Fireworks AI vs StepFun: Token Pricing, Speed & Intelligence
Full comparison of Fireworks AI and StepFun — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
StepFun
Step-5 — Chinese frontier LLM with strong multimodal and reasoning capability
StepFun is a Chinese AI startup developing the Step model series. Step-5 Preview is the frontier tier, competing with top Chinese and international models on reasoning and multimodal benchmarks. Step-3.7 Flash is the efficient tier for cost-sensitive workloads. StepFun is backed by Tencent and focuses on enterprise and developer API access.
Key metric comparison
—
—
—
—
—
—
—
—
—
—
—
—
Live token pricing
Strengths and weaknesses
Fireworks AI
StepFun
Key differentiators
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.
Step-5 is StepFun's frontier reasoning model with multimodal capability, backed by Tencent — positioned as a competitive alternative to Qwen and ERNIE for Chinese enterprise workloads.
Frequently asked questions
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.
StepFun FAQs
What is StepFun?
StepFun is a Chinese AI startup backed by Tencent, developing the Step model series. Step-5 Preview is the frontier tier and Step-3.7 Flash is the efficient tier, both available via the StepFun API.
How much does the StepFun API cost?
Step-5 Preview is $1.00/$2.70 per 1M input/output tokens. Step-3.7 Flash is $0.20/$1.15 per 1M tokens. See platform.stepfun.com/docs/pricing for current rates.
Does Step-5 support multimodal input?
Yes. Step-5 Preview supports text, image, and video understanding in a single API call, making it suitable for multimodal enterprise applications.
Provider resources
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.
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.
StepFun — Step-5 — Chinese frontier LLM with strong multimodal and reasoning capability
StepFun is a Chinese AI startup developing the Step model series. Step-5 Preview is the frontier tier, competing with top Chinese and international models on reasoning and multimodal benchmarks. Step-3.7 Flash is the efficient tier for cost-sensitive workloads. StepFun is backed by Tencent and focuses on enterprise and developer API access.
Step-5 is StepFun's frontier reasoning model with multimodal capability, backed by Tencent — positioned as a competitive alternative to Qwen and ERNIE for Chinese enterprise workloads.
Key strengths compared
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
StepFun
- Step-5 Preview is competitive with top Chinese frontier models on reasoning benchmarks
- Step-3.7 Flash at $0.20/$1.15 per 1M tokens offers strong value for efficient inference
- Multimodal capability on Step-5 (text, image, video understanding)
- Newer entrant — smaller track record than established frontier labs
- Documentation and support primarily in Chinese
Key weaknesses compared
Fireworks AI
- Slightly higher pricing than budget alternatives
- Smaller model catalog than Together AI
- Serverless Training is newer and less battle-tested
StepFun
- Newer entrant — smaller track record than established frontier labs
- Documentation and support primarily in Chinese
- Limited international ecosystem and third-party integrations
Provider category context
Fireworks AI is a inference api, founded in 2022. StepFun is a frontier lab, founded in 2023. Fireworks AI as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. StepFun as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Fireworks AI if you need 320+ tokens/sec on llama 3.3 70b — fast gpu inference. Choose StepFun if you need Chinese NLP. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.