Model Comparison → Compare

Llama 3.3 70B (Groq) vs Llama 3.3 70B

Our verdict

Same model, different hardware: Groq wins on raw speed (800 tok/s vs 60 tok/s). Together wins on price for batch workloads.

Llama 3.3 70B on Groq LPU ($0.59/M) vs Together AI ($0.23/M) — Together AI is 2.6× cheaper. Groq is 10-15× faster in tokens/second. The choice depends on your latency vs cost tradeoff: real-time chat interfaces benefit from Groq's speed; batch processing and offline workloads should use Together.

Side-by-side pricing

Llama 3.3 70B (Groq)Llama 3.3 70B
ProviderGroqMeta
Input price/1M$0.59$0.23
Output price/1M$0.79$0.40
Cache read/1M
Context window128K128K
Vision
Tool use
Prompt caching
Speed tierFastFast

Prices verified 2026-08-20. See changelog for history.

Winner by task

Real-time latency
Llama 3.3 70B (Groq)
~800 tok/s vs ~60 tok/s — dramatically faster for interactive use
Cost per token
Llama 3.3 70B
$0.23/M vs $0.59/M — 2.6× cheaper
Batch processing
Llama 3.3 70B
Cheaper and throughput matters more than latency
Model quality
Tie
Identical model weights; quality is the same

Calculate costs for each model

Llama 3.3 70B (Groq) pricing →Llama 3.3 70B pricing →Calculate for your workload →

Frequently Asked Questions

Is Groq actually faster than other inference providers?

Yes — Groq's LPU (Language Processing Unit) hardware achieves 800-2000 tokens/second for Llama 70B models, vs 50-100 tok/s on A100 GPU clusters. This is real and reproducible. For latency-sensitive applications (voice interfaces, real-time chat), Groq is meaningfully better.

Prices verified 2026-08-20. See methodology for calculation details.