Gemini · Fast / Budget · 128K context window

Gemini 2.5 Computer Use pricing for chatbot

$0.0125 per call at 2,000 input / 1,000 output tokens.

Per call

$0.0125

10K calls/mo

$125

Cache savings

0% off input

Batch savings

50% off all

Calculate your Gemini 2.5 Computer Use costs

Adjust token counts, volume, and discount toggles to model your chatbot spend. Prices verified daily against provider pricing pages.

Configure your usage

2,000
100100K
1,000
5050K
10,000
1001M

Estimated cost

Monthly cost
$125
10,000 calls/month
Cost per call$0.0125
Daily cost$4
Input rate$1.25/MTok
Output rate$10.00/MTok
Analyze your real spend

Quick start

Call Gemini 2.5 Computer Use with the Google Generative AI SDK:

import google.generativeai as genai

model = genai.GenerativeModel("gemini-2.5-computer-use")
response = model.generate_content("Your prompt here")
# Cost: ~$0.0125 per call at standard rates
# Input:  $1.25/MTok
# Output: $10.00/MTok

How Gemini 2.5 Computer Use compares on cost

Per-call cost for all models scoring 50+ on chatbot benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001600/call (87% less, 85/100 quality).

What drives chatbot cost

Conversational cost compounds: every turn resends the history, so the tenth message in a thread costs several times the first. Cost grows with the square of conversation length unless you cache the prefix or truncate history. Prompt caching is not an optimization here, it is the difference between a viable and an unviable unit economic.

For Gemini 2.5 Computer Use specifically, that means output tokens cost 8.0x more than input, at $10.00 vs $1.25 per MTok. At this use case’s 2,000/1,000 token split, output accounts for 80% of the $0.0125 per-call cost.

Complete Gemini 2.5 Computer Use pricing breakdown

Standard token rates

Direction$/MTokTokens per call
Input$1.252,000
Output$10.001,000

Prompt caching: 0% off input tokens

Caching drops input cost from $1.25 to $1.25/MTok. For repeated system prompts, that saves $0.0000 per call.

Batch API: 50% off all tokens

Submit requests asynchronously and receive 50% off all token costs. This works best for offline pipelines where latency requirements are flexible.

Monthly cost projections

Monthly volumeCost per callStandard monthlyCached monthlyYou save with caching
10,000 calls$0.0125$125$125$0.0000
50,000 calls$0.0125$625$625$0.0000
100,000 calls$0.0125$1,250$1,250$0.0000
500,000 calls$0.0125$6,250$6,250$0.0000
1,000,000 calls$0.0125$12,500$12,500$0.0000

Gemini 2.5 Computer Use quality benchmarks for chatbot

Benchmark data for chatbot is pending for Gemini 2.5 Computer Use. Test against your own evaluation suite before moving to production.

Performance across all task types

Gemini 2.5 Computer Use scores by task type. Chatbot highlighted.

Task typeConfidence scoreRank out of 72

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 10 weeks old, so treat the scores as directional and validate against your own evals.

Alternative models for chatbot

12 models score 80+ on chatbot benchmarks, sorted by input rate. Cheapest: GPT 5.6 Luna (87% less, 85/100 quality).

ModelProviderInput $/MTokOutput $/MTokQualityPer callvs Gemini
GPT 5.6 LunaGPT$0.20$1.2085/100$0.00160087% cheaper
Claude Haiku 4.5Claude$1.00$5.0086/100$0.00700044% cheaper
Gemini 3.5 FlashGemini$1.50$9.0084/100$0.01204% cheaper
Claude Sonnet 5Claude$2.00$10.0089/100$0.014012% more
GPT 5.6 TerraGPT$2.00$12.0092/100$0.016028% more
Gemini 3.1 ProGemini$2.00$12.0087/100$0.016028% more
GPT 5.4GPT$2.50$15.0091/100$0.020060% more
Claude Sonnet 4.6Claude$3.00$15.0088/100$0.021068% more
GPT 5.6 SolGPT$4.00$20.0091/100$0.0280124% more
Claude Opus 4.8Claude$5.00$25.0085/100$0.0350180% more
GPT 5.5GPT$5.00$30.0090/100$0.0400220% more
Claude Fable 5Claude$10.00$50.0088/100$0.0700460% more

About Gemini 2.5 Computer Use

Provider

Gemini

Tier

Fast / Budget

Context

128K tokens

Released

Not published

Backfilled on 2026-09-23. Prices confirmed by the provider pricing page and the LiteLLM cross-check. Release date not published in a machine-readable source. Not yet benchmarked, so never recommended.

