Simulating realistic Translation parameters (5,000 in / 5,500 out with 15% cache reuse). Groq LPU — Llama 4 Maverick delivers a 28% cost reduction over Cerebras — GPT OSS 120B.
| Traffic Volume Tier | Cerebras — GPT OSS 120B Monthly | Groq LPU — Llama 4 Maverick Monthly | Monthly Savings by picking Groq LPU — Llama 4 Maverick |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $5.875 | $4.225 | Save $1.65 / mo |
| 10,000 reqs/mo (Small App) | $58.75 | $42.25 | Save $16.50 / mo |
| 100,000 reqs/mo (Growth Production) | $587.50 | $422.50 | Save $165.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $5,875.00 | $4,225.00 | Save $1,650.00 / mo |
Groq LPU — Llama 4 Maverick is 28% cheaper for Translation workloads. At standard Translation parameter ratios (5,000 input tokens, 5,500 output tokens, 15% cache hit), Groq LPU — Llama 4 Maverick costs $0.004225 per request compared to $0.005875 on Cerebras — GPT OSS 120B.
Cerebras — GPT OSS 120B offers a context window of 128,000 tokens (max output: 8,192), while Groq LPU — Llama 4 Maverick offers 512,000 tokens (max output: 16,384).
At 100,000 requests per month, using Groq LPU — Llama 4 Maverick saves $165.00 every month (or $1,980.00 annually) compared to Cerebras — GPT OSS 120B.
Output length ≈ input length; budget both sides of the request. Japanese and Chinese text typically costs more per word than English due to tokenization. Cache translation memories and glossaries embedded in the prompt.