limit. A free trial and contact-based enterprise arrangements are also offered.

- **Warm-cache session routing:** Automatically keeps repeated calls from one agent session on the replica that already holds its context, reaching reported cache-hit rates around 99% and cutting effective input costs.
- **Drop-in API compatibility:** One API key works with both the OpenAI and Anthropic SDKs, so existing agent code can switch providers with minimal changes.
- **Curated open-model library:** Serves open-weight models with published pricing, tool calling, JSON mode, streaming and image-input capabilities, plus live output-speed and cache metrics.
- **Transparent cached billing:** Cache hits appear in usage and are billed at the cached rate, with a published measurement methodology and per-model effective input rates.
- **Coding-agent plans:** Flat monthly plans for Claude Code, opencode and 20+ other agents, with usage windows and a free standby option when limits are reached.

**Strengths:** Session-aware routing can push cache-hit rates near 99%, sharply lowering effective input cost; OpenAI and Anthropic SDK compatibility keeps migration effort low; Published per-model speed, cache and pricing data supports informed comparisons; Affordable coding plans with a free standby option when limits are hit

**Limitations:** Model library is curated and smaller than large general-purpose aggregators; Cached and effective pricing depends on best-effort cache hits, so results vary by workload; Some reported benchmark figures come from the vendor's own measurement method

[Profile (Markdown)](https://openaitools.app/tool/runinfra.md)

## SiliconFlow

SiliconFlow positions itself as AI infrastructure rather than a single model. The platform aggregates a broad catalog spanning text LLMs, image generation (for example FLUX family), video, and audio models, so teams can switch or compare models by changing one parameter instead of rebuilding an integration. Requests are served through an OpenAI-compatible endpoint, meaning existing SDK code often works with only a base-URL and key swap.

Deployment is flexible by design. Developers can start on Serverless inference with pay-per-use billing and no setup, move to dedicated endpoints for isolation and throughput, or reserve NVIDIA H100/H200, AMD MI300 and RTX 4090 class GPUs when they need guaranteed capacity and predictable billing. An Elastic GPU (FaaS) tier targets bursty or spiky inference workloads, and an AI Gateway layer adds smart routing, rate limiting and cost controls across models.

The platform also covers the surrounding lifecycle: data access and processing, fine-tuning and one-click deployment of customized models, and an inference engine tuned in-house for higher throughput and lower latency. SiliconFlow states that customer data is not stored, and pricing is published per million tokens with separate input, cached-input and output rates, which makes cost forecasting relatively straightforward.

**Pricing & Plans:** Pay-as-you-go with no upfront commitment: serverless inference is billed per million tokens (separate input, cached-input and output rates) or per generated image, and pricing tables are published publicly per model. Capacity-based options include dedicated endpoints, reserved GPUs and elastic GPU deployment, typically quoted via a sales conversation. A free "Get Started" tier is offered so you can test models before committing.

- **One OpenAI-compatible API:** Access a large catalog of LLMs and multimodal models through a single endpoint, so most existing SDK code works after swapping the base URL and key.
- **Serverless, dedicated and reserved deployment:** Start with pay-per-use serverless calls, then move to dedicated endpoints, reserved H100/H200/MI300 GPUs or elastic GPU (FaaS) deployment as throughput and cost requirements grow.
- **Fine-tuning and one-click deployment:** Customize supported models on your own data and push the tuned variant to a hosted endpoint without building a training pipeline from scratch.
- **Published per-token pricing:** Transparent rate tables list input, cached-input and output prices per million tokens, plus per-image rates for generation models, making budget planning concrete.
- **AI Gateway routing and controls:** A gateway layer centralizes model access with smart routing, rate limiting and cost-control policies across providers and model families.

**Strengths:** Large multi-vendor catalog behind one OpenAI-compatible API reduces integration work; Transparent, published per-token and per-image pricing makes cost modeling predictable; Deployment options scale from serverless prototyping to reserved GPUs without a platform migration; Stated no-data-retention policy and in-house inference optimization for latency and throughput

**Limitations:** Model-specific rate details and rapid catalog changes require monitoring to keep cost models accurate; Reserved GPU and dedicated capacity pricing is sales-led rather than fully self-serve; Feature depth varies by model family, so some advanced options are not uniform across the catalog

[Profile (Markdown)](https://openaitools.app/tool/siliconflow.md)

## Frequently Asked Questions

### How do RightNow Inference (RunInfra) and SiliconFlow compare in monthly traffic?

RightNow Inference (RunInfra) has 18,110 monthly visits, while SiliconFlow has 276,303. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

RightNow Inference (RunInfra) has a month-over-month growth rate of -22.6%; SiliconFlow has -10.5%.

### How does pricing compare?

RightNow Inference (RunInfra): Free Trial, Paid, Contact for Pricing. Metered API pricing is published per model, with cached input rates starting around $0.01 per million tokens and effective input costs often several times lower than list thanks to high cache-hit rates. Coding plans start at $10/month (Starter), $29/month (Pro) and $99/month (Team), with included usage that resets every five hours and weekly, plus pay-as-you-go credits or a free standby tier at the limit. A free trial and contact-based enterprise arrangements are also offered. SiliconFlow: Pay-as-you-go. Pay-as-you-go with no upfront commitment: serverless inference is billed per million tokens (separate input, cached-input and output rates) or per generated image, and pricing tables are published publicly per model. Capacity-based options include dedicated endpoints, reserved GPUs and elastic GPU deployment, typically quoted via a sales conversation. A free "Get Started" tier is offered so you can test models before committing.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [OpenAI Platform](https://openaitools.app/tool/openai) | 234,678,639 | -9.6% | Paid | Enterprise developer platform and API for deploying GPT-6 Astra, Sol, Luna, and realtime multimodal agents. | [.md](https://openaitools.app/tool/openai.md) |
| 3 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides direct access to Gemini models with a generous free tier, but lacks broader open-source model variety. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 4 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Aggregates a wider selection of global models, but lacks SiliconFlow's specialized high-throughput open-weight infrastructure. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 5 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) |
| 6 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Google's family of lightweight, open-weight AI models | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 7 | [Groq](https://openaitools.app/tool/groq) | 3,987,936 | +10% | Paid | Ultra-fast AI inference on the LPU and LPX platform | [.md](https://openaitools.app/tool/groq.md) |
| 8 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Specializes in high-speed generative media and image models, but offers less comprehensive large language model coverage. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 9 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Provides robust serverless inference for open models, but has a different pricing and developer tooling ecosystem. | [.md](https://openaitools.app/tool/together-ai.md) |
| 10 | [OrcaRouter](https://openaitools.app/tool/orcarouter) | 975,300 | -5.2% | Freemium | One OpenAI-compatible gateway for adaptive LLM routing, guardrails, and spend control | [.md](https://openaitools.app/tool/orcarouter.md) |

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Source: https://openaitools.app/compare/runinfra-vs-siliconflow

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