# Agent 37 vs Replicate AI

Agent 37 records 180,030 monthly visits with +24.2% month-over-month growth and Free Trial, Contact for Pricing pricing. Replicate AI records 904,038 monthly visits with -8.4% growth and Paid pricing.

| Metric | [Agent 37](https://openaitools.app/tool/agent-37) | [Replicate AI](https://openaitools.app/tool/replicate-ai) |
| :--- | :--- | :--- |
| Website URL | https://www.agent37.com | https://replicate.com |
| Categories | AI Coaching, AI Agent, AI Developer Tools, Large Language Models (LLMs) | AI API, AI Models, AI Developer Tools, Open Source AI Models |
| Pricing Model | Free Trial, Contact for Pricing | Paid |
| Monthly Visits | 180,030 | 904,038 |
| MoM Growth Rate | +24.2% | -8.4% |
| Primary Market | Paraguay | United States |
| Direct Visits | 72,672 | 577,501 |
| Review Score | 4.3 | 4.6 |
| Saved Count | 0 | 5 |
| Supported Platforms | Website | Website |

## Agent 37

Agent 37 is a cloud infrastructure product aimed at people who need somewhere real for AI agents to run. Instead of a chat window, every customer gets a sandbox: an isolated Linux container with CPU, memory, persistent disk, an optional public HTTPS URL, and outbound network access. The company positions itself primarily on price, claiming its sandboxes cost roughly 94% less than most competing providers and publishing a comparison table against AWS, Daytona, E2B, Modal, Vercel, and others. Billing is prepaid and metered by the minute — vCPU, memory, and disk each have their own unit rate — with no subscription fee.

Beyond raw compute, Agent 37 ships a layer of agent-specific conveniences. You can start from a ready-made harness such as Claude Code, Codex, OpenClaw, OpenCode, or Hermes, or bring your own Docker image. Agents keep their files across sleep, stop and restart cycles, and can be given cron schedules so they run unattended and simply report results. Model access can come from the platform gateway (Claude, OpenAI, Gemini, Grok) or from your own API keys, and integrations cover services such as Gmail, Slack, Notion, and GitHub through a Composio-based connector catalog, plus metered access to paid tools like web scraping and people/company data.

Security is a major part of the pitch: sandboxes are isolated with gVisor, hosts have no public hostname, ingress goes through Cloudflare with API-key authentication, and outbound traffic is restricted to the public internet. The company states it does not collect prompts, files, or terminal sessions, holds SOC 2 Type I, and is working toward Type II. It also offers startup credits and a free personal agent tier for individuals who just want an agent of their own.

**Pricing & Plans:** Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there.

- **Per-minute sandbox billing:** Pay for vCPU, memory and disk separately while the sandbox runs; when it sleeps or is deleted the compute meter stops and you are left with disk cost only.
- **Ready-made agent harnesses:** Launch Claude Code, Codex, OpenClaw, OpenCode, Hermes, Grok or your own Docker image, each in its own tenant-isolated sandbox.
- **Persistent workspace and scheduling:** Files survive sleep, restarts and weeks of inactivity, and agents can be attached to cron-style schedules so work runs unattended.
- **Networking and custom domains:** Expose individual ports publicly, attach your own domain, or keep everything behind an API key on an authenticated URL.
- **Integrations and metered tools:** Connect 1,000+ apps such as Gmail, Slack, Notion and GitHub, and buy one-off capabilities like scraping or enrichment from the same balance.

**Strengths:** Aggressively low per-minute pricing with an explicit public comparison against major sandbox providers; Persistent disk and scheduling make it suitable for real agent workloads rather than one-shot tasks; Strong isolation story (gVisor, firewalled egress, no public hostnames) plus SOC 2 Type I; Flexible model and tool sourcing: platform gateway, bring-your-own keys, or pay-per-use tools

**Limitations:** Prepaid balance model means you must top up in advance and monitor spend across many sandboxes; Persona pricing and plan details are only available after contacting the team for the white-label and enterprise tracks; Documentation and benchmark claims are largely self-published, so independent verification is limited

[Profile (Markdown)](https://openaitools.app/tool/agent-37.md)

## Replicate AI

Replicate's core pitch is a uniform interface over thousands of models. Models range from image generators such as FLUX, GPT Image, Nano Banana, Seedream, and Recraft, to video models from MiniMax, ByteDance, xAI, and Alibaba, plus speech, music, captioning, image restoration, and large language models. Each model page exposes concrete inputs, versioned releases, and cost estimates, and you call them the same way regardless of the underlying framework. The catalog blends community-contributed open-source models with officially maintained proprietary ones, and the company positions every listed model as actually working with a production-ready API rather than a demo.

