# DeepInfra vs Runware

DeepInfra records 457,810 monthly visits with -8.9% month-over-month growth and Paid pricing. Runware records 402,862 monthly visits with +27.1% growth and Paid pricing.

| Metric | [DeepInfra](https://openaitools.app/tool/deep-infra) | [Runware](https://openaitools.app/tool/runware) |
| :--- | :--- | :--- |
| Website URL | https://deepinfra.com | https://runware.ai |
| Categories | AI Models, AI API, Large Language Models (LLMs), AI Text Generator | AI API, AI Image Generator, Text to Image, AI Models |
| Pricing Model | Paid | Paid |
| Monthly Visits | 457,810 | 402,862 |
| MoM Growth Rate | -8.9% | +27.1% |
| Primary Market | United States | United States |
| Direct Visits | 237,817 | 189,796 |
| Review Score | 4.6 | 4.5 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## DeepInfra

DeepInfra positions itself as an inference cloud rather than a model lab: the product is fast, cheap, reliable access to models other people trained. The catalog spans more than 200 models grouped by task (text generation, text-to-image, text-to-music, text-to-speech, text-to-video, automatic speech recognition, embeddings, rerankers, zero-shot image classification) and by family, so you can pick a Claude, DeepSeek, Flux, Gemini, GLM, Kimi, Llama, Mistral, Nemotron or Qwen model and call it through the same API. Pricing is transparent and usage-based, quoted per million tokens with separate input, output and cached-input rates, and many models carry promotional discounts.

Beyond plain model hosting, DeepInfra runs its own inference-optimized hardware in US-based data centers and layers managed options on top: DeepStart for deploying your own models, DeepCluster for GPU clusters and on-demand GPU rental billed per instance-hour, plus a chat playground for quick testing. The company emphasizes security and privacy — a zero-retention policy for inputs and outputs, SOC 2 and ISO 27001 certifications — which matters for teams handling sensitive data. A large funding round (announced as a $107M Series B) and reported 25x growth in token volume signal an actively scaling business.

Practically, DeepInfra is aimed at engineering teams who want OpenAI-compatible style API calls without managing infrastructure, at startups that need cheap high-volume inference, and at organizations that want to rent GPUs for fine-tuning or custom serving on the same platform they use for hosted models.

**Pricing & Plans:** Paid, pay-as-you-go. Model inference is billed per million tokens with separate input, output and cached-input rates, and many models show temporary percentage discounts. On-demand GPUs are billed per instance-hour. No long-term contracts; enterprise support and custom arrangements are available via contact sales.

- **200+ Model Catalog:** Access text, image, speech, music and video models from multiple families through one consistent API, with task- and family-based browsing.
- **Transparent Token Pricing:** Per-million-token rates with input, output and cached-input breakdowns shown up front, including current discounts on many models.
- **On-Demand GPU Rental:** Rent data-center GPUs by the instance-hour when you need raw compute for fine-tuning, custom serving or burst workloads.
- **Zero-Retention Privacy:** Inputs and outputs are not retained, and the platform holds SOC 2 and ISO 27001 certifications for information security.
- **Managed Deployment Options:** DeepStart and DeepCluster let teams deploy their own models and scale clustered inference without building the infrastructure themselves.

**Strengths:** Very broad model catalog covering text, image, audio and video tasks behind one API; Transparent per-token pricing with cached-input rates and frequent promotional discounts; Security posture is documented: zero retention, SOC 2 and ISO 27001; Self-hosted, inference-optimized hardware with GPU rental and cluster options for scaling

**Limitations:** Costs are metered per token, so spend can grow quickly with high-volume or long-context workloads; The catalog changes fast, which means model names and prices need periodic rechecking; Some models in the listing are previews or promotional, so production reliability varies by model

[Profile (Markdown)](https://openaitools.app/tool/deep-infra.md)

## Runware

Runware started as a low-cost, high-speed image generation API and has grown into an end-to-end AI infrastructure company. The core promise today is consolidation: instead of stitching together separate endpoints for image, video, audio, LLM and 3D tasks, you POST an array of tasks to one endpoint, authenticate with one key, and receive one invoice. Switching models is described as a string change. Requests can travel over REST or WebSockets, results can stream back over SSE, and a webhook can be attached per task.

The performance story is built on hardware the company controls. Runware designs, builds and runs modular data centers called Sonic Pods, and pairs them with an orchestration layer — together branded the Sonic Inference Engine. Models are preloaded across regions and routed through shared queues to a pod that already has the weights in memory, which the company says is where its throughput and unit economics come from. Open models are billed on optimized compute time, so a faster generation costs less; closed and partner models are priced at negotiated volume rates.

Beyond managed model APIs, Runware sells raw compute. Serverless GPU workers are billed by the second and scale to zero when idle, and teams with a predictable baseline can reserve GPU capacity for a term, or take a dedicated bare-metal cluster starting from 72 GPUs. The company markets itself heavily on price — claiming up to 10x lower cost per generation than published market rates and GPU rates that undercut typical neocloud pricing — and backs the platform with SOC 2, ISO 27001 and GDPR compliance, EU/US data residency, a no-training-on-your-data policy, and an optional Zero Data Retention mode for enterprises.

