Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Together AI — Llama 4 Maverick delivers a 67% cost reduction over OpenRouter Auto-Best Router.
| Traffic Volume Tier | Together AI — Llama 4 Maverick Monthly | OpenRouter Auto-Best Router Monthly | Monthly Savings by picking Together AI — Llama 4 Maverick |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $6.00 | $18.00 | Save $12.00 / mo |
| 10,000 reqs/mo (Small App) | $60.00 | $180.00 | Save $120.00 / mo |
| 100,000 reqs/mo (Growth Production) | $600.00 | $1,800.00 | Save $1,200.00 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $6,000.00 | $18,000.00 | Save $12,000.00 / mo |
Together AI — Llama 4 Maverick is 67% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Together AI — Llama 4 Maverick costs $0.006 per request compared to $0.018 on OpenRouter Auto-Best Router.
Together AI — Llama 4 Maverick offers a context window of 1,000,000 tokens (max output: 16,384), while OpenRouter Auto-Best Router offers 1,000,000 tokens (max output: 32,768).
At 100,000 requests per month, using Together AI — Llama 4 Maverick saves $1,200.00 every month (or $14,400.00 annually) compared to OpenRouter Auto-Best Router.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.