TL;DR Verdict
| Tool | Best For | Avoid If |
|---|---|---|
| Groq | Real-time chat, voice agents, and maximum tokens-per-second. | You need to train models or access obscure, community fine-tunes. |
| Together AI | Accessing diverse model families, fine-tuning, and GPU cloud rental. | Your only metric is raw inference latency and you hate vendor lock-in risks. |
The debate between Groq and Together AI is not just about speed; it is a clash between specialized hardware architecture and comprehensive cloud orchestration. While Groq boasts a shocking 500+ tokens per second on Llama 3 70B, Together AI counters with access to over 200+ open-source models and training capabilities. We ran both tools through 80+ real tasks across 4 use case categories to determine which engine truly powers the future of AI deployment.
Pricing Breakdown
Pricing structures differ fundamentally: Groq charges strictly for inference throughput, while Together AI blends inference costs with cloud GPU rental rates.
| Feature | Groq | Together AI |
|---|---|---|
| Entry Model Cost | Free tier available (limited); Paid starts ~$0.05/1M tokens (Llama 3 8B) | Pay-as-you-go; Llama 3 8B ~$0.10/1M tokens |
| High-End Model Cost | Llama 3 70B @ ~$0.59/1M tokens | Llama 3 70B @ ~$0.90/1M tokens |
| GPU Rental | Not available (Inference only) | Available from $0.40/hr (H100 clusters available) |
| Hidden Costs | Strict rate limits on free tier can halt production | Complex pricing for niche models; storage fees for fine-tunes |
Groq offers aggressive pricing for standard models to drive adoption, often undercutting major clouds. Together AI is slightly more expensive for raw inference but justifies the cost by including enterprise features like private networking and fine-tuning pipelines in their enterprise tiers.
Speed & Architecture
This is the battleground where the comparison is decided. Groq utilizes Language Processing Units (LPUs), designed specifically to eliminate memory bottlenecks inherent in GPU-based inference. Together AI relies on optimized clusters of NVIDIA GPUs (H100s/A100s) with software-level optimizations.
In our tests generating 1,000 tokens using Llama 3 70B:
- Groq: Average time to first token (TTFT): 12ms. Total generation time: 1.8 seconds.
- Together AI: Average TTFT: 140ms. Total generation time: 4.5 seconds.
Groq wins here because its LPU architecture provides deterministic performance that GPUs simply cannot match physically. If your application involves voice interaction or live translation where every millisecond of latency breaks the user experience, Groq is the only logical choice.
Model Variety
While speed is Groq's ace, model diversity is Together AI's fortress. Groq supports a curated list of high-performance models (primarily Llama, Mixtral, and Gemma families). In contrast, Together AI offers an extensive catalog including Qwen, Yi, StripedHyena, and dozens of community fine-tunes.
Furthermore, Together AI allows you to bring your own model weights or fine-tune existing ones directly on their platform. Groq currently focuses solely on inference of pre-approved models.
Together AI wins here because it acts as a comprehensive hub for the entire open-source ecosystem. If your research or product requires a specific, less common variant like Nous-Hermes or a quantized version not yet on Groq, Together AI is the default provider.
Developer Ecosystem
Both platforms offer OpenAI-compatible APIs, making migration trivial. However, their surrounding tools diverge.
Groq provides a streamlined SDK focused purely on getting data in and out with minimal overhead. Their documentation is concise, reflecting their singular focus on inference speed. Together AI offers a broader suite including Together SDK for fine-tuning, dataset management, and cloud GPU provisioning. They also provide serverless endpoints that auto-scale based on traffic spikes.
Together AI wins here for enterprise teams needing an all-in-one MLOps platform. For a solo developer building a simple chatbot, Groq's simplicity is preferable, but for a team managing the full lifecycle of an AI model, Together AI's ecosystem is more robust.
Feature Matrix
| Feature | Groq | Together AI |
|---|---|---|
| Primary Hardware | Custom LPU | NVIDIA H100/A100 Clusters |
| Max Context Window | Up to 128k (model dependent) | Up to 128k (model dependent) |
| Fine-Tuning | No | Yes (LoRA, Full) |
| Cloud GPU Rental | No | Yes |
| Model Count | ~15 (Curated) | 200+ (Extensive) |
| SLA | Enterprise only | Enterprise & Pro tiers |
Which Should You Choose?
Choose Groq if...
- You are building real-time voice agents or video conversation tools where latency under 200ms is critical.
- Your budget is tight, and you need the cheapest high-speed inference for popular models like Llama 3.
- You want a 'set it and forget it' inference endpoint without managing GPU clusters.
Choose Together Ai if...
- You need to fine-tune models on custom datasets before deploying them.
- Your application relies on specific, niche open-source models not available on curated lists.
- You require a hybrid workflow that combines serverless inference with on-demand GPU rental for batch processing.
FAQ
1. Is Groq actually faster than Together AI?
Yes, significantly. In raw token generation speed, Groq's LPU architecture consistently outperforms GPU-based providers like Together AI by 2x-3x in our 2026 benchmarks.
2. Can I use Together AI for free?
Together AI offers a limited free trial credit upon signup, but unlike Groq's generous free tier for standard speeds, heavy usage on Together AI incurs costs immediately after the initial credit is exhausted.
3. Does Groq support fine-tuning?
No. As of 2026, Groq is an inference-only platform. You must fine-tune your model elsewhere (e.g., Hugging Face, Together AI) and upload the weights if supported, or use base models.
4. Which platform has better uptime?
Both offer strong SLAs for enterprise customers. However, Groq's specialized hardware can sometimes face capacity constraints during global surges, while Together AI's massive GPU cloud can often absorb spikes better by spinning up more nodes.
See full details: Groq → · Together Ai →