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Gemini API pricing explained per task

Gemini 3.8 Flash, 3.5 Flash-Lite and 3.1 Pro, priced by the job instead of by the token.

By Piotr Olszewski · Oct 11, 2026 · prices as of Oct 18, 2026

Gemini API pricing is a per-million-token rate for input, output and cached input, but your bill depends on how many tokens each task uses. Gemini 3.8 Flash and Gemini 3.1 Pro Preview both reason by default (my data lists "always"), and reasoning tokens are billed as output. In my measurements, Gemini 3.8 Flash was cheaper per task than 3.1 Pro Preview on every task I ran, but it was not the cheapest option against OpenAI and Anthropic counterparts.

List prices vs. cost per task

Per-token list prices are a starting point, not the answer. A model with a low input price can still be expensive if it writes long reasoning traces. My methodology counts reasoning tokens as output tokens, so they show up in the bill.

List price per 1M tokens for the Google models and their closest OpenAI and Anthropic counterparts:

ModelInputOutputCached inputLMArena Text
Gemini 3.8 Flash$0.75$3.75$0.0751496
GPT-5.4 Mini$0.75$4.50$0.0751447
Gemini 3.1 Pro Preview$2.00$12.00$0.201487
GPT-6.1 Sol$2.00$10.00$0.101476
Claude Sonnet 5.5$2.00$10.00$0.101476
Claude Opus 5.5$4.00$20.00$0.201507

Gemini 3.8 Flash matches GPT-5.4 Mini on input and cached input, and its output is cheaper. Gemini 3.1 Pro Preview has a higher output price than GPT-6.1 Sol or Claude Sonnet 5.5. Claude Opus 5.5 is the most expensive of the group per token.

Reasoning is on by default

Both models have reasoning always on in my data. Thinking tokens are billed at the output rate, so token counts matter as much as list price.

Reasoning loads varied by task. On the spreadsheet task, Gemini 3.8 Flash used 7,100 reasoning tokens and Gemini 3.1 Pro Preview used 4,358. On code review, Gemini 3.8 Flash used 2,074 output tokens and no reasoning tokens in my run, while 3.1 Pro Preview used 1,368 output and 7,256 reasoning tokens. That difference explains most of the gap in the code review bill.

Cost per task for Gemini 3.8 Flash

These are measured results: one run per task, default settings, via OpenRouter, output capped at 16,000 tokens.

TaskGemini 3.8 FlashMedian of 326 models
Answer a chat question0.61¢ ($6.14 per 1,000)0.24¢
Summarize a 20-page PDF1.4¢ ($14.24 per 1,000)0.83¢
Analyze a 200-row spreadsheet3.5¢ ($35.17 per 1,000)2.1¢
Review 500 lines of code1.2¢ ($11.68 per 1,000)1.4¢

Gemini 3.8 Flash is above the median on three tasks and below it on code review. On chat it is close to GPT-6.1 Sol at 0.67¢.

Pro tier: Gemini vs. OpenAI vs. Anthropic

Cost per task for Gemini 3.1 Pro Preview and its closest rivals:

TaskGemini 3.1 Pro PreviewGPT-6.1 SolClaude Sonnet 5.5Claude Opus 5.5
Chat2.1¢0.67¢1.3¢2.5¢
PDF summary4.6¢3.1¢4.5¢8.9¢
Spreadsheet7.5¢8.4¢17¢34¢
Code review11¢4.9¢8.0¢16¢

GPT-6.1 Sol was cheaper than Gemini 3.1 Pro Preview on chat, PDF and code review. On the spreadsheet task, Gemini 3.1 Pro Preview was cheaper than GPT-6.1 Sol and both Claude models. Claude Sonnet 5.5 and Claude Opus 5.5 hit the 16,000-token cap on that task, which inflated their bills.

For the live rankings, see the chat task page, PDF summary, spreadsheet analysis and code review.

#ModelCost per taskText scoreTokens in / outBasis
1Z.ai logo
GLM 5.3 FlashZ.ai
0.04¢$0.36 / 1,000
147448 / 1,782measured best value
2OpenAI logo
GPT-6 LunaOpenAI
0.06¢$0.59 / 1,000
144345 / 1,179measured
3Anthropic logo
Claude Haiku 5.5Anthropic
0.07¢$0.66 / 1,000
-61 / 1,299measured
4Alibaba Qwen logo
Qwen3.8 FlashAlibaba Qwen
0.08¢$0.76 / 1,000
-88 / 1,598measured
5Mistral logo
Mistral Small 4Mistral
0.08¢$0.83 / 1,000
-40 / 1,377estimated
6Xiaomi logo
MiMo-V2.6-ProXiaomi
0.09¢$0.90 / 1,000
1479206 / 933estimated best value
7DeepSeek logo
DeepSeek V4.1 FlashDeepSeek
0.09¢$0.91 / 1,000
147565 / 6,320measured
8Meta logo
Llama 4 MaverickMeta
0.11¢$1.06 / 1,000
132787 / 1,592estimated
9MiniMax logo
MiniMax M3MiniMax
0.12¢$1.18 / 1,000
1441205 / 929measured
10Cohere logo
Command A+Cohere
0.15¢$1.46 / 1,000
-205 / 930estimated

Cheaper Google options

Gemini 3.1 Flash Lite cost 0.25¢ on the chat task and Gemini 3.5 Flash Lite cost 0.41¢, both estimated. On code review, Gemini 3.1 Flash Lite was estimated at 0.44¢, well under Gemini 3.8 Flash at 1.2¢. The cheapest chat answer in my set was GPT-6 Luna at 0.06¢ (measured).

The tokenizer effect

The same English document produces different token counts by provider. Against OpenAI at 1.00, Anthropic comes in at 1.39 and Google at 0.98. A higher token count raises the cost of the same input.

Per-token price alone can mislead. Claude Haiku 5.5 lists at $0.10 input and $0.50 output, well below Gemini 3.8 Flash, and it was cheaper on the PDF task (0.22¢ vs 1.4¢). On code review it cost 0.66¢ against 1.2¢. Token counts and reasoning length decide the rest.

Gemini 3.8 Flash pricing is promotional

Google lists Gemini 3.8 Flash and 3.6 Flash at $0.75 input and $3.75 output per 1M tokens until December 31, 2026. The official page says the price doubles on January 1, 2027. Every Gemini 3.8 Flash figure here reflects the promotional rate. For 2027 budgets, use the post-promotion price from Google's pricing page.

Estimate your own cost

Multiply list prices by your task's token counts, including reasoning tokens. The calculator does this for you. Check context size and reasoning mode on the Gemini 3.8 Flash model page before choosing.

FAQ

Is Gemini 3.8 Flash cheaper than GPT-6.1 Sol per task?

In my data, yes on all four tasks: 0.61¢ vs 0.67¢ on chat, 1.4¢ vs 3.1¢ on PDF, 3.5¢ vs 8.4¢ on the spreadsheet and 1.2¢ vs 4.9¢ on code review. This is at the promotional Gemini price.

Why does Gemini 3.1 Pro Preview cost more per task than Gemini 3.8 Flash?

Its list price is higher at $2.00 input and $12.00 output, and on code review it also used 7,256 reasoning tokens against none for Gemini 3.8 Flash. That put code review at 11¢ vs 1.2¢.

Will Gemini 3.8 Flash stay at the current price?

No. Google lists $0.75 input and $3.75 output until December 31, 2026, and says the price doubles on January 1, 2027.