A model aggregator with an ML platform behind it
Abacus.AI sells a multi-model chat assistant (ChatLLM) on top of what is really an enterprise machine-learning platform — so alongside the chat you get agents, document search and the ability to build and serve your own models. → Reach for it when you want one subscription that covers several frontier models AND you expect to grow into custom pipelines rather than staying in a chat window. → The breadth is the trade-off: it is a larger, more technical product than the other platforms in this chapter, and most of it is aimed at data teams.
Not written yet — this chapter is a placeholder for Abacus.AI, one of the all-in-one AI platforms. Research and copy still to come.
The product is aimed at data teams and technical users who need a comprehensive AI stack rather than a simple chatbot, because it bundles many advanced services under one roof.
Select Abacus.AI when you want a single subscription covering several frontier models and plan to expand into custom pipelines, agents, or document‑search workloads beyond just chat interactions.
Abacus AI Desktop is the local client that gives you instant access to ChatLLM, coding tools and agents without opening a browser each time.
Sign into Abacus AI Desktop so you can start using ChatLLM and its integrated tools
Team collaboration in ChatLLM lets multiple users work together on the same AI workspace.
You will be able to add new users to your ChatLLM project and see them listed as collaborators.
The Image tab lets you generate pictures using a selection of top‑tier diffusion models directly inside ChatLLM.
Create AI‑generated images that reflect your textual description and chosen settings
An AI Agent in ChatLLM can automatically analyze and summarize uploaded documents.
You will set up an agent that extracts key points from PDFs or Word files you provide.
The Code Playground feature lets you generate, execute, and see output of self‑contained code snippets.
You will write a short Python script, run it, and observe its output directly in ChatLLM.
print('Hello from Abacus AI').print(2+3)) and run again to verify changes.Projects store custom instructions, uploaded files and settings that are automatically applied to every chat created inside them.
Set up a named project that injects the same context into all new conversations
48 outcomes in all — one per recipe below.
Write a prompt that describes the product, lighting (like window light), objects and subtle imperfections such as lens distortion and camera shake. Submit it to get a static reference image, then ask the agent to add motion, hand actions and vertical format (9:16). Download the generated video and check that the movement looks human.
Route LLM automatically picks the most suitable large language model for your query by matching the task type to a model’s strengths. In ChatLLM, click the ‘Route LLM’ button, enter your prompt, press ‘Go’, and the system will show which model is used and give you the answer.
Abacus AI offers “mini” models (e.g., GPT‑5 Mini) that do not consume credits. When writing a prompt, open the model selector instead of Route LLM and choose a Mini model; the request will be processed without reducing your credit balance.
Yes, use the Tasks feature: click ‘New Task’, enter the prompt (e.g., “Weekly AI advancements summary”), set the schedule (such as every Sunday at 5 PM), enable email alerts with your address, and save. The task will run on the chosen interval and send the output via email.
Want a chat AI you can use from a browser or curl
The Supercomputer CLI can interpret a prompt to install and run an open‑source model (e.g., Qwen 2.5 0.5B) as a web service. It handles downloading, setting up the inference backend, and exposing a chat API automatically.
A web app is hidden on a VM
After a service is running inside the virtual machine, you can ask the LLM‑driven terminal to “activate” it, which updates the cloud instance’s HTTP routing and assigns a public endpoint automatically.
Need a live multiplayer 3D game server
By providing a natural‑language prompt, the platform can generate all necessary code (WebSocket backend, HTML/JS client) and launch a multiplayer arena that is instantly accessible via a public link.
In‑game AI chat costs too much
The platform lets you add custom HTTP endpoints that forward requests to a locally running model, enabling in‑game AI interactions without external API costs.
Unsure which model to use for a new AI task
Root LLM is Abacus AI's default large language model that automatically selects the best underlying model for your prompt, letting beginners skip manual model selection. It tailors responses to a wide range of tasks, making it ideal for first‑time users.
Abacus AI combines text, image, slide, and workflow tools in one interface, allowing you to turn a single concept into PDFs, Canva files, landing pages, and social media graphics without leaving the platform.
Need to handle many documents at once
The Deep Agent in Abacus AI is designed for heavy‑duty tasks like analyzing up to 16 documents at once, automating extraction, summarization, or data mining without manual prompting.
Need offline, faster access to your AI projects
Abacus AI offers a downloadable desktop client that syncs your projects and data, giving you offline‑ready access while keeping your information private.