**Pricing & Plans:** Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales.

- **One API for every modality:** Image, video, audio, LLM and 3D tasks all POST to a single endpoint as an array, so mixed-modality batches can travel in one request with shared auth and billing.
- **400K+ model catalog:** Browse hosted, partner and community models through one addressing scheme, control parameters such as stacked LoRAs and swapped VAEs on open models, and add your own uploads.
- **Serverless and reserved GPU compute:** Bring your own container and weights to serverless GPUs billed by the second that scale to zero when idle, or commit to reserved capacity and bare-metal clusters for a lower per-hour rate.
- **Sonic Pods and the Sonic Inference Engine:** Purpose-built modular data centers plus an orchestration layer that keeps weights preloaded across regions and routes requests to pods that already hold the model in memory.
- **Developer tooling and agent integrations:** A hosted MCP server, CLI, skill files, playground, model schemas and llms.txt let you wire Runware into Claude Code, Cursor, Codex or any MCP-capable client with minimal setup.
- **Enterprise-grade trust and compliance:** SOC 2, ISO 27001 and GDPR compliance, EU and US data residency, SSO/SAML, configurable MFA, a strict no-training-on-customer-data policy and optional Zero Data Retention.

**Strengths:** Unusually broad catalog — hundreds of thousands of models behind one consistent endpoint and API key; Aggressive published pricing, with claims of up to 10x lower cost per generation than market rates; Both managed inference and raw compute in one platform, so you can migrate from API calls to your own containers without changing vendors; Real infrastructure differentiation through self-designed modular data centers rather than reselling someone else's capacity

**Limitations:** The breadth of the catalog and the mix of hosted, partner and community models can be overwhelming when choosing a model; Only a subset of models (currently around 300+) has published pricing on the rate sheet, so some community models require checking the playground for cost; LLM billing splits input, output and cache-read token dimensions, adding complexity to cost forecasting; Bare-metal and high-volume reserved capacity are sales-gated rather than self-serve

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

## Frequently Asked Questions

### How do DeepInfra and Runware compare in monthly traffic?

DeepInfra has 457,810 monthly visits, while Runware has 402,862. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

DeepInfra has a month-over-month growth rate of -8.9%; Runware has +27.1%.

### How does pricing compare?

DeepInfra: Paid. Paid, pay-as-you-go. Model inference is billed per million tokens with separate input, output and cached-input rates, and many models show temporary percentage discounts. On-demand GPUs are billed per instance-hour. No long-term contracts; enterprise support and custom arrangements are available via contact sales. Runware: Paid. Pay-as-you-go with no subscription required. Managed inference is billed per generation, per second of video, per character of audio, or per 1M tokens for LLMs; published rates include examples such as FLUX 3 Image Klein from about $0.003 per image and GLM-5.3-Flash at $0.15 per 1M input tokens. Serverless GPU compute is metered by the second (RTX PRO 6000 listed around $1.99 per GPU-hour) and scales to zero; reserved capacity is advertised as low as $0.63 per GPU-hour on term commitments, with dedicated bare-metal clusters available from 72 GPUs. Failed or rate-limited requests are not charged, new users signing up with a business email receive $2 in free credits, and volume discounts are available via sales.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides direct developer API access to Google's proprietary Gemini models rather than community open-weight models. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 2 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | One API key for hundreds of AI models from every major provider | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 3 | [Groq](https://openaitools.app/tool/groq) | 3,987,936 | +10% | Paid | Delivers significantly faster token generation speeds using specialized LPU hardware, though supporting a smaller model catalog. | [.md](https://openaitools.app/tool/groq.md) |
| 4 | [RunningHub](https://openaitools.app/tool/runninghub) | 3,105,554 | -28.5% | Freemium | Cloud ComfyUI platform to run workflows and build AI apps | [.md](https://openaitools.app/tool/runninghub.md) |
| 5 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Offers a similar developer-first cloud for ultra-fast generative media inference, but with distinct pricing tiers. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 6 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Stronger focus on open-source LLM hosting and dedicated clusters, but less tailored for instant image generation. | [.md](https://openaitools.app/tool/together-ai.md) |
| 7 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Provides comparable serverless model deployment and fine-tuning, but features a broader general-purpose ML ecosystem. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 8 | [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | -16.4% | Paid | Delivers unified access to generative media models, but lacks Runware's specialized focus on raw inference speed. | [.md](https://openaitools.app/tool/atlas-cloud.md) |
| 9 | [SiliconFlow](https://openaitools.app/tool/siliconflow) | 276,303 | -10.5% | Pay-as-you-go | Hosts popular open-weight LLMs and multimodal models with aggressive pricing similar to DeepInfra's cost structure. | [.md](https://openaitools.app/tool/siliconflow.md) |
| 10 | [Novita AI](https://openaitools.app/tool/novita-ai) | 271,371 | -10.4% | Paid | Focuses heavily on image generation and Stable Diffusion APIs, but offers slightly different serverless GPU pricing. | [.md](https://openaitools.app/tool/novita-ai.md) |

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Source: https://openaitools.app/compare/deep-infra-vs-runware

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