Fireworks AI vs Together AI: Token Pricing, Speed & Intelligence
Full comparison of Fireworks AI and Together AI — 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.
Together AI
MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — plus GB200/B200 GPU clusters
Together AI offers hosted inference for open-weight models, GPU clusters, provisioned throughput and fine-tuning. Compare listed rates and check the provider for current models, availability and terms.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Fireworks AI
Together AI
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.
An open-weight model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — with GPU clusters (GB200/B200), Provisioned Throughput, and a Serverless Training API.
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.
Together AI FAQs
What new models did Together AI add in 2026?
Together AI expanded its catalog with MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro 0813, gpt-oss-120B, Muse Glimmer 30B, and the full Qwen3.x family. Check api.together.ai/models for current pricing.
How much does Together AI cost?
Together AI uses per-token pricing across its model catalog. Check api.together.ai/models for current rates on MiniMax M3, DeepSeek V4 Pro, GLM-5.3, Llama 3.3 70B, and other models.
Does Together AI offer GPU compute?
Yes. Together AI offers GPU clusters with H100, H200, B200, and GB200/GB300 NVL72 (contact sales). Check together.ai/pricing for current GPU compute rates.
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.
Together AI — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — plus GB200/B200 GPU clusters
Together AI offers hosted inference for open-weight models, GPU clusters, provisioned throughput and fine-tuning. Compare listed rates and check the provider for current models, availability and terms.
An open-weight model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B — with GPU clusters (GB200/B200), Provisioned Throughput, and a Serverless Training API.
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
Together AI
- Open-model catalog — MiniMax M3, Kimi K3, GLM-5.3, DeepSeek V4 Pro, gpt-oss-120B, Qwen3.x, Llama 4
- GB200/B200/H200/H100 GPU clusters with preemptible and reserved pricing
- Provisioned Throughput (PTUs) for SLA-backed capacity
- No proprietary frontier models
- Throughput lower than Groq/Cerebras for speed-critical apps
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
Together AI
- No proprietary frontier models
- Throughput lower than Groq/Cerebras for speed-critical apps
- Fine-tuning adds complexity vs. pure inference providers
Provider category context
Fireworks AI is a inference api, founded in 2022. Together 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 Fireworks AI and Together 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.