Gemini vs GPT: API Pricing Compared
Side-by-side Gemini and GPT API pricing on the same workload. Google prices its whole catalogue as a workhorse; OpenAI spans a far wider range.
Short answer
Their cheap tiers are close. The difference is that Google has no frontier-priced model at all, so its ceiling is a fraction of OpenAI's.
Prices verified 2026-08-15. Set your own token counts below, because the ranking changes with workload shape.
| Model | Input | Output | Monthly total | vs cheapest |
|---|---|---|---|---|
GPT-5 nano OpenAI gpt-5-nano | $13.80 | $6.40 | $20.20 | 1.0x |
Gemini 2.5 Flash-Lite Google gemini-2.5-flash-lite | $27.60 | $6.40 | $34.00 | 1.7x |
GPT-5.6 Luna OpenAI gpt-5.6-luna | $55.20 | $19.20 | $74.40 | 3.7x |
GPT-5.4 nano OpenAI gpt-5.4-nano | $55.20 | $20.00 | $75.20 | 3.7x |
Gemini 3.1 Flash-Lite Google gemini-3.1-flash-lite | $69.00 | $24.00 | $93.00 | 4.6x |
GPT-5 mini OpenAI gpt-5-mini | $69.00 | $32.00 | $101.00 | 5.0x |
Gemini 3.5 Flash-Lite Google gemini-3.5-flash-lite | $82.80 | $40.00 | $122.80 | 6.1x |
Gemini 2.5 Flash Google gemini-2.5-flash | $82.80 | $40.00 | $122.80 | 6.1x |
Gemini 3.7 Flash Google gemini-3.7-flash | $207.00 | $60.00 | $267.00 | 13.2x |
Gemini 3.6 Flash Google gemini-3.6-flash | $207.00 | $60.00 | $267.00 | 13.2x |
GPT-5.4 mini OpenAI gpt-5.4-mini | $207.00 | $72.00 | $279.00 | 13.8x |
GPT-5.1 OpenAI gpt-5.1 | $345.00 | $160.00 | $505.00 | 25.0x |
Gemini 3.5 Flash Google gemini-3.5-flash | $414.00 | $144.00 | $558.00 | 27.6x |
GPT-5.6 Terra OpenAI gpt-5.6-terra | $552.00 | $192.00 | $744.00 | 36.8x |
Gemini 3.1 Pro (Preview) Google gemini-3.1-pro-preview | $552.00 | $192.00 | $744.00 | 36.8x |
GPT-4.1 OpenAI gpt-4.1 | $660.00 | $128.00 | $788.00 | 39.0x |
GPT-5.4 OpenAI gpt-5.4 | $690.00 | $240.00 | $930.00 | 46.0x |
GPT-4o OpenAI gpt-4o | $1,050 | $160.00 | $1,210 | 59.9x |
GPT-5.6 Sol OpenAI gpt-5.6-sol | $1,380 | $480.00 | $1,860 | 92.1x |
GPT-5.5 OpenAI gpt-5.5 | $1,380 | $480.00 | $1,860 | 92.1x |
GPT-5.5 Pro OpenAI gpt-5.5-pro | $18,000 | $2,880 | $20,880 | 1033.7x |
Across the models shown, this workload ranges from $20.20 to $20,880 a month, a 1034x spread. Model choice is almost always a larger lever than prompt optimisation.
Prices are USD per million tokens, taken from each provider's own pricing page and last verified on 2026-08-15. Standard tier only: enterprise discounts, committed-use pricing, and free tiers are not modelled. Verify against Anthropic, OpenAI, Google, xAI before committing budget.
Comparing something else? See the other head-to-heads or use the full calculator across all four providers.
How to use Gemini vs GPT: API Pricing Compared
Describe one request
Enter the input and output tokens for a single typical request, or pick a preset. The table is fixed to Google and OpenAI.
Set volume and caching
Add your monthly request count, then set the share of input tokens served from the prompt cache. Caching usually moves the answer more than the choice of provider does.
Compare the monthly bill
Models are ranked cheapest first across both providers, with the multiple over the cheapest option so you can see whether a switch is worth the migration.
Two catalogues with completely different shapes
At the cheap end these two are genuinely comparable. Google's least expensive model runs a little under twice OpenAI's least expensive on the same workload, which is close enough that capability, latency and rate limits should decide it rather than price.
The catalogues diverge sharply at the other end. Google's most expensive model costs a small fraction of OpenAI's most expensive, because Google has not shipped anything priced like a reasoning-heavy Pro tier. Everything Google sells is priced as a workhorse.
The practical consequence is that Google's pricing is easy to forecast and hard to blow up. The spread across its entire range is roughly twentyfold, against roughly a thousandfold on OpenAI. If your main risk is an unpredictable bill rather than a high one, that compression is worth more than any individual rate.
What to check before switching on price
Google publishes context windows of about 1,048,576 tokens on its larger models, effectively matching OpenAI's largest. Neither number is the real constraint, since retrieval accuracy falls off long before a million tokens, but it does mean a long-context workload is not a reason to pick one over the other.
Preview models are the trap on the Google side. A model marked preview can change price, change behaviour, or be withdrawn, so building a cost model on one is building on something the provider has not committed to. Where a preview model is the cheapest row in the table below, treat it as an indication rather than a plan.
Free tiers are not modelled here. Google has historically offered a generous free allowance on some models, which can make small projects effectively free and makes the paid comparison irrelevant until you outgrow it.
Frequently Asked Questions
Is Gemini cheaper than GPT?
At the budget end they are close, with Google's cheapest model costing a little under twice OpenAI's cheapest on the same workload. Across the rest of the range Google is generally cheaper, mostly because it does not sell anything at OpenAI's top price point. Compare at your own token counts rather than on headline rates.
Why is Google's most expensive model so much cheaper than OpenAI's?
Google has not shipped a reasoning-heavy tier priced the way OpenAI prices its Pro models. Its catalogue is positioned as high-volume workhorse models rather than as a premium tier, so the ceiling is far lower. That makes budgets predictable, and it also means there is no Google row to compare against OpenAI's most capable model on price.
Should I use a Gemini preview model in production?
Be careful. Preview models can change price or behaviour, or be withdrawn, and none of that is covered by a stability commitment. They are worth benchmarking and worth pricing, but a cost model built on a preview rate is built on a number the provider has not promised to keep.
Do these prices include the free tier?
No. Every figure here is standard paid list pricing. Google has offered free allowances on some models, which can cover a small project entirely, so check the current free tier before assuming you will pay anything at low volume.
Suggested Tools
LLM API Cost Calculator
Compare what a workload costs across Anthropic, OpenAI, Google and xAI, including prompt caching, batch rates and long-context tiers.
Token Counter & Context Visualizer
Paste a prompt or file to estimate its token count, see how much of each model's context window it fills, and what it costs to send.