Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). DeepSeek R1 (Reasoner) delivers a 55% cost reduction over o3-mini.
Quick answer
For AI coding assistant, DeepSeek R1 (Reasoner) is the lower-cost option at $0.008028 per request versus $0.018 for o3-mini, a modeled saving of 55%.
Method & trust
The comparison uses 12,000 input tokens, 2,000 output tokens, and 60% cache reuse for the selected workload. Pricing is applied per model, then scaled to monthly request volumes.
| Traffic Volume Tier | DeepSeek R1 (Reasoner) Monthly | o3-mini Monthly | Monthly Savings by picking DeepSeek R1 (Reasoner) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $8.028 | $18.04 | Save $10.012 / mo |
| 10,000 reqs/mo (Small App) | $80.28 | $180.40 | Save $100.12 / mo |
| 100,000 reqs/mo (Growth Production) | $802.80 | $1,804.00 | Save $1,001.20 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $8,028.00 | $18,040.00 | Save $10,012.00 / mo |
DeepSeek R1 (Reasoner) is 55% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), DeepSeek R1 (Reasoner) costs $0.008028 per request compared to $0.018 on o3-mini.
DeepSeek R1 (Reasoner) offers a context window of 64,000 tokens (max output: 8,000), while o3-mini offers 200,000 tokens (max output: 100,000).
At 100,000 requests per month, using DeepSeek R1 (Reasoner) saves $1,001.20 every month (or $12,014.40 annually) compared to o3-mini.
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.