Groq vs Together AI: Which Fast Inference API Is Right for You?
Groq vs Together AI for fast LLM inference — speed (tokens/sec), pricing, model selection, free tier, rate limits, and use case guide. Which API is faster and cheaper in 2025?
Quick comparison
| Feature | Groq | Together AI |
|---|---|---|
| Hardware | Custom LPU | NVIDIA GPU clusters |
| Speed (70B model) | ~750–900 tok/s | ~100–200 tok/s |
| Free tier | Daily limits per model | Trial credits only |
| Model catalog | 20–30 models (LPU-compiled) | 100+ models |
| Llama-3.3-70b price | $0.59/1M tokens | ~$0.90/1M tokens |
| Embeddings | No | Yes (e5-mistral-7b) |
| Fine-tuning | No | Yes (custom models) |
| API compatibility | OpenAI-compatible | OpenAI-compatible |
Speed: LPU vs GPU
Groq's LPU hardware is purpose-built for LLM inference — sequential token generation with minimal memory bandwidth bottleneck. Benchmark: Llama-3.3-70b on Groq achieves 750–900 tokens/second. Together AI on GPU clusters delivers 100–200 tokens/second for the same model.
This gap matters for real-time chatbots where streaming speed is a direct UX metric. A response that takes 2 seconds to start streaming on Together AI might feel instant on Groq. For batch processing pipelines where you submit 1,000 requests and wait, the per-request latency difference matters less than total throughput — and Together AI's large GPU fleet can run many requests in parallel.
Rule of thumb: if latency-per-request is your constraint, Groq wins decisively. If total throughput at scale is the metric, compare actual benchmarks for your workload on both platforms.
Model selection
Groq model catalog
Groq supports a curated set of ~25 models that have been compiled for LPU silicon. The list includes llama-3.3-70b-versatile, mixtral-8x7b, gemma2-9b, qwen-qwq-32b, and several other popular open-source models. The full list is at console.groq.com/docs/models and changes as new compilations are released.
The key constraint: if Groq hasn't compiled a model for LPU, it's not available — no exceptions. This is a hard boundary that doesn't exist on GPU-based providers.
Together AI model catalog
Together AI hosts 100+ models including many experimental and fine-tuned variants not available elsewhere. This includes deepseek-r1 variants, code-focused models, math-specialized models, and models from smaller research labs.
Together AI also offers embeddings via e5-mistral-7b-instruct, which Groq does not provide. If your application needs both completions and embeddings from one provider, Together AI is the only choice between the two.
Pricing
Groq offers an input-heavy pricing model with a free tier that includes per-model daily limits. For paid usage, Llama-class models run $0.05–$0.79/1M tokens depending on model size. Llama-3.3-70b is $0.59/1M. The free tier is genuinely useful for prototyping and low-volume applications.
Together AI has no free tier beyond initial trial credits. Most models are priced at $0.20–$0.90/1M tokens. meta-llama-3.1-70b is ~$0.90/1M — roughly 50% more expensive than Groq's equivalent. However, for models only available on Together AI (deepseek-r1 variants, specialized fine-tunes), price comparison is not applicable.
For the overlapping model set (Llama 3.x, Mixtral), Groq is consistently cheaper. For models exclusive to Together AI, there's no competition — Together AI is the only option.
Rate limits
Groq free tier: 30 requests per minute (RPM) and 14,400 requests per day (RPD) per model. Each model has its own independent limit — hitting the limit on llama-3.3-70b doesn't affect your mixtral-8x7b quota. During peak hours, hitting the RPM limit is common for active developers. Groq's paid tiers unlock higher limits via their console.
Together AI: rate limits are based on account spend tier. Higher monthly spend unlocks higher limits. The structure rewards production usage patterns — as your billing increases, your limits increase proportionally. There's no hard per-model separation like Groq's approach.
For production high-throughput workloads, both providers require upgrading beyond their entry tiers. Plan for this in your architecture — rate limit errors at scale are a common source of silent failures if not handled with exponential backoff.
OpenAI API compatibility
Both Groq and Together AI are OpenAI API-compatible — you can use the official OpenAI SDK with either by changing two parameters.
Groq:
base_url="https://api.groq.com/openai/v1" api_key="gsk_..."
Together AI:
base_url="https://api.together.xyz/v1" api_key="..."
For most OpenAI SDK code, this is a drop-in replacement. The main incompatibility is model names — you must use the model IDs specific to each provider rather than gpt-4o. Streaming, function calling, and system prompt support all work across both providers.
Which should you use?
Use Groq if…
- You need maximum streaming speed for chatbot UX
- Your target model is available on Groq's LPU catalog
- You want to prototype for free with daily limits
- You want the cheapest option for Llama or Mixtral class models
- Low per-request latency is more important than model variety
Use Together AI if…
- You need a model not available on Groq (deepseek-r1, fine-tunes, etc.)
- You need embeddings alongside completions
- You need fine-tuning on custom data
- You want access to 100+ experimental and research models
- Batch throughput matters more than per-request latency
Track Groq API and Together AI uptime at prismix.dev
Both have had outages during peak hours. Get email alerts before your production app notices.
FAQ
Is Groq faster than Together AI?
Yes, Groq uses custom LPU (Language Processing Unit) hardware and is typically 3–10x faster in tokens/second than Together AI's GPU clusters. Groq llama-3.3-70b-versatile achieves ~800 tok/s vs Together AI's ~100–200 tok/s for the same model.
Is Groq or Together AI cheaper?
Groq's free tier is quite generous (daily limits per model). Together AI charges per token with no free tier beyond trial credits. For production: Together AI offers meta-llama-3.1-70b at $0.90/1M tokens; Groq charges $0.59/1M for the same model class. Groq is often cheaper for mid-tier models.
Does Groq support all LLM models?
No. Groq only supports models compiled for their LPU hardware (listed at console.groq.com/docs/models). Together AI supports 100+ models including many open-source options not on Groq. If you need a specific model, check Groq first, then fall back to Together AI.
Which has better uptime, Groq or Together AI?
Both had occasional outages in 2024–2025. Groq tends to have capacity limits during peak hours — per-model rate limits hit 30 RPM on the free tier. Monitor both at prismix.dev/service/groq-api and prismix.dev/service/together-ai.