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Groq vs Replicate: Token Pricing, Speed & Intelligence

Full comparison of Groq and Replicate — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Updated July 2026.

Groq

LPU-powered inference — the fastest tokens per second available

Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.

SpeedReal-time chatVoice AICost-efficiencyBatch processing
Open-weight hostHosts open weights

Replicate

Run open-source AI models with a simple API — no infrastructure required

Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including Llama, Stable Diffusion, Whisper, and more. Pay per prediction with no infrastructure to manage — ideal for prototyping and production inference.

Image generationAudio transcriptionVideo modelsPrototypingCustom model deployment
Open-weight hostHosts open weights

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

Groq

750+ tokens/sec on Llama 3.3 70B — fastest GPU-class inference
Sub-100ms time-to-first-token for real-time applications
Very competitive pricing on open-weight models
OpenAI-compatible API
Free tier available
Limited model selection vs. Together AI or Fireworks
No vision model support on most models
No fine-tuning capability

Replicate

Thousands of community models available instantly
Simple pay-per-prediction pricing
No infrastructure management
Strong image/video/audio model support
Easy model deployment for custom models
Higher per-token cost than dedicated inference APIs for text models
Cold start latency on less popular models
Less suitable for high-throughput text inference

Key differentiators

Groq

Groq's custom LPU chips deliver 750+ tokens/sec on Llama 3.3 70B — 4–5× faster than any GPU-based provider.

Replicate

The largest catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Unmatched for image, audio, and video model access.

Frequently asked questions

Groq FAQs

How fast is Groq inference?

Groq delivers 750+ tokens/second on Llama 3.3 70B and 1,200+ tokens/second on Llama 3.1 8B. This is 4–5× faster than typical GPU-based providers, making it ideal for real-time applications.

How much does Groq cost?

Llama 3.3 70B costs $0.59/1M input and $0.79/1M output tokens. Llama 3.1 8B is just $0.05/$0.08 per 1M tokens — among the cheapest options for a capable open-weight model.

What is a Groq LPU?

A Language Processing Unit (LPU) is Groq's custom silicon designed specifically for sequential token generation. Unlike GPUs which are optimised for parallel matrix operations, LPUs excel at the autoregressive decoding step that dominates LLM inference latency.

Replicate FAQs

How does Replicate pricing work?

Replicate charges per prediction based on the compute time used. Pricing varies by model and GPU type. Text models are billed per token; image models per image. Some models are free with rate limits.

What types of models does Replicate support?

Replicate supports text (Llama, Mistral), image (Stable Diffusion, FLUX), audio (Whisper), video, and many other model types. It has one of the broadest model catalogs of any inference platform.

Can I deploy my own model on Replicate?

Yes. Replicate lets you package and deploy custom models using Cog, their open-source model packaging tool. Once deployed, your model gets a public API endpoint.

Provider resources

GroqLPU-powered inference — the fastest tokens per second available

Groq runs custom Language Processing Units (LPUs) that deliver dramatically higher throughput than GPU-based inference — Llama 3.3 70B reaches 750+ tokens/second on Groq, versus 100–200 on typical GPU providers. Ideal for latency-sensitive applications, real-time chat, and high-volume batch workloads.

Groq's custom LPU chips deliver 750+ tokens/sec on Llama 3.3 70B — 4–5× faster than any GPU-based provider.

ReplicateRun open-source AI models with a simple API — no infrastructure required

Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including Llama, Stable Diffusion, Whisper, and more. Pay per prediction with no infrastructure to manage — ideal for prototyping and production inference.

The largest catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Unmatched for image, audio, and video model access.

Key strengths compared

Groq

  • 750+ tokens/sec on Llama 3.3 70B — fastest GPU-class inference
  • Sub-100ms time-to-first-token for real-time applications
  • Very competitive pricing on open-weight models

Replicate

  • Thousands of community models available instantly
  • Simple pay-per-prediction pricing
  • No infrastructure management

Provider category context

Groq is a inference api, founded in 2016. Replicate is a inference api, founded in 2021. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both Groq and Replicate host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.