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AI · head to head

Atlas Cloud vs Keras

Atlas Cloud logo

Atlas Cloud

AI

One API for 500+ image, video, LLM and audio models

From
On request
Free plan
No
Full reviewWebsite
Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Keras has a free tier, so it costs nothing to try first.
  • Each has a real cost: Atlas Cloud not every model accepts every request format. Each model publishes its own supported_apis list, and Gemini models expose their full multimodal capability only on the native Gemini format, so 'change the base URL' does not hold for every model.; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: Atlas Cloud covers 500+ models, one API key, Keras covers Sequential and Functional API.
  • Prices and features above were last checked on 12 November 2026.

Where they differ

Only the attributes on which Atlas Cloud and Keras actually diverge.

Attributes where Atlas Cloud and Keras differ
AttributeAtlas CloudKeras
Starting priceOn requestFree
Pricing modelusage-basedopen-source
Free tierNoYes
Platformsweb, apiPython, Google Colab, Jupyter
CategoryAIMachine Learning
FoundedUnknown2015

Identical on both: user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Atlas Cloud

  • 500+ models, one API key
  • OpenAI-compatible LLM endpoint
  • Pay-as-you-go pricing
  • ComfyUI nodes
  • MCP server and CLI
  • Playground and Generator
  • Streaming, batch and webhooks
  • Coding Plan

Only in Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • TensorFlow
  • JAX
  • PyTorch

What people use each for

The jobs each tool is most often brought in to do.

Atlas Cloud

  • Adding AI image or video generation to an app without an account at each model providernot Keras
  • Switching an existing OpenAI, Anthropic or Gemini SDK integration to other models by changing the base URLnot Keras
  • Running hosted image and video models inside ComfyUI workflows without a local GPUnot Keras
  • Comparing image and video models side by side in a playground before committing to onenot Keras
  • Giving coding agents access to open-weight LLMs on a flat-rate plannot Keras

Keras

  • Machine learningnot Atlas Cloud
  • Data analysisnot Atlas Cloud
  • Model trainingnot Atlas Cloud
  • Predictive analyticsnot Atlas Cloud

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Atlas Cloud

  • Not every model accepts every request format. Each model publishes its own supported_apis list, and Gemini models expose their full multimodal capability only on the native Gemini format, so 'change the base URL' does not hold for every model.
  • No Anthropic models were listed when checked in November 2026: the provider directory showed Anthropic with 0 models, so the Anthropic Messages format is a compatibility layer for other models rather than access to Claude.
  • The model count is stated inconsistently across the site: the homepage title says 400+, the vendor says 500+ and the pricing page listed 550, which makes it hard to know what is available without checking the live list.
  • Billing is prepaid. When the balance runs out new API requests are rejected with 402 Payment Required unless auto top-up is enabled, which matters for production workloads.
  • Most models are third-party models resold through the platform, so pricing and availability follow upstream providers and change often; prices on the pricing page are shown against a separate official price and discounts vary by model.

Keras

  • Limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • Error messages can be vague and unhelpful, making debugging challenging
  • Smaller ecosystem and fewer pre-trained models than TensorFlow or PyTorch

Pricing, plan by plan

Atlas Cloud

On request
  • Pay-as-you-go$undefined/usage
    • Billed per image, per second of video or per token; no subscription
    • GPT Image 2 text-to-image: $0.004 per image
    • Seedream 5.5 generation or edit: $0.02 per image
  • Coding Plan$undefined/month
    • Monthly subscription with a monthly total and a weekly limit
    • Or 90-day pay-as-you-go credit packs with no weekly cap
    • Open-weight LLMs including GLM, MiniMax, Kimi and DeepSeek
  • Enterprise$undefined/custom
    • Volume API discounts
    • SLA options through sales
    • Dedicated infrastructure and private hosting on request

Keras

Free
  • Open SourceFree
    • High-level API
    • Pre-built layers
    • Model serialization

Which should you pick?

