# SiliconFlow

According to OpenAITools.app telemetry verified on 2026-11-11, SiliconFlow (siliconflow.com) is an AI platform indexed under AI Developer Tools generating 276.3K monthly visits with a month-over-month traffic delta of -32.46K (-10.5%). Its primary geographic market is United States (18.8% traffic share), and it operates on a Pay-as-you-go pricing model. Top competing alternatives by monthly volume include OpenRouter (19.94M visits/mo), Together AI (1.65M visits/mo), DeepInfra (457.81K visits/mo).

One API for fast, cost-predictable inference on LLMs and multimodal models

## Key Telemetry & Specifications

| Metric | Value |
| :--- | :--- |
| Tool Name | SiliconFlow |
| Handle | siliconflow |
| Status | active |
| Origin | independent |
| Maintenance | active |
| Official Domain | siliconflow.com |
| Website URL | https://www.siliconflow.com |
| Categories | AI Developer Tools, AI API, AI Models |
| Pricing Model | Pay-as-you-go |
| Monthly Visits | 276,303 |
| MoM Traffic Change | -32,455 |
| MoM Growth Rate | -10.5% |
| Primary Market | United States |
| Market Share | 18.8% |
| Direct Visits | 95,109 |
| Organic Search Visits | — |
| Social Visits | — |
| Referral Visits | 18,122 |
| Email Visits | 2,118 |
| Review Score | 4.6 |
| Saved Count | 1 |
| Supported Platforms | Website |
| Billing Platforms |  |
| Attributes | Features: Website |
| Tags |  |

## Overview

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.

## Key Features & Capabilities

- **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.

## Primary Use Cases

- **Ship LLM features fast (Application developers):** Prototype and productionize chat, summarization or RAG features through one API without provisioning or tuning GPUs yourself.
- **Cost-optimized inference at scale (ML and platform engineers):** Route high-volume traffic across flash, pro and cached-input tiers, then reserve GPUs where guaranteed throughput beats spot capacity.
- **Multimodal content pipelines (Product teams):** Generate images or video and combine them with text models in one workflow, using a single account and billing surface.
- **Tool-using and multi-step agents (Agent builders):** Serve reasoning and function-calling models behind a stable endpoint with gateway-level rate limits to keep agent loops reliable and affordable.

## 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

## Frequently Asked Questions

### What kinds of models can I use on SiliconFlow?
The catalog covers text LLMs (including DeepSeek, Qwen, GLM and Kimi families), image generation models such as the FLUX series, plus video and audio models. New releases are added regularly and appear with context length and pricing on the models and pricing pages.

### How does billing work?
Serverless inference is billed pay-as-you-go, with separate rates for input, cached input and output tokens per million tokens, and per-image pricing for generation models. You can also pay for dedicated endpoints or reserved GPU capacity if you need guaranteed performance.

### Is it compatible with the OpenAI SDK?
Yes. The API is OpenAI-compatible, so in many cases you only change the base URL and API key to point existing integrations at SiliconFlow models.

### Can I fine-tune models here?
Fine-tuning is supported, with one-click deployment of the resulting model to a hosted endpoint so you can serve your customized variant alongside stock models.

### What is SiliconFlow's monthly traffic and growth trend?
SiliconFlow currently receives 276.3K monthly visits, with a month-over-month traffic change of -32.46K (-10.5% growth rate). Its primary source market is United States (18.8% share), including 95.11K direct visits/mo and — organic search visits/mo.

### Is SiliconFlow free? What is its pricing model?
SiliconFlow operates on a Pay-as-you-go pricing model. 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. Supported billing and checkout platforms include: not listed.

### What are the best SiliconFlow alternatives in 2026?
Based on OpenAITools.app category traffic and feature fit, the top five alternatives to SiliconFlow are: 1. OpenRouter (19.94M visits/mo); 2. Together AI (1.65M visits/mo); 3. DeepInfra (457.81K visits/mo); 4. Fireworks (659.69K visits/mo); 5. Google AI Studio (112.62M visits/mo).

### Which platforms and core AI capabilities does SiliconFlow support?
SiliconFlow is classified under AI Developer Tools, AI API, AI Models, supports the following platforms: Website, and its core capability tags include: AI Developer Tools, AI API, AI Models.

## Alternatives

| Tool Name | Monthly Visits | Pricing Model | Compare |
| :--- | :--- | :--- | :--- |
| [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | Paid | [Compare](https://openaitools.app/compare/openrouter-ai-vs-siliconflow) |
| [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | Freemium, Paid | [Compare](https://openaitools.app/compare/siliconflow-vs-together-ai) |
| [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | Paid | [Compare](https://openaitools.app/compare/deep-infra-vs-siliconflow) |
| [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | Contact for Pricing | [Compare](https://openaitools.app/compare/fireworks-ai-vs-siliconflow) |
| [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | Freemium | [Compare](https://openaitools.app/compare/google-ai-studio-vs-siliconflow) |
| [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | Paid | [Compare](https://openaitools.app/compare/replicate-ai-vs-siliconflow) |
| [Novita AI](https://openaitools.app/tool/novita-ai) | 271,371 | Paid | [Compare](https://openaitools.app/compare/novita-ai-vs-siliconflow) |
| [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | Paid, pay-as-you-go usage-based pricing | [Compare](https://openaitools.app/compare/fal-ai-vs-siliconflow) |
| [AI/ML API](https://openaitools.app/tool/ai-ml-api) | 232,946 | Pay-as-you-go credits (free to start); enterprise custom pricing on request | [Compare](https://openaitools.app/compare/ai-ml-api-vs-siliconflow) |
| [Chutes](https://openaitools.app/tool/chutes) | 250,187 | Paid | [Compare](https://openaitools.app/compare/chutes-vs-siliconflow) |
| [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | Free | [Compare](https://openaitools.app/compare/siliconflow-vs-unsloth-ai) |
| [OpenAI Platform](https://openaitools.app/tool/openai) | 234,678,639 | Paid | [Compare](https://openaitools.app/compare/openai-vs-siliconflow) |

---
Source: https://openaitools.app/tool/siliconflow