gemini-3.5-flash vs gpt-oss-120b
Google Gemini against Cerebras, priced on the same four workloads with price book 2026-10-22.
On real workloads
| Workload | gemini-3.5-flash per call | gpt-oss-120b per call | Monthly difference |
|---|---|---|---|
| Chat reply 1,500 input and 400 output tokens, 100,000 calls a month |
$0.00585 | $0.000825 | −$502.50 |
| RAG answer, cached context 2,000 fresh + 4,000 cached input, 500 output, 100,000 calls a month |
$0.0081 | $0.00248 | −$562.50 |
| Agent step 4,000 fresh + 8,000 cached input, 800 output, 250,000 calls a month |
$0.01 | $0.0048 | −$2,400.00 |
| Batch summary 3,000 input and 300 output tokens via the Batch API, 1,000,000 calls a month |
$0.0036 | — | — |
Monthly difference is gpt-oss-120b minus gemini-3.5-flash. Batch rows use each provider's Batch API rates where published. Price both on your own workload.
Rates
| Model | Input | Output | Cache read | Cache write | Context |
|---|---|---|---|---|---|
| google/gemini-3.5-flash | $1.50 | $9.00 | $0.15 | — | 1M |
| cerebras/gpt-oss-120b | $0.35 | $0.75 | — | — | 131.1K |
Price is one input. Before switching, run your own prompts through both and compare quality; then veqen diff prices the change at your production volume.