LiteLLM's cost calculation for OpenAI's gpt-image-1 model is incomplete and significantly underestimates actual costs by completely ignoring input token costs.

Current behavior:
The cost calculator only computes the cost of generating output images using a fixed per-pixel rate:

# litellm/cost_calculator.py:1166
return cost_info["input_cost_per_pixel"] * height * width * n

What's missing:
LiteLLM completely ignores input token costs:

1. Input text token costs: Every gpt-image-1 call includes a text prompt that should be billed at $1.00-$5.00/1M tokens (depending on tier)
2. Input image token costs: When processing input images (for editing/variation), should be billed at $10.00/1M tokens

Expected behavior:
Cost calculation should be:

total_cost = (
    prompt_tokens * text_token_rate +           # Missing: input prompt costs
    input_image_tokens * image_input_rate +     # Missing: input image costs  
    current_output_image_cost                   # Keep existing per-pixel calculation
)

Impact:
This causes significant cost underestimation since input token costs are often much higher than output image costs. Users get completely inaccurate billing estimates.

Root cause:
LiteLLM treats gpt-image-1 like DALL-E 3 (pure image generation model) instead of recognizing it's a multimodal model that processes both text and image inputs.

Reference:
According to OpenAI's official pricing (https://platform.openai.com/docs/pricing), gpt-image-1 has separate pricing sections for:

• Text tokens: $1.00-$5.00/1M tokens
• Image tokens: $10.00/1M input tokens
• Image generation: $0.011-$0.25 per image (current implementation covers this)

LiteLLM version: v1.75.9