Need a hero section that matches my design image
You describe the desired layout, colors, and effects in natural language and upload a reference image. The agent asks clarifying questions, then builds HTML/CSS/JS that matches the design, saving hours of manual coding.
Need to change the hero picture without touching code
By uploading a new image and giving a short textual instruction, the AI can locate specific components in the existing page and swap them out without touching code directly.
Typed letters disappear from the quiz input field
When a component misbehaves, you can describe the symptom and provide visual context; the agent patches the underlying code automatically.
Want a full SaaS landing page with courses, pricing and dashboard
You can request multiple high‑level features (course list, pricing, testimonials, dashboards) in one natural‑language description; the agent breaks it into tasks and builds each piece sequentially.
Need users to sign up, log in and see a personal dashboard
The platform includes a built‑in authentication service; by specifying fields (name, email, password) in your prompt, the agent provisions the backend and UI automatically.
Stuck on a homework question?
By describing the desired tutor capabilities (answer questions, summarize topics), the agent adds a chat UI and connects it to a selected LLM, enabling real‑time assistance.
I need a quiz on any subject
The agent can generate backend logic that takes a topic input, calls an LLM to produce questions, and renders them instantly, all from a single prompt.
Need a week‑by‑week learning roadmap
By providing input fields for goal, skill level, weekly hours, and duration, the agent builds logic that queries an LLM to output a structured study plan.
My AI calls are slow
Activating the ‘Supercomputer’ feature gives your project access to powerful GPU resources, allowing large models and faster inference without external hardware.
The platform runs built‑in tests after each generation step, catching errors early; you can view test results to ensure reliability.
Need an Instagram‑style product clip
By describing a natural scene with specific lighting, objects, and hand movement, the agent generates a believable social‑style clip. Detailing imperfections like smartphone lens distortion and slight camera shake prevents the output from looking overly synthetic.
Want to show an empty space becoming a cozy home office
The platform can act as a storyboard generator: after you give a high‑level concept, it asks clarifying questions, then outputs a scene‑by‑scene plan with duration, camera moves, overlays and music. Approving this plan ensures the final video follows a coherent narrative.
Using a single environment, you can generate an initial still, convert it to motion, add audio, upscale, and export—all without switching tools. This end‑to‑end workflow saves time and keeps assets consistent.
Want an AI desktop ready to use
The video walks through downloading the installer for Windows, macOS or Linux, granting admin privileges for the shell command, and signing in with an Abacus AI account. This establishes the core environment needed for all other features.
Need a written record of a meeting as it happens
The separate Listener app can record microphone audio and screen content, producing real‑time transcription that is saved as JSON or PDF. It also lets you chat with the transcript while it’s being generated.
While the Listener is running, you can type queries into the chat pane; the AI uses both the audio transcript and on‑screen context to answer, summarize, or extract tasks.
New files appear and need markdown conversion
Rules act like templates that tell the Deep Agent what to do when certain events occur (e.g., a new JSON transcript appears). They let you automate repetitive steps without re‑typing prompts each time.
Got transcript JSON and need Obsidian notes
The built‑in command‑line interface can read a rule and automatically scaffold code (Node.js script) that watches a folder, parses JSON transcripts, and writes Markdown files with proper titles, tags, and action items.
Need meeting summaries in your note vault
After the CLI creates markdown notes, you can drag them into your Obsidian vault. The notes include front‑matter with date, tags, and extracted tasks, making them instantly searchable.
Need a quick view of your meeting notes
By prompting the Deep Agent with a specification (e.g., show total meetings, pending tasks, tag cloud), it scaffolds a full‑stack desktop UI, installs dependencies, and writes code that reads markdown notes in real time.
My automations eat up AI credits
The video shows how selecting smaller models (e.g., Gwen‑3 coder) for simple tasks and reusing rules reduces token consumption, extending monthly credit limits.
Need a document‑upload chatbot with login and Stripe payments
By describing the desired features (file upload, backend storage, auth, Stripe) Deep Agent asks clarifying questions, plans architecture, searches for best practices, then writes front‑end, back‑end, database and deployment code automatically. It also generates documentation and a subdomain for instant hosting.
Error message shows up
After an error occurs, you can feed the exact error message to Deep Agent. It launches a virtual computer, reproduces the issue, inspects console logs, patches the code, runs tests and reports the fix, all while consuming credits proportionally.
Want to tweak AI‑generated code locally
The desktop version provides a VS Code‑like environment where you can download the project zip, open it, and chat with the agent while editing files. This lets you make targeted changes, test them instantly, and redeploy without re‑running the full autonomous build.
