Machine Learning · head to head
Keras vs Together AI
The short version
- Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Together AI free tier limits not clearly specified in pricing documentation
- They diverge on capability: Keras covers Sequential and Functional API, Together AI covers Open-source models.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Keras and Together AI actually diverge.
| Attribute | Keras | Together AI |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Python, Google Colab, Jupyter | Api, Cloud |
| Category | Machine Learning | AI |
| Founded | 2015 | 2022 |
Identical on both: starting price (Free), free tier (Yes), 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 Keras
- Sequential and Functional API
- Pre-built neural network layers
- Model training and evaluation
- Transfer learning
- Model serialization
- TensorFlow
- JAX
- PyTorch
Only in Together AI
- Open-source models
- Fine-tuning
- Fast inference
- Embeddings
- REST API
- Python SDK
- OpenAI compatible
- Api support
What people use each for
The jobs each tool is most often brought in to do.
Keras
- Machine learningnot Together AI
- Data analysisnot Together AI
- Model trainingnot Together AI
- Predictive analyticsnot Together AI
Together AI
- LLM inference for production AI applicationsnot Keras
- Content generation at scalenot Keras
- Code execution and embeddingsnot Keras
- Model fine-tuning and trainingnot Keras
- Startup and enterprise AI deploymentnot Keras
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Together AI
- Free tier limits not clearly specified in pricing documentation
- Pricing varies significantly by model and use case
- Requires account setup for production access
- Batch API discounts apply only to non-urgent workloads
Pricing, plan by plan
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
Together AI
Free- Serverless Inference$0.03/1M input tokens
- Chat and Vision models
- Image generation
- Video generation
- Provisioned Throughput$21600/month
- Up to 83% savings vs commercial alternatives
- Reserved capacity
- Guaranteed throughput
- Dedicated Inference$5.49/hour
- H100 GPU instance
- Single-tenant deployment
- No resource sharing
- GPU Clusters$3.99/GPU-hour
- On-demand capacity
- Volume discounts available
- Reserved options with up to 35% savings
Which should you pick?
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.
Choose Together AI if
- You need open-source models.
- You want to start without paying.
- You work on Api, Cloud.
- You also want fine-tuning.
Questions people ask
- Is Keras or Together AI better?
- Neither clearly leads. Keras starts at Free and Together AI at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Keras or Together AI?
- Keras starts at Free and Together AI at Free.
- Does Keras or Together AI run on more platforms?
- Keras runs on Python, Google Colab, Jupyter. Together AI runs on Api, Cloud.
- Can I use Keras for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Keras best used for?
- Keras is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Together AI is typically brought in for.
- What can Keras do that Together AI cannot?
- Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Together AI covers Open-source models, Fine-tuning, Fast inference, Embeddings.
Answered from the vendors’ own pages
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.
SourceTogether AI: Does Together AI offer a free tier?
Yes, Together AI advertises 'Start for free, scale on demand,' but specific free tier usage limits are not detailed on the pricing page.
SourceKeras: 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.
SourceTogether AI: What are Together AI's highest model prices?
Serverless inference pricing ranges from free for base models up to $4.40 per 1M input tokens for premium models. Video generation costs $0.14 to $3.20 per video depending on resolution.
SourceKeras: 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.
SourceTogether AI: How much can I save with Provisioned Throughput?
Together AI offers up to 83% savings compared to commercial alternatives when using their Provisioned Throughput option with reserved capacity.
SourceKeras: 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.
SourceTogether AI: What is Together AI's fine-tuning pricing?
Standard fine-tuning costs $0.48 to $2.90 per 1M tokens depending on model size, with a minimum charge of $4.00 per job.
SourceKeras: 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.
SourceRelated pages
More on Together AI
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