About 16; min
Running open-source LLMs through an API saves you from managing GPUs. Together AI and Groq are two of the fastest-growing inference providers in 2026, each with a different approach. Together AI offers the widest model selection with competitive pricing. Groq built custom hardware (LPU) that delivers the fastest token generation speeds in the industry. Here’s how they compare for developers building AI applications.
Quick Comparison
| Feature | Together AI | Groq |
|---|---|---|
| Focus | Widest model selection | Fastest inference speed |
| Models Available | 200+ open-source models | ~15 curated models |
| Custom Hardware | NVIDIA GPUs | Groq LPU (custom chip) |
| Speed (Llama 70B) | ~80 tokens/sec | ~300 tokens/sec |
| Llama 3.1 70B Price | $0.88/M tokens | $0.59 in / $0.79 out per M |
| Free Tier | $5 credit | Free (rate-limited) |
| Fine-Tuning | Yes (serverless) | No |
| Embedding Models | Yes | No |
| Image Models | Yes (FLUX, SDXL) | No |
Together AI Overview
Together AI hosts 200+ open-source models covering text generation, code, embeddings, image generation, and vision. Llama 3.1 8B costs $0.18/M tokens, 70B costs $0.88/M, and 405B costs $5.00/M. Qwen, Mistral, DeepSeek, and Gemma models are all available. Serverless fine-tuning lets you customize any supported model with your data — upload a dataset, train, and deploy without managing infrastructure. Image generation through FLUX and Stable Diffusion XL is available at $0.006-0.05 per image. Embedding models (BAAI, Nomic) cost $0.008/M tokens. Together AI’s breadth makes it the default choice for teams that need access to multiple model families through a single API. The developer experience includes OpenAI-compatible endpoints, streaming, function calling, and JSON mode.
Groq Overview
Groq’s LPU (Language Processing Unit) is purpose-built hardware that generates tokens 3-10x faster than GPU-based inference. Llama 3.1 70B runs at approximately 300 tokens per second — responses that take 10 seconds elsewhere arrive in 2-3 seconds on Groq. Pricing: Llama 3.1 8B at $0.05 in / $0.08 out per M tokens, 70B at $0.59 / $0.79, DeepSeek R1 distilled models at $0.30 / $0.60. The free tier provides rate-limited access to all models — generous enough for development and prototyping. Groq supports a curated selection of approximately 15 models: Llama, Gemma, Mixtral, and DeepSeek variants. The model library is smaller than Together AI, but every model runs at exceptional speed. The API is OpenAI-compatible with streaming, tool use, and JSON mode.
Speed Comparison
| Model | Together AI (tokens/sec) | Groq (tokens/sec) |
|---|---|---|
| Llama 3.1 8B | ~150 t/s | ~750 t/s |
| Llama 3.1 70B | ~80 t/s | ~300 t/s |
| Mixtral 8x7B | ~100 t/s | ~500 t/s |
| Gemma 2 9B | ~130 t/s | ~600 t/s |
| Time to First Token | ~200-500ms | ~50-100ms |
Groq’s speed advantage is most noticeable in interactive applications — chatbots, autocomplete, and real-time agents where latency directly affects user experience. For batch processing, background jobs, and non-interactive workloads, Together AI’s speed is perfectly adequate and the wider model selection matters more.
Pricing Comparison
| Model | Together AI (per M tokens) | Groq (per M tokens) |
|---|---|---|
| Llama 3.1 8B | $0.18 | $0.05 in / $0.08 out |
| Llama 3.1 70B | $0.88 | $0.59 in / $0.79 out |
| Mixtral 8x7B | $0.60 | $0.24 in / $0.24 out |
| Gemma 2 9B | $0.30 | $0.20 in / $0.20 out |
| Fine-tuned models | Supported (extra cost) | Not available |
| Embedding models | $0.008/M tokens | Not available |
| Image generation | $0.006-0.05/image | Not available |
Beyond Text Generation
Together AI serves as a complete AI infrastructure platform. Fine-tune Llama or Mistral on your company’s data with serverless training — upload JSONL, pick a base model, and Together handles GPU allocation, training, and deployment. Generate images with FLUX or Stable Diffusion through the same API key. Create embeddings for RAG applications using models like nomic-embed or BAAI/bge. Run vision models that process images alongside text. This breadth means a single API key and billing account covers your entire AI stack.
Groq is laser-focused on fast text inference. No fine-tuning, no image generation, no embedding models. This focused approach is deliberate — Groq’s custom LPU hardware is designed specifically for autoregressive text generation, and everything else would dilute its core advantage. For teams that need the fastest possible text generation and handle other AI tasks through separate providers, Groq does one thing better than anyone else.
Who Should Pick What
Pick Together AI if:
- You need access to 200+ models through a single API
- Fine-tuning on custom data is part of your workflow
- Embeddings, image generation, or vision models are needed alongside text
- The widest model selection lets you benchmark and compare models easily
Pick Groq if:
- Response speed is your primary concern (chatbots, real-time agents)
- Time-to-first-token under 100ms matters for your user experience
- The models you need are in Groq’s curated library (Llama, Mixtral, Gemma)
- The free tier lets you develop and prototype without upfront costs
Together AI wins for most teams building AI applications. The combination of 200+ models, serverless fine-tuning, embeddings, and image generation through a single API covers the full development lifecycle. Groq earns runner-up for delivering inference speeds that no GPU-based provider can match — when your application needs sub-100ms time-to-first-token and 300+ tokens per second, Groq’s custom hardware creates an experience that feels instantaneous. Many teams use both: Groq for latency-sensitive production traffic, Together AI for fine-tuning, embeddings, and model experimentation.
FAQ
Is Groq really 3-10x faster than GPU inference?
Yes. Groq’s LPU architecture generates tokens significantly faster than NVIDIA GPU-based inference. Independent benchmarks consistently confirm 300+ tokens/sec for Llama 70B on Groq versus 60-100 tokens/sec on typical GPU providers.
Can I use both providers in the same application?
Yes. Both offer OpenAI-compatible APIs. Use a router like OpenRouter or build simple logic that sends latency-sensitive requests to Groq and batch/training tasks to Together AI.
Which is cheaper for high-volume inference?
Groq is generally cheaper per token for the models it supports. Together AI offers more models at varying price points. For Llama 8B specifically, Groq at $0.05/M is 3.6x cheaper than Together at $0.18/M. For models Groq doesn’t support, Together AI is the only option.
Does Groq support function calling?
Yes. Groq’s API supports tool use (function calling) and JSON mode on compatible models. The implementation follows the OpenAI function calling format, making migration from OpenAI straightforward.
What about latency spikes on Groq?
During peak usage periods, Groq can experience higher latency as demand exceeds available LPU capacity. Together AI’s larger GPU fleet handles traffic spikes more consistently. For production applications requiring guaranteed low latency, Groq’s enterprise tier offers dedicated capacity with SLA commitments. The free tier and standard plans are best-effort and may see variable performance during high-demand periods.
