I Ran 10 Coding AIs Through Real Client Work — Here's the Bill

Описание и применение

Разработчик-одиночка сравнил 10 LLM‑моделей по стоимости и качеству, выявив, что DeepSeek V4 Flash и Qwen3‑Coder‑30B дают наилучшее соотношение качества к цене для типичных задач, а премиальные модели используют только для критических проверок безопасности.

Задача

Freelance developers need to choose cost‑effective LLMs for client work, balancing quality and token cost.

Результат

Using DeepSeek V4 Flash and Qwen3‑Coder‑30B for routine coding tasks delivers the best quality‑per‑dollar, while premium models are reserved for security reviews, improving profitability and billing accuracy.

Рабочий процесс

• 1. Identify 10 available, affordable models and list their per‑million output token cost.
• 2. Select five representative coding tasks that match typical client work.
• 3. Prompt each model with the same task and record output token count and cost.
• 4. Score each output on correctness, quality, documentation, and edge‑case handling (1–10).
• 5. Calculate value as score divided by cost per million tokens.
• 6. Rank models by value to identify the most cost‑effective options.
• 7. Update workflow: use low‑cost models for routine tasks, premium models for security reviews or detailed explanations.
• 8. Track token usage per day to forecast monthly costs and adjust model usage accordingly.

Доказательства

DeepSeek V4 Flash scored 8.7 with an output cost of $0.25/M, yielding a value of 34.8.

Источник

Qwen3‑Coder‑30B achieved a score of 8.8 for $0.35/M, value 25.1.

Источник

DeepSeek‑R1 found 9 security issues versus 6 for cheaper models.

Источник