Problem

Currently, Codex CLI doesn't provide users with control over OpenAI API service tiers, limiting cost optimization options for different use cases.

Proposed Solution

Add service_tier configuration option to control API request cost and latency via OpenAI's service tier parameter:

• auto (default): Standard processing with automatic tier selection
• flex: 50% cheaper processing with increased latency, ideal for non-production workloads
• priority: Faster processing for enterprise users

Implementation Details

• Configuration via service_tier in config.toml and profiles
• CLI flag --service-tier for per-session override
• Model compatibility validation with fallback to auto
• Support for both exec and TUI modes

Use Cases

• Development/testing: Use flex tier for 50% cost savings on non-critical workloads
• Production: Use priority tier for faster response times
• Batch processing: Use flex for cost-effective background tasks

Configuration Examples

# Global setting
service_tier = "flex"

# Profile-specific
[profiles.cost-optimized]
model = "o3"
service_tier = "flex"

# CLI usage
codex --service-tier flex "Analyze this code"
codex exec --service-tier priority "Generate tests"

Benefits

• Cost optimization: Up to 50% savings with flex tier
• Performance control: Priority tier for time-sensitive work
• Flexibility: Per-session and per-profile configuration
• Backward compatibility: Auto tier maintains existing behavior

This feature aligns with OpenAI's service tier offerings and provides users with cost/performance control without breaking existing workflows.