Most indie devs and small SaaS waste massive budget on expensive OpenAI/Claude APIs. After 2 months of production testing, I built a cost-saving solution combining Qwen-Turbo and DeepSeek series, cutting total token cost up to 72% without downgrading response quality. This guide includes official raw pricing, task allocation rules and real billing data.
- Raw Official Token Price List (USD / 1M Tokens) Model Input Output Core Advantage Best Scenario Qwen-Turbo $0.05 $0.10 Ultra-low cost, multilingual Classification, short chat, translation DeepSeek-V3(Cache Hit) $0.028 $0.28 Cache discount Multi-turn customer chat DeepSeek-V3(Normal) $0.14 $0.28 Balance cost&quality General long document summary DeepSeek-R1 $0.55 $2.19 Top reasoning Math/code/logic calculation Core highlight：Qwen-Turbo input only $0.05 per million tokens, far cheaper than most mainstream open-source cloud APIs.
- Core Optimization 3 Rules Task-based model routing（成本降幅 45%） Simple tasks(intention extraction, keyword pull): Qwen-Turbo; daily chat: DeepSeek-V3; complex reasoning: DeepSeek-R1 only. Most projects misuse high-end model for trivial requests, which causes overspending. Enable input cache（cost cut extra 25%） DeepSeek native cache auto-discount repeated context input; our platform adds global request cache to Qwen services, repeat prompts hit cached result directly with zero token cost. Prompt compression（save 5%-10% token） Trim redundant system prompt, remove useless description in fixed prompt template.
- Real Case: Small AI Chatbot Monthly Cost Comparison Original: Full GPT-3.5 → $218/month After Qwen+DeepSeek optimization → $59/month (↓72%) Ending If you want ready-to-use low-price Qwen & DeepSeek API with built-in routing+cache system, check our pricing page: asiatekai.com. We provide pay-as-you-go token billing and monthly subscription plans for indie developers.
source & further reading
dev.to — original article
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