Cheapest AI API for Coding
Compare all 34 AI models ranked by code generation cost. Adjust token counts and requests per day to find the cheapest API for your exact coding workload.
Cheapest Model
All 34 Models Ranked by Coding Cost
Models sorted from cheapest to most expensive per code request. Adjust inputs above to re-rank in real time.
| Rank | Model | Provider | Input/1M | Output/1M | Cost/Request | Monthly (1K/day) | Relative Cost |
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Best Model by Coding Task
Recommended models for each type of coding workflow based on cost and capability
| Coding Task | Tokens (In/Out) | Best Value Model | Cost/Request | Monthly Cost (1K/day) | Runner-Up |
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How to Choose the Cheapest AI API for Coding
The cost of using an AI API for code generation depends on two factors: input price per 1M tokens (your prompts and context) and output price per 1M tokens (the generated code). Since code generation typically produces more output than input relative to chat use cases, output pricing matters disproportionately.
At default coding settings (2,000 input + 800 output tokens per request), the cheapest options are:
- DeepSeek V4 Flash ($0.14/$0.28): The overall cheapest for code generation at $0.000504/request. Excellent code quality for the price.
- Llama 3.1 8B ($0.10/$0.10): Cheapest input pricing. Great for code completion and simple tasks where you need low latency.
- Gemini 2.0 Flash Lite ($0.075/$0.30): Lowest input price of any model. Good for input-heavy code review tasks.
- DeepSeek V4 Pro ($0.44/$0.87): Best quality-to-cost ratio for complex code generation. 3x more expensive but significantly better code quality.
- GPT-5 mini ($0.25/$2.00): Good middle ground if you want OpenAI ecosystem compatibility.
Coding Cost by Task Type
Different coding tasks have different token profiles, which changes which model is cheapest:
- Code completion (500/200): Short prompts, short outputs. Llama 3.1 8B wins at $0.00005/request because its symmetric $0.10/$0.10 pricing excels for short outputs.
- Code generation (2,000/800): Medium prompts, longer outputs. DeepSeek V4 Flash wins at $0.000504/request. Its low output price ($0.28/1M) is key.
- Code review (3,000/600): Large context, moderate output. Gemini 2.0 Flash Lite wins at $0.000405/request thanks to its ultra-low input price ($0.075/1M).
- Debugging (1,500/500): Moderate tokens. DeepSeek V4 Flash wins at $0.000351/request.
- Refactoring (4,000/1,000): Large context and output. DeepSeek V4 Flash wins at $0.00084/request, with Llama 3.1 8B close behind.
How to Reduce Your AI Coding API Costs
- Use model routing: Route code completion to the cheapest model (Llama 3.1 8B) and complex generation to a mid-tier model (DeepSeek V4 Pro). Saves 40-70%.
- Trim context windows: Don't send entire files when only relevant functions are needed. Reducing input from 4,000 to 1,500 tokens cuts costs by 60%+.
- Set max_tokens: Cap output at what you actually need. If your code snippets are 300 tokens, don't set max_tokens to 2,000.
- Batch processing: Use batch APIs where available for non-urgent tasks like code review. Typically 50% cheaper.
- Cache common prompts: If your IDE sends the same file context repeatedly, use prompt caching to reduce input token costs.
Related Tools
- LLM Cost Calculator — Estimate costs for any model and usage pattern
- Cost Explorer — Interactive dashboard comparing all 34 models
- Model Switch Calculator — See savings from switching to a cheaper model
- Compare Models — Side-by-side model comparison tool
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