Fireworks AI vs Together AI (2026)
Updated March 10, 2026
Overview
Fireworks AI is a generative AI inference platform that offers fast, cost-efficient model serving. The platform hosts popular open-source models and supports custom model deployments with optimized inference using proprietary serving technology. Fireworks specializes in compound AI systems with features like function calling, JSON mode, and grammar-guided generation that make it easy to build structured AI applications.
Together AI provides a cloud platform for running, fine-tuning, and training open-source AI models. The platform hosts popular models like Llama, Mistral, and Stable Diffusion with optimized inference that delivers fast generation at competitive prices. Together AI also offers GPU clusters for custom training jobs and has contributed to several breakthrough open-source AI research projects.
Key features
Core capabilities each platform advertises.
- Optimized inference for open-source models
- Function calling and JSON mode
- Fast iteration with model playground
- Competitive pricing
- Enterprise deployment options
- Inference and training cloud
- Open-source model hosting
- Serverless inference endpoints
- Fine-tuning as a service
- Competitive GPU pricing
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- 1-2 orders of magnitude cheaper than competitors
- Flexible deployment options (serverless/dedicated)
- Cost-effective fine-tuning capabilities
- NVIDIA Blackwell support for 10× cost reduction
Cons
- Pay-per-token pricing requires careful monitoring
- Costs vary significantly by model and usage
- Dedicated GPU hourly rates add up for 24/7 use
Pros
- Competitive pricing starting at USD 0.10 per million tokens
- 50 percent discounts on batch inference and prompt caching
- Strong backing from NVIDIA and Salesforce Ventures
- Flexible deployment with both serverless and dedicated options
Cons
- Focused on open-source models may limit access to proprietary models
- Per-minute billing for dedicated GPUs can be complex to predict
- Newer platform with less extensive documentation than established providers
- Pricing varies significantly by model making cost planning difficult
Fireworks AI or Together AI — which should you choose?
Choose Fireworks AI if you wantChoose if you want
- Production inference for open-source LLMs
- Fine-tuned model deployment
- Low-latency AI applications
- Compound AI systems
- Cost-optimized inference
Choose Together AI if you wantChoose if you want
- Hosting open-source LLMs in production
- Fine-tuning models on custom data
- Cost-efficient inference at scale
- Training custom models
- Rapid model prototyping
Compare the models
How Fireworks AI's and Together AI's models score on public benchmarks, and their live API status.
Compare Fireworks AI and Together AI on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.
Try Respan free