Simulating realistic Content generation parameters (800 in / 1,200 out with 30% cache reuse). Groq LPU — Llama 4 Scout delivers a 5% cost reduction over Fireworks AI — Llama 4 Scout.
Quick answer
For Content generation, Groq LPU — Llama 4 Scout is the lower-cost option at $0.000483 per request versus $0.000506 for Fireworks AI — Llama 4 Scout, a modeled saving of 5%.
Method & trust
The comparison uses 800 input tokens, 1,200 output tokens, and 30% cache reuse for the selected workload. Pricing is applied per model, then scaled to monthly request volumes.
| Traffic Volume Tier | Fireworks AI — Llama 4 Scout Monthly | Groq LPU — Llama 4 Scout Monthly | Monthly Savings by picking Groq LPU — Llama 4 Scout |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $0.5064 | $0.4828 | Save $0.0236 / mo |
| 10,000 reqs/mo (Small App) | $5.064 | $4.828 | Save $0.236 / mo |
| 100,000 reqs/mo (Growth Production) | $50.64 | $48.28 | Save $2.36 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $506.40 | $482.80 | Save $23.60 / mo |
Groq LPU — Llama 4 Scout is 5% cheaper for Content generation workloads. At standard Content generation parameter ratios (800 input tokens, 1,200 output tokens, 30% cache hit), Groq LPU — Llama 4 Scout costs $0.000483 per request compared to $0.000506 on Fireworks AI — Llama 4 Scout.
Fireworks AI — Llama 4 Scout offers a context window of 10,000,000 tokens (max output: 16,384), while Groq LPU — Llama 4 Scout offers 512,000 tokens (max output: 16,384).
At 100,000 requests per month, using Groq LPU — Llama 4 Scout saves $2.36 every month (or $28.32 annually) compared to Fireworks AI — Llama 4 Scout.
Output-heavy workloads favor models with a low output price, not a low input price. Batch similar generation tasks with shared style prompts to exploit caching. Draft with a cheap tier, refine the winners with a premium model.