Groq vs Together AI
Side-by-side comparison of features, pricing, and ratings
Groq or Together AI: which should you choose?
| Dimension | Groq | Together AI |
|---|---|---|
| Pricing | Freemium, linear pricing, batch 50% cheaper | Freemium, per-token serverless, dedicated plans |
| Core focus | Ultra-low-latency LPU inference for real-time apps | Full-stack AI cloud: inference, fine-tuning, pre-training |
| Models | Open-source incl. GPT-OSS, Kimi K2, day-zero access | 100+ open-source, incl. DeepSeek V4 Pro, Llama 4 Maverick, Qwen3.7-Max |
| Key differentiator | Sub-200ms latency, Compound AI systems, Orpheus TTS | Batch inference up to 30B tokens, fine-tuning with FlashAttention-4 |
| Integrations | OpenAI SDK, MCP, BrowserBase, Stripe, Tavily | CodeSandbox, Hugging Face, LangChain, Weights & Biases |
| Best for | Real-time agents, voice AI, low-latency apps | Production coding agents, batch processing, fine-tuning |
If you need real-time responsiveness under 200ms — chatbots, voice assistants, agentic systems — Groq's LPU is the clear winner, with day-zero model access and a dead-simple switch from OpenAI. But if your workloads are batch-heavy, require fine-tuning, or need massive async token throughput (up to 30B tokens), Together AI's full-stack cloud — from sandbox to AI Factory — offers more flexibility and training depth. Choose Groq for speed, Together AI for scale and customization.
Groq delivers fast LLM inference on its own LPU and LPX silicon through an OpenAI-compatible API.
Visit WebsiteTogether AI is an AI cloud for open-weight models: per-token inference APIs with GPU clusters underneath.
Visit WebsiteWho should pick Groq, and who should pick Together AI?
- Solo founder building a real-time chatbotPick: Groq
Groq's sub-200ms latency and easy switch from OpenAI SDK make it ideal for quick, responsive MVPs without infrastructure complexity.
- Enterprise running batch inference on massive datasetsPick: Together AI
Together AI's batch inference scales to 30B tokens per model, handling async heavy loads efficiently with per-token pricing.
- ML researcher fine-tuning open-source modelsPick: Together AI
Together AI offers fine-tuning with FlashAttention-4 and ATLAS kernels, plus pre-training support—Groq only provides inference.
- Voice AI developer needing instant TTSPick: Groq
Groq's Orpheus TTS delivers 100+ chars/s for real-time speech, paired with low-latency inference.
- Startup scaling from prototype to production with custom infrastructurePick: Together AI
Together AI's sandbox via CodeSandbox and AI Factory custom infrastructure let you grow without migration, unlike Groq's fixed LPU setup.
Frequently Asked Questions
Groq vs Together AI: which should you choose?
If you need real-time responsiveness under 200ms — chatbots, voice assistants, agentic systems — Groq's LPU is the clear winner, with day-zero model access and a dead-simple switch from OpenAI. But if your workloads are batch-heavy, require fine-tuning, or need massive async token throughput (up to 30B tokens), Together AI's full-stack cloud — from sandbox to AI Factory — offers more flexibility and training depth. Choose Groq for speed, Together AI for scale and customization.
Can I use Groq for fine-tuning models?
No, Groq's features listed are inference-focused only; fine-tuning isn't mentioned in its offering. For fine-tuning, Together AI is the go-to.
Which platform supports the latest open-source models first?
Groq claims day-zero support for new models like GPT-OSS and Kimi K2, as shown in its news. Together AI also hosts many models but doesn't stress day-zero in its description.
Does Together AI offer a low-latency option?
Together AI doesn't claim sub-200ms latency like Groq; it emphasizes high TPS and throughput. For real-time critical apps, Groq is the safer bet.
Is there a free tier on both?
Yes, both are freemium, but the free tier limits are not detailed here. Expect trial credits or limited usage.
Which is easier for a developer familiar with OpenAI's API?
Groq's OpenAI-compatible API can be switched in two lines of code, making it the quickest transition. Together AI also integrates with OpenAI SDK but may require more setup.
Can Groq handle heavy batch processing?
Groq offers a Batch API with 50% lower cost, but its focus is on latency, not massive throughput like Together AI's 30B token scaling. For extreme batch volumes, Together AI is stronger.
What about voice and multi-modal support?
Groq has Orpheus TTS and Whisper ASR. Together AI mentions container inference for video, audio, and image models, but no specific TTS/ASR products are listed.
Which platform is better for agentic workflows?
Groq's Compound AI systems integrate web search, code execution, and browser automation, plus MCP server support, making it more agent-ready. Together AI lacks such bundled agent tools.
What else are Groq and Together AI compared with?
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Where can you read more about Groq and Together AI?
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