API Prices Down to 1/10-1/30
GPT-4 in early 2023 was $30/1M input tokens, but as of 2026, even GPT-5-class frontier models are $2.50-$10, and lightweight models down to $0.05-$0.50/1M tokens. 1/10-1/30 in 3 years. Both semiconductor-efficiency gains and intensified competition contribute.
Main Model Prices (2026)
| Model | Input ($/1M) | Output ($/1M) |
|---|---|---|
| GPT-5.4 | $2.50 | $10 |
| GPT-5 Mini | $0.20 | $0.80 |
| GPT-5 Nano | $0.05 | $0.20 |
| Claude Opus 4.7 | $5 | $25 |
| Claude Sonnet 4.6 | $1 | $5 |
| Claude Haiku 4.5 | $0.20 | $1 |
| Gemini 3.1 Pro | $1.25 | $5 |
| Mistral Large 3 | $2 | $6 |
| DeepSeek V3 | $0.27 | $1.10 |
* Approximate. Prompt caching/batch API discount a further 50-90%.
Price-War Dynamics
Downward Pressure
- Increased number of competitors
- Hardware-efficiency gains like NVIDIA Blackwell, TPU v6
- Inference-cost cuts via MoE, quantization, distillation
- Dedicated-ASIC (Groq, Cerebras) entry
- More self-host options with open-weight models
Upward Pressure
- Rising frontier-model training cost (tens to hundreds of billions of yen)
- Long-context (1M-10M tokens) processing cost
- Multimodal (audio/video) extra cost
- GPU tightness from demand growth
The Standard of Selective Model Use
- Frontier: complex reasoning, code generation, agent commander
- Mid-tier: daily work, summary, translation
- Light: classification, routing, batch
A "model cascade" design using multiple tiers in one app is common. A config handling 80% with Light, 15% Mid, 5% Frontier cuts cost to 1/5-1/10 vs frontier-only.
Cost-Lock-in Measures
Abstraction Layer
- API abstraction with LangChain, LlamaIndex, Vercel AI SDK
- Unified API with OpenRouter, Together AI
- Make a thin in-house wrapper for easy switching
Multi-Model Testing
- Periodically evaluate multiple models on the same task
- Monitor cost/performance difference on vendor switch
- A/B test on new-model announcements
Use Prompt Caching
Provided by Anthropic, OpenAI, Google. Reusing the same system prompt + tool definitions cuts input-token cost up to 90%. Essential for agent operation.
Self-Hosting Break-Even
- Low volume (under 1M tokens/month): API is cheaper
- Mid volume (100M tokens/month): in-house and API are even
- High volume (over 1B tokens/month): in-house is 30-70% cheaper
But include operating cost (GPU rental, observability, security, incident response) in the estimate.
2026 Outlook
- API prices continue a downward base
- Increased extra charges for long-context/multimodal features
- Chinese models' (DeepSeek, Qwen) cheapness pressures the market
- Full introduction of "free tiers"
Summary
The API price war is a tailwind for both consumers and companies. To maximize the price drop, the iron rule is to systematize 4 points: (1) model-cascade design, (2) vendor abstraction, (3) prompt caching, (4) periodic re-evaluation. The self-host decision is decided by volume and operational capability.
