Fireworks AIvs
DeepInfra


DeepInfra: Both offer pay-per-token hosting of open-source models with competitive pricing.

Fast inference and fine-tuning platform for open and custom AI models
As of 29 August 2026, Fireworks AI has a free plan and paid plans start at $0.07/month. Platform to train, fine-tune, and deploy AI models with serverless, on-demand, and reserved GPU inference options. Softwr lists it under Cloud. Fireworks AI is available on Web, API.
Overview
Fireworks AI is an AI infrastructure platform for training, fine-tuning, and deploying machine learning models, built by former PyTorch engineers. It hosts 30+ optimized open and closed models, including DeepSeek, Qwen, and Kimi, with context windows exceeding 1 million tokens. Deployment options include serverless pay-per-token inference, on-demand dedicated instances, and reserved capacity, all compatible with OpenAI and Anthropic API formats. Its Nexus product routes coding-assistant requests across models to cut AI coding costs, and customers include Cursor, Vercel, Notion, and Sourcegraph.
The honest half
Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Fireworks AI.
Cross-shopped
Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.


DeepInfra: Both offer pay-per-token hosting of open-source models with competitive pricing.


Anyscale: Both provide training and inference infrastructure for large-scale AI workloads.
Pricing
Taken from the vendor's own pricing page. Prices move, so check before you buy.
Serverless
On request
On-Demand
$7 /mo
Reserved
On request
Capabilities
Serverless inference
Pay-per-token access to 30+ optimized open and closed models
On-demand and reserved deployments
Dedicated GPU instances with multi-region support and priority hardware
Managed fine-tuning
LoRA and full-parameter SFT/DPO training priced per token
OpenAI/Anthropic API compatibility
Drop-in replacement for existing model API integrations
Nexus router
Intelligently routes AI coding requests to cut costs by 50-75%
Long context models
Supports context windows beyond 1 million tokens
Answered, with sources
Each answer names the page it came from, so you can check it rather than take our word for it.
Serverless inference uses postpaid, pay-per-token billing across Standard, Priority, and Fast tiers, with rates from $0.07 to $1.74 per million tokens depending on model.
SourceNew accounts receive $1 in free credit to try serverless inference before adding a payment method.
SourceDedicated on-demand instances range from $7-8/hour for H100/H200 GPUs up to $18-20/hour for GB300, billed per GPU second with no start-up surcharge.
SourceManaged training is billed per 1 million training tokens for supervised or preference tuning, while reinforcement tuning is billed per GPU hour.
SourceYes, region-restricted on-demand deployments carry a 1.5x premium over standard regional pricing.
SourceKeep looking
Platform for scaling AI and data workloads on Ray, built by Ray's creators
Serverless GPU infrastructure for real-time AI inference and applications
Serverless GPU computing with sub-second cold starts and multi-cloud support
Build and deploy serverless applications on AWS Lambda
High-performance serverless infrastructure for APIs, inference, and databases
Cloud cost estimates in pull requests, with governance in the paid tier
Open source distributed block storage for Kubernetes, incubating at the CNCF
Softwr does not host reviews and shows no star rating for Fireworks AI, because a rating we did not collect is not ours to publish. What is here is the pricing and platform detail from the vendor’s own pages, limitations we could state concretely, and alternatives a reviewer confirmed people weigh against it. Tell us if any of it is wrong.
What people switch to, and what they give up
Every tier, and where the cost actually lands
Put it head to head with anything we hold
Its rating, and an embed for your own site
Open source distributed block storage for Kubernetes, incubating at the CNCF
Open source, no licence feeDeployment platform that provisions and operates Kubernetes inside your own cloud account
quoteCloud cost estimates in pull requests, with governance in the paid tier
Free open source tool, then per month by run volumeFree self-hosted platform built on Docker Swarm with a dashboard and automatic certificates
Open source, no licence feeOpen source self-hosted platform that deploys applications and databases to servers you already own
Open source, no licence fee