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The Cost Problem

A typical coding agent session burns through tokens fast:
ActivityTokens per callCalls per hourHourly tokens
Code generation5,000–50,00010–30150K–1.5M
Codebase search2,000–20,00020–50100K–1M
Code review10,000–80,0005–10100K–800K
Autocomplete500–3,00050–20050K–600K
Total400K–4M+
At premium model rates, that’s 3–30/hourperdeveloper.Forateamof10,that′s3–30/hour per developer. For a team of 10, that's 500–5,000/month.

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Smart Model Selection

Not every coding task needs the most expensive model. Match the task to the right tier:
TaskRecommendedCost TierWhy
Architecture designclaude-opus-4-6, gpt-5.4$$$$ PremiumComplex reasoning needed
Code generationclaude-sonnet-4-6, gemini-3-pro-preview$$$ StandardBest quality/cost balance
Code reviewclaude-sonnet-4-6, deepseek-r1$$–$$$Pattern matching, less creativity
Bug fixingclaude-sonnet-4-6, gpt-5-mini$$–$$$Focused, well-defined tasks
Tab completiongpt-5-mini, gemini-3-flash-preview$$ BudgetSpeed matters more than depth
Boilerplatedeepseek-v3.2, gpt-5-mini$ EconomySimple, repetitive patterns
See Model Selection Guide for detailed model comparisons and per-tool configuration.

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Caching Strategies

Coding agents are ideal for caching because they repeat similar patterns constantly.

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Prompt Cache (Provider-Level)

Upstream prompt caching is automatic through AI Sonar. Long system prompts — which coding agents always include — get cached at the provider level:
ProviderCache DiscountMin Tokens
Anthropic90% off reads1,024
OpenAI50% off reads1,024
DeepSeek90% off reads64
Since coding agents send the same system prompt + project context on every call, prompt cache hit rates are typically 70–90%.

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Prompt Cache Savings Example

For a request with 50,000 input tokens (typical coding agent call): 
Direct API (no caching):
  50,000 tokens × $3.00/1M = $0.150

With prompt cache (40,000 cached + 10,000 new):
  Cached:  40,000 × $0.30/1M = $0.012
  New:     10,000 × $3.00/1M = $0.030
  Total: $0.042 (72% savings)

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Real Cost Comparison

Estimated costs for a typical 1-hour coding session (~3M tokens):
SetupHourly CostMonthly (160h)
Direct API (premium model)~$15–25~$2,400–4,000
AI Sonar (smart routing)~$10–18~$1,600–2,900
AI Sonar + prompt cache~$4–8~$640–1,280
These are illustrative estimates. Actual costs depend on your model choice, usage patterns, and cache hit rates. Check real-time pricing for current rates.

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Token Management Tips

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Set max_tokens

Prevent runaway generation: 
{
  "model": "claude-sonnet-4-6",
  "max_tokens": 4096,
  "messages": [...]
}
Most coding tasks need 1,000–4,000 output tokens. Setting a limit prevents the model from generating unnecessarily long responses.

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Use Auto-Compact

Most coding agents support context compaction — summarizing old conversation turns to reduce token count. Enable it:
  • Claude Code: Built-in auto-compact triggers at context limits
  • Cursor: Automatic context management
  • Codex CLI: Use --max-context flag

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Avoid Context Bloat

  • Don’t paste entire files when a function is enough
  • Use .gitignore-style patterns to exclude irrelevant files from agent context
  • Clear conversation history when switching tasks

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Quick Configuration

Each tool needs just a few lines to connect through AI Sonar: 
export ANTHROPIC_API_KEY="sk-your-api-key"
export ANTHROPIC_BASE_URL="https://api.aisonar.dev"
Full setup guide →
Settings → Models → OpenAI API Key: sk-your-key, Base URL: https://api.aisonar.dev/v1Full setup guide →
export OPENAI_API_KEY="sk-your-api-key"
export OPENAI_BASE_URL="https://api.aisonar.dev/v1"
Full setup guide →
export GEMINI_API_KEY="sk-your-api-key"
export GOOGLE_GEMINI_BASE_URL="https://api.aisonar.dev"
Full setup guide →