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OpenAI vs Groq: Token Pricing, Speed & Intelligence

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

OpenAI

GPT-4o, o3, and the world's most widely-used AI API

OpenAI is the creator of the GPT model family and the ChatGPT product. Their API provides access to frontier models including GPT-4o, the o-series reasoning models, and the GPT-4.1 long-context family. Pricing is competitive for frontier-tier capability, with prompt caching available on most models.

CodingChatVisionReasoningAgents
Proprietary models

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

Key metrics

Cheapest input ($/1M)

Cheapest output ($/1M)

Peak throughput

Best latency (TTFT)

Intelligence score

Context window

Live token pricing

Strengths & weaknesses

OpenAI

Largest ecosystem & third-party integrations
Best-in-class function calling & structured outputs
Prompt caching on all major models
o3/o4-mini reasoning models for complex tasks
1M+ token context on GPT-4.1
No open-weight models — full vendor lock-in
Output pricing is among the highest for frontier tier
Rate limits can be restrictive on lower tiers

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

Key differentiators

OpenAI

The most widely-integrated LLM API — virtually every AI framework and tool supports OpenAI natively.

Groq

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

Frequently asked questions

OpenAI FAQs

How much does the OpenAI API cost?

GPT-4o costs $2.50/1M input tokens and $10/1M output tokens. GPT-4o-mini is $0.15/$0.60 per 1M tokens. Prompt caching cuts input costs by 50% on eligible requests.

What is the difference between GPT-4o and o3?

GPT-4o is a fast, multimodal model optimised for chat, vision, and coding. o3 is a reasoning model that uses chain-of-thought to solve complex problems — it is slower and more expensive but significantly more capable on math, science, and hard coding tasks.

Does OpenAI support prompt caching?

Yes. Prompt caching is available on GPT-4o, GPT-4.1, o3, and o4-mini. Cached input tokens are billed at 50% of the standard input price, making long-context and repeated-system-prompt workloads significantly cheaper.

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.

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