Other models from Gemini

ModelTierInput $/MTokOutput $/MTokContext
Gemini 3.1 ProMid-tier$2.00$12.001,048.576K
Gemini 3.5 FlashFast / Budget$1.50$9.001,048.576K
Gemini 3 FlashFast / Budget$0.50$3.001,048.576K
Gemini 3.5 Flash-LiteFast / Budget$0.30$2.501,048.576K
Gemini 2.5 FlashFast / Budget$0.30$2.501,048.576K
Gemini 2.5 Flash-LiteFast / Budget$0.10$0.401,048.576K
Gemini 2.5 ProMid-tier$1.25$10.001,048.576K
Gemini 3.1 Flash-LiteFast / Budget$0.25$1.501,048.576K
Gemini 3.1 Pro Custom ToolsMid-tier$2.00$12.001,048.576K
Gemini 3.6 FlashFast / Budget$0.75$3.751,048.576K
Gemini 3.7 FlashFast / Budget$0.75$3.751,048.576K
Gemini 3.8 FlashFast / Budget$0.75$3.751,048.576K
Gemini Omni 1.1 FlashFast / Budget$1.50$9.001,048.576K
Gemini Omni FlashFast / Budget$1.50$9.001,048.576K
Gemini Robotics ER 2Fast / Budget$1.00$5.00131.072K

You can compare Gemini 2.5 Computer Use head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions

How much does Gemini 2.5 Computer Use cost for chatbot per API call?

A typical chatbot call using Gemini 2.5 Computer Use costs about $0.0125 per call. This estimate uses 2,000 input tokens and 1,000 output tokens at standard rates. Standard rates are $1.25 per million input tokens and $10.00 per million output tokens.

Is Gemini 2.5 Computer Use the best model for chatbot?

Our benchmark data does not yet include a chatbot ranking for Gemini 2.5 Computer Use. We recommend testing it against your own evaluation criteria before production usage.

What is the cheapest model for chatbot with good quality?

The most affordable model for chatbot above 80/100 quality is GPT 5.6 Luna. It comes from GPT at $0.20 per million input tokens. Output costs $1.20 per million tokens with a quality score of 85/100. Switching from Gemini 2.5 Computer Use to GPT 5.6 Luna saves about 87% per API call.

How can I reduce my Gemini 2.5 Computer Use costs for chatbot?

Three strategies lower Gemini 2.5 Computer Use costs for this task type effectively. Prompt caching gives a 0% discount on input tokens when reusing system prompts. The batch API gives 50% off all tokens for asynchronous processing workloads. Prompt optimization reduces token counts through more concise instructions and context windows. Combining caching with batching brings your cost from $0.0125 to about $0.006250 per call.

How does Gemini 2.5 Computer Use pricing compare to other Gemini models?

Gemini has 15 other models alongside Gemini 2.5 Computer Use today: Gemini 3.1 Pro at $2.00/$12.00 per million tokens (mid-tier), Gemini 3.5 Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini 3 Flash at $0.50/$3.00 per million tokens (fast / budget), Gemini 3.5 Flash-Lite at $0.30/$2.50 per million tokens (fast / budget), Gemini 2.5 Flash at $0.30/$2.50 per million tokens (fast / budget), Gemini 2.5 Flash-Lite at $0.10/$0.40 per million tokens (fast / budget), Gemini 2.5 Pro at $1.25/$10.00 per million tokens (mid-tier), Gemini 3.1 Flash-Lite at $0.25/$1.50 per million tokens (fast / budget), Gemini 3.1 Pro Custom Tools at $2.00/$12.00 per million tokens (mid-tier), Gemini 3.6 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini 3.7 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini 3.8 Flash at $0.75/$3.75 per million tokens (fast / budget), Gemini Omni 1.1 Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini Omni Flash at $1.50/$9.00 per million tokens (fast / budget), Gemini Robotics ER 2 at $1.00/$5.00 per million tokens (fast / budget). The right choice depends on whether your chatbot workload prioritizes quality, cost, or speed.

What context window does Gemini 2.5 Computer Use support?

Gemini 2.5 Computer Use supports a context window of 128K tokens per API call. This sets the maximum combined length of your input prompt and generated response. For chatbot, typical calls use 2,000 input and 1,000 output tokens. That is well within this limit, leaving room for longer prompts or multi-turn conversations.

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