Fireworks AI vs Together AI
Side-by-side comparison of AI visibility scores, market position, and capabilities
Fireworks AI (ex-Meta PyTorch) reached ~$315M ARR at $4B valuation, serving 10K+ customers at 10T+ tokens/day on $327M raised; fastest open-model inference.
About
Fireworks AI is a high-performance AI inference platform founded in San Francisco by veterans of Meta's PyTorch team. The company was built to solve a critical gap in the AI infrastructure market: making large language model inference fast enough, cheap enough, and reliable enough for production-scale applications. Fireworks AI's founding team brings direct experience building the open-source deep learning framework that underlies much of the industry's AI work.\n\nThe platform offers access to a broad model library — including open-source models like Llama and Mixtral, as well as Fireworks' own optimized variants — served through a high-throughput API optimized for low latency and high concurrency. Key differentiators include custom model fine-tuning and serving, function calling, and structured output generation, along with pricing that can be dramatically lower than hyperscaler alternatives for high-volume workloads. Customers range from AI-native startups building inference-heavy products to enterprises migrating workloads from OpenAI or Anthropic to open models.\n\nFireworks AI has achieved approximately $315 million in annualized recurring revenue and processes over 10 trillion tokens per day — metrics that place it among the leading independent AI inference providers. The company reached a $4 billion valuation after raising $327 million in total funding. With 10,000+ customers, Fireworks AI is benefiting from the rapid growth of open-weight model adoption as organizations seek to reduce AI infrastructure costs while maintaining performance.
Open-source AI cloud. $300M ARR (Sep 2025). $3.3B valuation. $533M total raised. Backed by Salesforce, NVIDIA, Kleiner Perkins. Founded by ex-Stanford AI researchers.
About
Together AI was founded in 2022 with a mission to build the leading open-source AI cloud—a platform where developers and enterprises can train, fine-tune, and run inference on open-weight models without the constraints and costs of proprietary AI APIs. The company recognized early that as powerful open-weight models like Llama, Mistral, and FLUX proliferated, there was a massive opportunity to provide optimized infrastructure for running and customizing them. Together AI built a multi-cloud GPU platform with custom inference kernels and distributed training optimizations specifically engineered for open-source models.\n\nTogether AI's platform offers fine-tuning, inference, and training services across a curated library of leading open-weight models, with performance-optimized endpoints that often outperform what users can achieve running models on general-purpose cloud infrastructure. The company targets AI engineers, ML researchers, and enterprises that want flexibility—either for cost reasons, privacy requirements, or the need to customize model behavior through fine-tuning. Together's API design closely mirrors OpenAI's, making migration straightforward. Its pricing is consistently below proprietary model APIs for comparable capability tiers.\n\nTogether AI has achieved $300M in annualized revenue as of September 2025, growing to a $3.3B valuation with $533M in total funding. Investors include NVIDIA, Salesforce, and Kleiner Perkins—a combination that provides both strategic GPU supply chain relationships and enterprise go-to-market leverage. The open-source AI cloud market is a significant and growing segment as enterprises prioritize model flexibility and cost control alongside the maturation of open-weight models that increasingly compete with frontier proprietary models.
AI Visibility Head-to-Head
Key Details
Capabilities & Ecosystem
Capabilities
Also Compare
Track AI Visibility in Real Time
Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.