Claude vs GPT-4 vs Gemini: Cheapest Model for Long Context (2026)

Our document analysis feature sends 80k tokens per request. Full context, full history. When we looked at the bill, input costs were 2.5x output. We were paying for every token we sent, every time. Long context AI cost adds up fast. The question: which model is cheapest when input dominates? Claude vs GPT-4 vs Gemini for long context — the pricing varies by model and provider.

Long context AI cost: what we found (March 2026)

For high-volume long context, Gemini 2.0 Flash wins: $0.10/1M input. GPT-4o mini is $0.15/1M. Claude Haiku 3 is $0.25/1M. We switched our bulk document summarisation to Gemini Flash and cut that feature's cost by 40%. For flagship models — complex reasoning over long docs — Gemini 2.5 Pro ($1.25/1M) was cheaper than GPT-4.1 ($2/1M) and Claude Sonnet ($3/1M). Your input/output mix will change the math. Claude vs GPT-4 long context: Claude often costs more for input-heavy workloads. Gemini long context pricing tends to be competitive.

Cheapest model for long context: use case matters

The cheapest model for long context depends on your quality bar. For simple summarisation or extraction, the cheaper models held up. For nuanced analysis — contract review, complex Q&A — we stayed on the flagship. One wrong extraction in a legal doc cost more than the token savings. Test on your use case. The numbers tell you the range; your quality bar tells you where to land.

What we did

We split our long-context work: bulk summarisation on Gemini Flash, contract analysis on Claude Sonnet. Our long context AI cost dropped 30% overall. We didn't chase the absolute cheapest for everything — we matched model to task. That's how you optimise Claude vs GPT-4 vs Gemini long context pricing.

Use our model comparison tool to plug in your token volumes. For cost by customer and feature, PerUnit gives you the breakdown.