Baseten vs Fireworks AI: Token Pricing, Speed & Intelligence
Full comparison of Baseten and Fireworks AI — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Baseten
Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection
Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.
Fireworks AI
H100/H200/B200/B300/GB300 on-demand — Serverless Training API, Forge 2026 conference
Fireworks AI provides optimised inference for open-weight models with a focus on production reliability and low latency. On-demand GPU compute (H100, H200, B200, B300, GB300) is available alongside serverless inference. The Serverless Training API enables fine-tuning for GLM 5.3, Qwen 3.8 27B, Kimi K3, DeepSeek V4 Flash, and Muse Glimmer 30B without managing GPU infrastructure. Fireworks hosted its inaugural Forge 2026 conference.
Key metric comparison
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$0.10
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$0.10
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320 tok/s
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180ms
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82/100
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131K
Live token pricing
No live pricing data available.
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| Model | Input | Output |
|---|---|---|
| accounts/fireworks/models/llama-v3p3-70b-instruct | $0.90EST Jul 2026 | $0.90 |
| accounts/fireworks/models/deepseek-r1 | $3.00EST Jul 2026 | $8.00 |
| llama-v3p1-8b-instruct | $0.10EST Jul 2026 | $0.10 |
| llama-v3p1-70b-instruct | $0.90EST Jul 2026 | $0.90 |
| deepseek-v3 | $0.90EST Jul 2026 | $0.90 |
Strengths and weaknesses
Baseten
Fireworks AI
Key differentiators
The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.
Production-grade reliability with the latest GPU hardware (B300/GB300) and a Serverless Training API — the most complete platform for open-weight model inference and fine-tuning.
Frequently asked questions
Baseten FAQs
What is Baseten?
Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.
How does Baseten differ from Together AI or Replicate?
Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.
What GPUs does Baseten support?
Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.
Fireworks AI FAQs
What GPU hardware does Fireworks AI offer?
Fireworks AI offers on-demand H100, H200, B200, B300, and GB300 GPU instances for dedicated deployments, alongside their serverless inference API for pay-per-token access.
What is the Fireworks Serverless Training API?
Fireworks AI's Serverless Training API lets you fine-tune open-weight models without managing GPU infrastructure. Upload your training data, run fine-tuning jobs, and deploy the resulting model via their inference API.
What models does Fireworks AI offer?
Fireworks AI hosts Llama 3.3 70B, DeepSeek R1, Mixtral, and other popular open-weight models. They focus on production-ready models with optimised inference rather than the broadest possible catalog.
Provider resources
Key strengths compared
Baseten
- Full control over model serving: custom preprocessing, postprocessing, and business logic
- Bring your own weights — deploy any HuggingFace model or custom fine-tune
- GPU selection: H100, A100, A10G, T4 with per-second billing
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
Fireworks AI
- 320+ tokens/sec on Llama 3.3 70B — fast GPU inference
- H100/H200/B200/B300/GB300 on-demand GPU access
- Serverless Training API for fine-tuning without infrastructure
- Slightly higher pricing than budget alternatives
- Smaller model catalog than Together AI
Key weaknesses compared
Baseten
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
- Pricing is higher than shared inference APIs for low-volume workloads
Fireworks AI
- Slightly higher pricing than budget alternatives
- Smaller model catalog than Together AI
- Serverless Training is newer and less battle-tested
Provider category context
Baseten is a inference api, founded in 2019. Fireworks AI is a inference api, founded in 2022. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Baseten and Fireworks AI host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.