Choose Atlas Cloud if

  • You need 500+ models, one api key.
  • You work on web, api.
  • You also want openai-compatible llm endpoint.
Atlas Cloud review

Choose Keras if

  • You need sequential and functional api.
  • You want to start without paying.
  • You work on Python, Google Colab, Jupyter.
  • You also want pre-built neural network layers.
Keras review

Questions people ask

Is Atlas Cloud or Keras better?
Neither clearly leads. Atlas Cloud starts at On request and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Atlas Cloud or Keras?
Keras has a free tier; the other does not. Paid plans start at On request for Atlas Cloud and Free for Keras.
Does Atlas Cloud or Keras run on more platforms?
Atlas Cloud runs on web, api. Keras runs on Python, Google Colab, Jupyter.
Can I use Keras for free?
Yes. Keras has a free tier, so you can try it without paying. Atlas Cloud starts at On request.
What is Atlas Cloud best used for?
Atlas Cloud is most often used for adding ai image or video generation to an app without an account at each model provider, switching an existing openai, anthropic or gemini sdk integration to other models by changing the base url, running hosted image and video models inside comfyui workflows without a local gpu, comparing image and video models side by side in a playground before committing to one. Of those, adding ai image or video generation to an app without an account at each model provider and switching an existing openai, anthropic or gemini sdk integration to other models by changing the base url are not what Keras is typically brought in for.
What can Atlas Cloud do that Keras cannot?
Atlas Cloud covers 500+ models, one API key, OpenAI-compatible LLM endpoint, Pay-as-you-go pricing, ComfyUI nodes. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning.

Answered from the vendors’ own pages

Atlas Cloud: How is Atlas Cloud priced?

Pay as you go, per image, per second of video or per token, drawn from a prepaid balance with no subscription required. Examples in November 2026 were $0.004 per image for GPT Image 2 text-to-image, $0.02 per image for Seedream 5.5 and from $0.11 per second for Kling 4.0. Enterprise volume discounts are available through sales.

Source
Keras: What is Keras?

Keras is a high-level deep learning API built on top of TensorFlow that simplifies building and training neural networks. Keras 3 supports multiple backends including TensorFlow, PyTorch, and JAX, making it backend-agnostic.

Source
Atlas Cloud: Is the Atlas Cloud API OpenAI-compatible?

Yes. The base URL https://api.atlascloud.ai accepts OpenAI Chat Completions, Completions, Responses and Images requests, Anthropic Messages and Google Gemini requests with the same API key. Not every model supports every format; each model publishes a supported_apis list.

Source
Keras: What model architectures does Keras support?

Keras supports the Sequential model for linear stacks of layers, the Functional API for arbitrary graph architectures, and model subclassing for custom implementations. All approaches provide access to layers, optimizers, metrics, and callbacks.

Source
Atlas Cloud: Can I use Atlas Cloud in ComfyUI?

Yes. The Atlas Cloud ComfyUI nodes, installed from the AtlasCloudAI/atlascloud_comfyui GitHub repository, call hosted models from a ComfyUI graph. Generation runs on Atlas Cloud, so large video and image models work without a local GPU.

Source
Keras: Can Keras models run on TPUs and GPUs?

Yes, Keras models can run on TPU Pods or large GPU clusters, be exported to run in browsers or on mobile devices, and be served via web APIs.

Source
Atlas Cloud: What happens when my balance runs out?

New API requests are rejected with 402 Payment Required and you receive low-balance notifications. Service resumes as soon as you top up, and auto top-up can be enabled to avoid interruptions.

Source
Keras: Does Keras offer pre-trained models?

Yes, Keras provides pre-trained models through KerasHub and Keras Applications for common deep learning tasks like image classification, object detection, and NLP.

Source
Atlas Cloud: What is the Atlas Cloud Coding Plan?

A set of flat-rate subscriptions and 90-day credit packs for open-weight LLMs such as GLM, MiniMax, Kimi and DeepSeek, designed for coding agents including Claude Code, Codex and Cursor. Monthly subscriptions carry a weekly limit that resets every Monday.

Source
Keras: Who should use Keras?

Keras is ideal for beginners and rapid prototyping due to its simplicity and user-friendly interface. Advanced users and production deployments may benefit more from lower-level frameworks like TensorFlow or PyTorch for greater customization.

Source
Atlas Cloud: Where is Atlas Cloud based?

Its headquarters are at 1540 Broadway, New York, with offices in Silicon Valley and Calgary.

Source
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