Multi-Provider LLM Cost Analysis: Finding the Cheapest Brain for Your Task

Not all tokens cost the same. A prompt that costs $0.50 on Claude might cost $0.08 on Gemini or $0.03 on DeepSeek. The challenge is knowing which model to reach for without sacrificing quality.

The Pricing Landscape (Per 1M Tokens, April 2026)

ModelInputOutputContext Window
Claude 3.5 Sonnet$3.00$15.00200K
GPT-4o$2.50$10.00128K
Gemini 1.5 Pro$1.25$5.002M
GPT-4o-mini$0.15$0.60128K
Gemini 1.5 Flash$0.075$0.301M
DeepSeek V3$0.07$0.28128K

Cost Drivers Beyond Per-Token Pricing

1. Output Verbosity

Some models are chatty. Claude 3.5 Sonnet tends to write comprehensive explanations, often 2-3x the token count of Gemini Flash for the same task. Your effective cost is input + output, so a cheaper input rate with a verbose model can still be expensive.

2. Context Caching

Anthropic and Gemini both support prompt caching. For repetitive workloads — like coding assistants with the same system prompt — caching can reduce costs by 90%.

3. Thinking Budgets

Claude's extended thinking mode burns extra tokens on internal reasoning before emitting output. This improves quality on complex tasks but doubles or triples the effective cost. Use it only when reasoning depth matters.

Decision Framework

Use this flowchart for every prompt:

  • Simple classification/extraction? → GPT-4o-mini or Gemini Flash
  • Creative writing with nuance? → Claude 3.5 Sonnet
  • Multimodal (images + text)? → GPT-4o or Gemini Pro
  • Massive context (100K+)? → Gemini 1.5 Pro (2M window)
  • Budget constrained prototype? → DeepSeek V3

The AIWorkbench.dev Cost Calculator

Our built-in calculator normalizes these rates and estimates your monthly spend based on daily usage patterns. It factors in context caching, average output length per model, and your selected providers.

Key Takeaway

The most expensive model is the one you use for every task. Match the model to the cognitive load of the prompt. Your wallet is a function of your routing strategy.