Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). Cerebras — Gemma 4 31B delivers a 69% cost reduction over Cohere Command R+.
| Traffic Volume Tier | Cohere Command R+ Monthly | Cerebras — Gemma 4 31B Monthly | Monthly Savings by picking Cerebras — Gemma 4 31B |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $7.50 | $2.353 | Save $5.147 / mo |
| 10,000 reqs/mo (Small App) | $75.00 | $23.525 | Save $51.475 / mo |
| 100,000 reqs/mo (Growth Production) | $750.00 | $235.25 | Save $514.75 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $7,500.00 | $2,352.50 | Save $5,147.50 / mo |
Cerebras — Gemma 4 31B is 69% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), Cerebras — Gemma 4 31B costs $0.002353 per request compared to $0.0075 on Cohere Command R+.
Cohere Command R+ offers a context window of 128,000 tokens (max output: 4,096), while Cerebras — Gemma 4 31B offers 128,000 tokens (max output: 8,192).
At 100,000 requests per month, using Cerebras — Gemma 4 31B saves $514.75 every month (or $6,177.00 annually) compared to Cohere Command R+.
Volume makes nano-tier models attractive — extraction rarely needs frontier reasoning. Constrain output with JSON schema modes to avoid retry loops on malformed responses. Cache shared schema instructions and few-shot examples across calls.