# Polymath vs RunningHub Polymath records 0 monthly visits with — month-over-month growth and Free pricing. RunningHub records 3,105,554 monthly visits with -28.5% growth and Freemium pricing. | Metric | [Polymath](https://openaitools.app/tool/polymath) | [RunningHub](https://openaitools.app/tool/runninghub) | | :--- | :--- | :--- | | Website URL | https://github.com/samim23/polymath | https://www.runninghub.ai | | Categories | AI Stems Splitter, AI Midi Generator, AI Song Remixer, Open Source AI Models | AI App Builder, AI Workflow, AI Image Generator, AI Developer Tools | | Pricing Model | Free | Freemium | | Monthly Visits | 0 | 3,105,554 | | MoM Growth Rate | — | -28.5% | | Primary Market | Global | China | | Direct Visits | 0 | 2,297,199 | | Review Score | 4.4 | 4.4 | | Saved Count | 4 | 2 | | Supported Platforms | Open Source | Website | ## Polymath Polymath is built around a simple idea: any large music collection is effectively an untapped sample pack. Instead of digging through folders manually, you point the tool at your audio and let a chain of neural networks label, slice and align it. Music source separation is handled by Demucs, structure segmentation by sf_segmenter, pitch tracking and key detection by Crepe, and audio-to-MIDI by Basic Pitch, with pyrubberband and librosa covering quantization and metadata. Once a song has been analyzed once, it lives in a local database file, so repeated searches and quantization steps are fast and do not require re-processing. You add tracks with the -a flag (single files, folders or YouTube IDs), quantize with -q against a target BPM or the track's own tempo, and search for similar material with -s. Everything is driven from the terminal or through the included Docker image. Typical workflows split into two camps. Producers and DJs use Polymath to extract a beat from one genre, a bassline from another and horns from a third, all tempo-matched and ready to drop into a DAW — or to assemble smooth, hour-long mixes from tracks that share a feel. Machine-learning developers use it to generate large, richly labeled audio datasets for training generative music models. **Pricing & Plans:** Polymath is free and open source under the MIT license. The repository is public on GitHub, so there is no subscription, license fee or account. Running it does require compatible software (ffmpeg and Python 3.7–3.10) and, for practical speeds, a GPU — the cost of any hardware or cloud compute is yours. - **Library ingestion from disk or YouTube:** Feed Polymath a single track, a folder, or a list of YouTube IDs and it builds a persistent local database of analyzed songs that can be searched instantly afterwards. - **Neural stem separation:** Demucs splits each song into beats, bass, vocals and other stems, which are then saved to a separated folder for use in your DAW. - **Tempo quantization to a common grid:** Every track can be time-stretched and re-aligned to a shared tempo and beat grid (for example 120 BPM), so elements from different songs line up cleanly. - **Structure, key and loudness analysis:** Polymath labels musical sections such as verse and chorus, detects key and loudness, and exposes that metadata for search and filtering. - **Audio-to-MIDI transcription:** Pitch tracking and Basic Pitch transcription turn melodic material into MIDI files you can edit and re-arrange in any instrument track. - **Similarity search across the library:** Given a song already in the library, Polymath finds the most similar tracks (optionally including BPM as a criterion) to support mash-ups and long-form mixes. **Strengths:** Completely free and open source under a permissive MIT license; Chains several proven ML models (Demucs, Crepe, Basic Pitch) into one workflow; Persistent library database makes repeated search and quantization fast; Handles both local files and YouTube sources, plus batch additions **Limitations:** Python stack is pinned to Python 3.7–3.10, so newer environments may need extra setup work; Requires ffmpeg plus a sizeable set of ML dependencies, and initial GPU support is easiest on native installs; Analysis of every new track takes time before it becomes searchable; There is no hosted web UI — everything runs through the command line or Docker [Profile (Markdown)](https://openaitools.app/tool/polymath.md) ## RunningHub RunningHub is an all-in-one AI content creation platform built around cloud ComfyUI. Instead of installing Stable Diffusion, Flux, ControlNet, and LoRA setup on your own GPU, you run workflows on RunningHub's servers and interact through a browser. The platform supports importing and running ComfyUI graphs, then turning them into polished single-click "AI Apps" that non-technical users can operate with simple prompts. Beyond the workflow engine, RunningHub