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Anthropic vs Groq: Token Pricing, Speed & Intelligence

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

Anthropic

Claude — safety-focused frontier AI with exceptional coding ability

Anthropic builds the Claude model family, known for long context windows (up to 200K tokens), strong coding performance, and a safety-first design philosophy. Claude 4 Opus and Sonnet lead on many coding and reasoning benchmarks. Prompt caching is available at significant discounts.

CodingReasoningLong-contextChatAgents
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

Anthropic

Top coding benchmark scores (Claude 4 Opus)
200K context window on all Claude models
Aggressive prompt caching — up to 90% discount
Strong instruction-following and safety alignment
Extended thinking / reasoning mode on Opus
No open-weight models — full vendor lock-in
Opus is the most expensive frontier model at $15/$75 per 1M tokens
No native image generation capability

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

Anthropic

Claude 4 Opus scores highest on coding benchmarks among all frontier models, with a 200K context window and aggressive prompt caching.

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

Anthropic FAQs

How much does the Anthropic Claude API cost?

Claude 4 Opus costs $15/1M input and $75/1M output tokens. Claude Sonnet 4.5 is $3/$15 per 1M tokens. Claude Haiku 3.5 is the budget option at $0.80/$4.00. Prompt caching reduces input costs by up to 90%.

What is the context window for Claude models?

All Claude models support a 200,000-token context window, making them ideal for processing long documents, codebases, or multi-turn conversations without truncation.

How does Anthropic prompt caching work?

Anthropic's prompt caching lets you mark portions of your prompt (system prompts, documents, tool definitions) to be cached server-side. Cached tokens are billed at 10% of the standard input price after the first write, making repeated long-context calls dramatically 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.

Provider resources

AnthropicClaude — safety-focused frontier AI with exceptional coding ability

Anthropic builds the Claude model family, known for long context windows (up to 200K tokens), strong coding performance, and a safety-first design philosophy. Claude 4 Opus and Sonnet lead on many coding and reasoning benchmarks. Prompt caching is available at significant discounts.

Claude 4 Opus scores highest on coding benchmarks among all frontier models, with a 200K context window and aggressive prompt caching.

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.

Key strengths compared

Anthropic

  • Top coding benchmark scores (Claude 4 Opus)
  • 200K context window on all Claude models
  • Aggressive prompt caching — up to 90% discount

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

Provider category context

Anthropic is a frontier lab, founded in 2021. Groq is a inference api, founded in 2016. Anthropic as a frontier lab trains and serves its own proprietary models. Groq as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose Anthropic if you need top coding benchmark scores (claude 4 opus). Choose Groq if you need 750+ tokens/sec on llama 3.3 70b — fastest gpu-class inference. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.