Not sure how many AI credits your prompt will need
Each example in the Deep Agent library shows an estimated credit cost. By selecting a similar template or entering your own prompt, you can see how many credits the system expects to consume before running, helping you budget usage.
Can’t tell which AI model fits my question
Route LLM analyzes your query and chooses the most suitable large language model, saving you from manually testing each provider. It works by matching task type (e.g., research, coding, image generation) to a model’s strengths.
Need consistent prompts and docs across chats
Projects let you store context (custom prompts, uploaded documents) that automatically apply to every chat inside the project, turning ChatLLM into a personal knowledge base and team hub.
Need a regular AI report emailed
Tasks turn any prompt into a repeatable job that can run daily, weekly, or on custom intervals, delivering results via chat or email while consuming credits predictably.
Need to keep credits at zero
ChatLLM offers “mini” versions of major models (GPT‑5 Mini, Gemini Flash 2.0, etc.) that do not consume monthly credits, ideal for simple tasks while preserving budget for heavy workloads.
I have a topic and need slides
Deep Agent combines web search, content synthesis, and design templates to produce a complete slide deck from a single high‑level instruction, dramatically reducing manual work.
Need a fresh account and org setup
You can quickly create an account on Abacus AI using Google, Apple, or Microsoft OAuth. After authentication you name your organization and add payment info to unlock the dashboard.
Need a picture in a specific size and style
The platform lets you pick any of its integrated diffusion models, set aspect ratio, guidance scale, seed and number of outputs, then generate images from a text prompt in seconds.
Want to add stuff to a generated image
After an image is created you can send it back to the platform with an edit instruction; the model re‑renders the picture adding or changing requested details while preserving style.
Want a slide deck from just a few notes
Using the built‑in PPT generator, you provide a topic or brief outline; Abacus AI builds slides, adds titles, bullet points and designs automatically.
Need a ready‑to‑launch landing page
The platform’s coding agent can write full HTML/CSS/JS files from natural language prompts and even suggest corrections, acting as an interactive IDE.
Need every request handled by the strongest AI
Max mode is a setting inside Abacus AI that forces every request to be sent to Claude Fable 5, the platform’s strongest frontier model. Using it gives you full root access so the model can plan, code, run, debug and deploy autonomously.
I want a 3D racing game but can’t code
By describing the desired gameplay (controls, visuals, soundtrack) in one paragraph, Claude Fable 5 creates a complete self‑contained web page that implements the game and publishes it to a public URL without any manual coding.
One English request runs nine AI agents to trade
A single English request can instruct Fable 5 to orchestrate nine cooperating agents that ingest market data, research news, generate strategies, back‑test, risk‑check and present live trade decisions—all visualized on a dashboard.
Want your own AI chat without relying on others
Fable 5 can download an open‑source large language model (e.g., Qwen 2.5), install it as a persistent system service, and automatically generate a web interface that streams responses token‑by‑token, giving you full ownership of the model.
Simple questions drain budget
Abacus AI lets you define routing rules that send hard‑coding requests to Claude Fable 5, debugging queries to Claude Opus 4.8, and simple syntax questions to GLM 5.2, optimizing cost while keeping performance where it matters.
The same set on /recipes, filtered by tool and role.
The clearest demo of the aggregator value proposition, aimed at non-developers.
Write a prompt that describes the product, lighting (like window light), objects and subtle imperfections such as lens distortion and camera shake. Submit it to get a static reference image, then ask the agent to add motion, hand actions and vertical format (9:16). Download the generated video and check that the movement looks human.
Route LLM automatically picks the most suitable large language model for your query by matching the task type to a model’s strengths. In ChatLLM, click the ‘Route LLM’ button, enter your prompt, press ‘Go’, and the system will show which model is used and give you the answer.
Abacus AI offers “mini” models (e.g., GPT‑5 Mini) that do not consume credits. When writing a prompt, open the model selector instead of Route LLM and choose a Mini model; the request will be processed without reducing your credit balance.
Yes, use the Tasks feature: click ‘New Task’, enter the prompt (e.g., “Weekly AI advancements summary”), set the schedule (such as every Sunday at 5 PM), enable email alerts with your address, and save. The task will run on the chosen interval and send the output via email.
promptvertical video (9:16)horizontal video (16:9)media planupscaleRoute LLMChatLLMcreditsmini modelsDeep AgentThinking Modehero sectionAsk, share, or report — over on the Heidelberg AI community forum.