bundles a broad creative toolkit: text-to-image and text-to-video generation, image-to-image and image-to-video conversion, inpainting, outpainting, and upscaling powered by self-developed models. An infinite canvas and rapid-creation templates help users assemble campaigns, product visuals, and short videos. The homepage also showcases a community gallery of featured workflows, model APIs, and viral video templates. RunningHub follows a freemium, credit-based model with free daily usage and subscription tiers for heavier production. It targets creators, small studios, and developers, and offers workflow, model, LLM, and app APIs so teams can embed generational capabilities into their own products. **Pricing & Plans:** Freemium with daily free credits and pay-as-you-go credits; subscription tiers unlock higher concurrency, member discounts, and advanced models. API usage is priced separately. - **Cloud ComfyUI:** Run, import, and share ComfyUI workflows in the cloud without local GPU hardware. - **AI Apps Builder:** Publish a workflow as a single-click AI app that anyone can run with simple inputs. - **Image & Video Generation:** Use hosted image and video models, including self-developed upscaling and enhancement tools, from one dashboard. - **Developer APIs:** Integrate generation into your product via workflow, model, LLM, and app APIs. - **Template Library & Community:** Explore a gallery of community workflows, viral video templates, and creator rewards. **Limitations:** Complex workflows have a learning curve; Credit-based costs add up for heavy video generation; Best experience assumes some ComfyUI familiarity [Profile (Markdown)](https://openaitools.app/tool/runninghub.md) ## Frequently Asked Questions ### How do Polymath and RunningHub compare in monthly traffic? Polymath has 0 monthly visits, while RunningHub has 3,105,554. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Polymath has a month-over-month growth rate of —; RunningHub has -28.5%. ### How does pricing compare? Polymath: Free. Polymath is free and open source under the MIT license. The repository is public on GitHub, so there is no subscription, license fee or account. Running it does require compatible software (ffmpeg and Python 3.7–3.10) and, for practical speeds, a GPU — the cost of any hardware or cloud compute is yours. RunningHub: Freemium. Freemium with daily free credits and pay-as-you-go credits; subscription tiers unlock higher concurrency, member discounts, and advanced models. API usage is priced separately. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Adobe Firefly](https://openaitools.app/tool/adobe) | 396,998,213 | -8.6% | Freemium | Commercially safe generative AI workspace for images, video, audio, vectors, and multi-model creative production. | [.md](https://openaitools.app/tool/adobe.md) | | 2 | [Higgsfield](https://openaitools.app/tool/higgsfield) | 47,127,865 | +16.2% | Freemium, Free Trial | AI-native creative suite for cinematic video and images | [.md](https://openaitools.app/tool/higgsfield.md) | | 3 | [Runway](https://openaitools.app/tool/runwayml) | 7,498,396 | +16.9% | Freemium, Paid, Contact for Pricing | Generative video, image, and audio tools built on frontier AI research | [.md](https://openaitools.app/tool/runwayml.md) | | 4 | [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | +12.8% | Freemium | Discover, download and generate with open-source AI models for image, video and 3D. | [.md](https://openaitools.app/tool/civitai.md) | | 5 | [Pollo AI](https://openaitools.app/tool/pollo-ai) | 6,641,636 | -9.6% | Freemium | All-in-one AI studio for video, image, and agent-driven content creation | [.md](https://openaitools.app/tool/pollo-ai.md) | | 6 | [Krea](https://openaitools.app/tool/krea) | 4,583,022 | +2.9% | Freemium | Realtime generative AI studio for images, video and custom models | [.md](https://openaitools.app/tool/krea.md) | | 7 | [ComfyUI](https://openaitools.app/tool/comfyui) | 4,379,348 | +13.4% | Contact for Pricing, Free | Node-based visual AI studio for images, video, 3D and audio | [.md](https://openaitools.app/tool/comfyui.md) | | 8 | [ModelScope](https://openaitools.app/tool/modelscope-community) | 3,085,423 | +5.1% | Free | Open-source model and dataset hub with one-click online demos | [.md](https://openaitools.app/tool/modelscope-community.md) | | 9 | [Tensor.Art](https://openaitools.app/tool/tensor-art) | 2,618,069 | +9.4% | Free | Free online AI image generation, video creation and model hosting in your browser | [.md](https://openaitools.app/tool/tensor-art.md) | | 10 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/tool/together-ai.md) | --- Source: https://openaitools.app/compare/polymath-vs-runninghub More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)