# Replicate AI vs Jellyfish (VibeOnly)

Replicate AI records 904,038 monthly visits with -8.4% month-over-month growth and Paid pricing. Jellyfish (VibeOnly) records 0 monthly visits with 0% growth and Demo-based / contact sales pricing.

| Metric | [Replicate AI](https://openaitools.app/tool/replicate-ai) | [Jellyfish (VibeOnly)](https://openaitools.app/tool/vibeonly) |
| :--- | :--- | :--- |
| Website URL | https://replicate.com | https://www.vibeonly.ai |
| Categories | AI API, AI Models, AI Developer Tools, Open Source AI Models | AI Recruiting, AI Testing, AI Developer Tools |
| Pricing Model | Paid | Demo-based / contact sales |
| Monthly Visits | 904,038 | 0 |
| MoM Growth Rate | -8.4% | 0% |
| Primary Market | United States | Global |
| Direct Visits | 577,501 | 0 |
| Review Score | 4.6 | 3.8 |
| Saved Count | 5 | 0 |
| Supported Platforms | Website | Website |

## 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)

## Jellyfish (VibeOnly)

Jellyfish began life as VibeOnly, an AI skills assessment product for evaluating AI-native talent. The company has since repositioned around a different problem: how recruiting firms turn their best recruiters' instincts into something repeatable. The result is Amy, an AI sourcing employee that studies a firm's real hiring behavior and replicates it on new searches.

The product works from intake to outreach. Recruiters hand Amy a job order or call notes; she extracts and proposes requirements, flags gaps the brief missed (for example, whether a government role needs a security clearance), and waits for approval on each requirement. From there she sources beyond LinkedIn into projects, research, and online communities, and shows the evidence behind every match so recruiters decide who is worth submitting.

The core differentiator is learning. Amy records who gets submitted, who gets passed on, and who gets placed, and carries that pattern into the next role — even a role of a different type. Each client's requirements stay separated, and firms choose how much Amy is allowed to do autonomously versus what gets checked first. Access is via a live demo, and the application sign-in lives at recruiter.vibeonly.ai.

**Pricing & Plans:** Jellyfish does not publish public pricing. Access starts with a live demo booked through the site, after which commercial terms are handled directly with the sales team. The legacy VibeOnly free trial is no longer advertised.

- **Taste learning from real outcomes:** Amy tracks who each recruiter submits, passes on, and places, then applies those patterns to future searches instead of relying on static filters.
- **Guided intake and requirement approval:** Paste a job order or call notes and Amy drafts the requirement list, suggests criteria you may have missed, and waits for your approval before anything is added.
- **Sourcing beyond LinkedIn:** Candidates are surfaced from projects, research, and online communities, with supporting evidence for each match so recruiters can judge fit before reaching out.
- **Autonomous sourcing and outreach:** Once Amy understands your taste, she can keep sourcing and contacting candidates while your team is on calls, with configurable autonomy per workflow step.
- **Cross-role and per-client memory:** What Amy learns on one search carries into the next, including different role types, while each client's requirements remain kept separate.

**Strengths:** Learns from actual submissions, rejections, and placements rather than static keyword filters; Surfaces candidates from projects, research, and communities that LinkedIn-first searches overlook; Requirement intake is collaborative — Amy proposes, you approve before criteria are locked in; Configurable autonomy lets firms decide what runs on its own and what needs review

**Limitations:** No public pricing or self-serve plan; you must book a demo to get started; The rebrand from VibeOnly to Jellyfish can be confusing when searching for the product; Value depends on having historical recruiting data for the model to learn from; Best suited to recruiting firms and internal talent teams, not individual job seekers

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

## Frequently Asked Questions

### How do Replicate AI and Jellyfish (VibeOnly) compare in monthly traffic?

Replicate AI has 904,038 monthly visits, while Jellyfish (VibeOnly) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Replicate AI has a month-over-month growth rate of -8.4%; Jellyfish (VibeOnly) has 0%.

### How does pricing compare?

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. Jellyfish (VibeOnly): Demo-based / contact sales. Jellyfish does not publish public pricing. Access starts with a live demo booked through the site, after which commercial terms are handled directly with the sales team. The legacy VibeOnly free trial is no longer advertised.

## 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 | [Workable](https://openaitools.app/tool/workable) | 10,780,627 | +5.5% | Free Trial, Paid | The agent recruits, you manage talent | [.md](https://openaitools.app/tool/workable.md) |
| 3 | [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) |
| 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 | [Jack and Jill](https://openaitools.app/tool/jack-and-jill) | 1,254,267 | +11.2% | Freemium, Contact for Pricing | AI agents that introduce great candidates to ambitious companies | [.md](https://openaitools.app/tool/jack-and-jill.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 | [HireAI: AI Recruiter by Arc](https://openaitools.app/tool/hireai-ai-recruiter-by-arc) | 496,923 | -2.2% | Paid | AI-powered candidate matching inside Arc's vetted remote-talent marketplace | [.md](https://openaitools.app/tool/hireai-ai-recruiter-by-arc.md) |
| 10 | [Kula AI](https://openaitools.app/tool/kula-ai) | 492,326 | +4.2% | Paid, Contact for Pricing | The AI-native ATS that replaces your entire recruiting stack | [.md](https://openaitools.app/tool/kula-ai.md) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)