Beyond running hosted models, Replicate is a deployment and training layer. Cog, the project's open-source packaging tool, converts a model into a container with a generated HTTP API, so your own weights can be served from the same interface. Public models run on shared infrastructure and you pay only for processing time, while private models run on dedicated hardware and are billed for the full time instances are online — setup, idle, and active — with an exception for fast-booting fine-tunes that only bill when processing. Automatic scaling handles traffic spikes without manual capacity planning.

Pricing is strictly consumption-based. Public models are usually billed per second of runtime according to the hardware selected, with some billed per input and output instead; published examples include Flux 1.1 Pro at $0.04 per output image and DeepSeek R1 at $3.75 per million input tokens. Hardware rates are public too, from a T4 at roughly $0.81 per hour up to eight H100s at about $43.92 per hour. You can start free, and enterprise contracts unlock additional multi-GPU A100, H100, and H200 capacity.

**Pricing & Plans:** Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

- **Thousands of models behind one API:** Run image, video, audio, speech, and language models through a uniform API surface, with official models for FLUX, Nano Banana, Seedream, Grok Imagine, MiniMax, Wan, Seedance, and more.
- **One-line-of-code inference:** Set up a model in minutes and make an API call in Python, Node, or plain HTTP after authenticating with an API token.
- **Cog packaging and custom deployments:** Package your own model with Cog, an open-source tool for packaging machine learning models, and deploy it on dedicated hardware that scales up and down with demand.
- **Model fine-tuning:** Fine-tune models on your own data, including fast-booting fine-tunes that are billed only while actively processing requests rather than for idle time.
- **Published hardware and inference rates:** Transparent per-second hardware rates across CPU, T4, L40S, A100, H100, and H200 configurations, with committed-spend options for multi-GPU capacity.

**Strengths:** Very broad model catalog spanning image, video, audio, speech, and LLMs behind one consistent API; Usage-based billing with openly published per-second hardware and per-output model rates; Cog makes it straightforward to package and deploy your own private models; Automatic scaling handles traffic spikes without manual capacity planning

**Limitations:** Costs are consumption-based and can rise quickly with heavy traffic or always-on private deployments; Private models bill for idle and setup time, not just request processing, unless they are fast-booting fine-tunes; Long-running GPU models can queue on shared public capacity during peak periods; It is an infrastructure layer, so you still need your own prompts, pipelines, and application code

[Profile (Markdown)](https://openaitools.app/tool/replicate-ai.md)

## Frequently Asked Questions

### How do Agent 37 and Replicate AI compare in monthly traffic?

Agent 37 has 180,030 monthly visits, while Replicate AI has 904,038. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Agent 37 has a month-over-month growth rate of +24.2%; Replicate AI has -8.4%.

### How does pricing compare?

Agent 37: Free Trial, Contact for Pricing. Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there. Replicate AI: Paid. Paid, usage-based — you only pay for what you use. Most public models are billed by runtime at per-second hardware rates; some models are billed per input and output (for example, $0.04 per output image on Flux 1.1 Pro, $3.75 per million input tokens on DeepSeek R1). Published GPU hardware ranges from about $0.81/hr for a T4 up to roughly $43.92/hr for 8x H100. Private deployments bill for setup, idle, and active time on dedicated hardware, and you can start for free. Enterprise and volume discounts available.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Excels at routing text and multimodal prompts across various providers, but lacks Replicate's dedicated custom ML deployment. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 2 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Faster serverless execution for image and video models, but less generalized custom model deployment than Replicate. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 3 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | The AI developer cloud for GPU pods, serverless inference and clustering | [.md](https://openaitools.app/tool/runpod.md) |
| 4 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Stronger focus on LLM inference and fine-tuning, but lacks Replicate's diverse community-curated media model catalog. | [.md](https://openaitools.app/tool/together-ai.md) |
| 5 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Runs serverless Python containers optimized for AI model inference and batch jobs rather than persistent agent sandboxes. | [.md](https://openaitools.app/tool/modal-com.md) |
| 6 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Specializes specifically in ultra-efficient model fine-tuning, rather than providing a general-purpose model hosting API. | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 7 | [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | -16.4% | Paid | Offers a broad mix of generative media models via API, but lacks Replicate's massive community deployment ecosystem. | [.md](https://openaitools.app/tool/atlas-cloud.md) |
| 8 | [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | +6% | Contact for Pricing | Delivers exceptionally fast inference speeds for open models, but has a narrower model selection than Replicate. | [.md](https://openaitools.app/tool/fireworks-ai.md) |
| 9 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Significantly cheaper pricing for running open-weight models, but offers fewer advanced custom training and deployment features. | [.md](https://openaitools.app/tool/deep-infra.md) |
| 10 | [Pollinations](https://openaitools.app/tool/pollinations) | 316,875 | +22.8% | Free | Open infrastructure and one API for generative AI builders | [.md](https://openaitools.app/tool/pollinations.md) |

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Source: https://openaitools.app/compare/agent-37-vs-replicate-ai

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