Software · head to head
Anyscale vs Together AI

Anyscale
Software
Platform for scaling AI and data workloads on Ray, built by Ray's creators
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Anyscale pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.; Together AI fine tuning carries a minimum charge of $4.00 per job regardless of dataset size
- They diverge on capability: Anyscale covers Distributed model training, Together AI covers Open-source models.
Where they differ
Only the attributes on which Anyscale and Together AI actually diverge.
| Attribute | Anyscale | Together AI |
|---|---|---|
| Platforms | web, api | Api, Cloud |
| Founded | Unknown | 2022 |
Identical on both: starting price (Free), pricing model (usage-based), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Anyscale
- Distributed model training
- Multimodal data curation
- Batch embedding generation
- Multi-cloud orchestration
- Governance and security
- Observability
- Bring-your-own-cloud deployment
- Elastic GPU allocation
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.
Anyscale
- Training large models on distributed GPU clustersnot Together AI
- Running batch inference and embedding jobsnot Together AI
- Preparing multimodal datasets at scalenot Together AI
- Post-training LLMs with reinforcement learning frameworksnot Together AI
Together AI
- Serverless inference against open source chat, vision, embedding, image and video modelsnot Anyscale
- Renting dedicated single tenant H100, H200 or B200 GPU clusters by the hournot Anyscale
- Fine tuning open weight models on a per token basisnot Anyscale
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Anyscale
- Pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.
- Built around Ray, so teams not already using Ray face a steeper adoption curve than single-purpose inference APIs.
- No published fixed-fee subscription tier; all listed pricing is usage-based on-demand compute.
Together AI
- Fine tuning carries a minimum charge of $4.00 per job regardless of dataset size
- Reserved GPU commitments beyond 180 days are priced by contacting sales with no published rate
- Volume and enterprise discounts are quote only with no published threshold
- Reserved dedicated inference pricing is contact sales while only on demand rates of $5.49 to $8.99 per GPU hour are published
Pricing, plan by plan
Anyscale
Free- Pay-as-you-go$undefined/mo
- CPU only from $0.0135/hr
- NVIDIA T4 $0.5682/hr
- NVIDIA L4 $0.9542/hr
- Committed contract$undefined/mo
- Volume discounts
- Use of existing GPU reservations
Together AI
Free- FreeFree
- $5 credits
- API access
- Pay-per-use$0.2/per-million-tokens
- All models
- Fine-tuning
Which should you pick?
Choose Anyscale if
- You need distributed model training.
- You want to start without paying.
- You work on web, api.
- You also want multimodal data curation.
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 Anyscale or Together AI better?
- Neither clearly leads. Anyscale 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, Anyscale or Together AI?
- Anyscale starts at Free and Together AI at Free.
- Does Anyscale or Together AI run on more platforms?
- Anyscale runs on web, api. Together AI runs on Api, Cloud.
- Can I use Anyscale for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Anyscale best used for?
- Anyscale is most often used for training large models on distributed gpu clusters, running batch inference and embedding jobs, preparing multimodal datasets at scale, post-training llms with reinforcement learning frameworks. Of those, training large models on distributed gpu clusters and running batch inference and embedding jobs are not what Together AI is typically brought in for.
- What can Anyscale do that Together AI cannot?
- Anyscale covers Distributed model training, Multimodal data curation, Batch embedding generation, Multi-cloud orchestration. Together AI covers Open-source models, Fine-tuning, Fast inference, Embeddings.
Answered from the vendors’ own pages
Anyscale: How much does Anyscale cost?
Anyscale bills on a pay-as-you-go basis: CPU compute starts at $0.0135/hr, NVIDIA T4 at $0.5682/hr, and NVIDIA A100 at $4.9591/hr, with committed contracts offering volume discounts for larger workloads.
SourceAnyscale: Is there a free trial or credit?
New users receive $100 in Anyscale credits to explore the platform, which can be applied toward starter templates and on-demand compute usage.
SourceAnyscale: How is usage billed?
Hosted usage is billed hourly per compute instance type and invoiced monthly by credit card; bring-your-own-cloud usage is invoiced through Anyscale or the customer's cloud marketplace account.
SourceAnyscale: What support is included?
Hosted plans include business-hours support with up to 5 case submissions, while bring-your-own-cloud deployments get 24x7 enterprise SLAs and unlimited case submissions.
SourceRelated pages
More on Together AI
Keep looking
Other head to heads
- Anyscale vs Grafana Cloud
- Anyscale vs Neon
- Anyscale vs DigitalOcean
- Anyscale vs AWS (Amazon Web Services)
- Anyscale vs Lambda (AWS Serverless)
- Anyscale vs Fireworks AI
- Anyscale vs DeepInfra
- Anyscale vs Deno Deploy
- Anyscale vs Heroku
- Anyscale vs Hetzner Cloud
- Anyscale vs Linode
- Anyscale vs Packer
- Anyscale vs Pulumi
- Anyscale vs Render
- Anyscale vs Upstash
- Anyscale vs Vagrant
- Anyscale vs Vultr
- Anyscale vs Akamai
- Anyscale vs Pika
- Anyscale vs Anthropic API
- Anyscale vs D-ID
- Anyscale vs Fathom
- Anyscale vs Stable Diffusion
- Anyscale vs Perplexity
- Anyscale vs Arize AI
- Anyscale vs Black Forest Labs
- Anyscale vs Cartesia
- Anyscale vs Deepgram
- Anyscale vs Helicone
- Anyscale vs Ideogram
- Anyscale vs Jasper
- Anyscale vs PromptLayer
- Anyscale vs Resemble AI
- Anyscale vs AI21 Labs
- Anyscale vs Copy.ai
- Anyscale vs HeyGen
- Together AI vs Grafana Cloud
- Together AI vs Neon
- Together AI vs DigitalOcean
- Together AI vs AWS (Amazon Web Services)
- Together AI vs Lambda (AWS Serverless)
- Together AI vs Fireworks AI
- Together AI vs DeepInfra
- Together AI vs Deno Deploy
- Together AI vs Heroku
- Together AI vs Hetzner Cloud
- Together AI vs Linode
- Together AI vs Packer
- Together AI vs Pulumi
- Together AI vs Render
- Together AI vs Upstash
- Together AI vs Vagrant
- Together AI vs Vultr
- Together AI vs Akamai
- Together AI vs Pika
- Together AI vs Anthropic API
- Together AI vs D-ID
- Together AI vs Fathom
- Together AI vs Stable Diffusion
- Together AI vs Perplexity
- Together AI vs Arize AI
- Together AI vs Black Forest Labs
- Together AI vs Cartesia
- Together AI vs Deepgram
- Together AI vs Helicone
- Together AI vs Ideogram
- Together AI vs Jasper
- Together AI vs PromptLayer
- Together AI vs Resemble AI
- Together AI vs AI21 Labs
- Together AI vs Copy.ai
- Together AI vs HeyGen

