While developing an Agent system, the author faced budget constraints and needed to handle extensive code reading and writing. The article provides an in-depth comparison of several mainstream AI models: Deepseek v3.2, with only 160K context but low cost; Gemini 3 Flash, featuring ultra-long context and affordable pricing, though its capabilities remain to be tested; Grok Code Fast1, offering 256K context but questionable performance as an older model; and GPT-5.1-Codex-mini, cost-effective with unknown capabilities. The author shares practical usage experience, emphasizing the critical trade-offs between context length, price, and performance, offering valuable insights for AI developers to optimize system design under resource constraints.
