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Claude Sonnet 5.5 vs Gemini 3.8 Flash: API cost

Both models are in our mid-range tier, based on how Anthropic and Google (Gemini API) describe them. Gemini 3.8 Flash is cheaper in all 5 standard workloads priced on both.

The biggest difference is the bulk tagging workload: Claude Sonnet 5.5 costs $5,475 a month against $2,053 for Gemini 3.8 Flash, 2.7× as much. 89% of that difference comes from input tokens: Claude Sonnet 5.5 charges $2.00 per million of them, against $0.75. The gap is narrowest for the cached-prompt assistant workload, where Gemini 3.8 Flash costs 60% less.

Prices on this page last verified on Sources

Monthly cost at five standard workloads

Claude Sonnet 5.5 and Gemini 3.8 Flash monthly cost by workload
WorkloadTokens in / outClaude Sonnet 5.5Gemini 3.8 FlashDifference a monthPricier byMost of the gap
Short chat10,000 requests a day1,000 / 300$1,521$570.31$950.52 (Gemini 3.8 Flash cheaper)2.7×Output tokens
Long-document questions1,000 requests a day30,100 / 500$1,983$743.69$1,239 (Gemini 3.8 Flash cheaper)2.7×Input tokens
Bulk tagging200,000 requests a day400 / 10$5,475$2,053$3,422 (Gemini 3.8 Flash cheaper)2.7×Input tokens
Long-form writing500 requests a day1,500 / 3,000$501.88$188.20$313.67 (Gemini 3.8 Flash cheaper)2.7×Output tokens
Cached-prompt assistant20,000 requests a day8,000 / 400$5,232$2,099$3,133 (Gemini 3.8 Flash cheaper)2.5×Input tokens

Published prices side by side

Per million tokens, for the first price tier of each model (Claude Sonnet 5.5: all prompt lengths; Gemini 3.8 Flash: all prompt lengths).

Claude Sonnet 5.5 and Gemini 3.8 Flash prices per million tokens
PriceClaude Sonnet 5.5Gemini 3.8 Flash
Input$2.00$0.75
Cached input$0.10$0.075
Output$10.00$3.75
Batch input$1.00$0.375
Batch cached inputn/a$0.0375
Batch output$5.00$1.875

Why these two are compared

We only compare models in the same capability tier, read from each provider’s own description of the model. Both are in our mid-range tier:

  • Claude Sonnet 5.5: Provider text: "The best combination of speed and intelligence". Positioned as balancing speed and capability: mid. platform.claude.com (checked )
  • Gemini 3.8 Flash: Provider text: "Our most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, and complex enterprise workflows." Most capable model of the faster Flash line: mid. aistudio.google.com (checked )

Workload assumptions

Short chat

Input tokens per request
Part of the promptTokensCachedWhy
Instructions300NoShort instructions, treated as uncached.
Message and recent turns700NoChanges with every request.
Total1,000None cached
Requests a day: 10,000
A popular in-app assistant.
Output tokens per request: 300
A reply of about 220 words.
Batch API: not used
Real-time replies.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Long-document questions

Input tokens per request
Part of the promptTokensCachedWhy
Document30,000NoAbout 22,000 words, different every time.
Question100NoOne or two sentences.
Total30,100None cached
Requests a day: 1,000
A research or legal team asking questions of whole documents.
Output tokens per request: 500
An answer of about 370 words.
Batch API: not used
Real-time answers.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Bulk tagging

Input tokens per request
Part of the promptTokensCachedWhy
Instructions and labels300NoShort instructions, treated as uncached.
Item100NoA short text.
Total400None cached
Requests a day: 200,000
Items such as tickets, reviews or records tagged as they arrive.
Output tokens per request: 10
One label.
Batch API: not used
Tagged as items arrive.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Long-form writing

Input tokens per request
Part of the promptTokensCachedWhy
Brief and style notes1,500NoDifferent for each piece.
Total1,500None cached
Requests a day: 500
Articles, reports or long emails drafted a day.
Output tokens per request: 3,000
About 2,200 words.
Batch API: not used
Drafts are wanted straight away.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Cached-prompt assistant

Input tokens per request
Part of the promptTokensCachedWhy
Instructions and tool definitions6,000YesThe same on every request, so read from the prompt cache.
Conversation and request2,000NoChanges with every request.
Total8,00075% cached
Requests a day: 20,000
A busy assistant with long instructions and tool definitions.
Output tokens per request: 400
A reply of about 300 words.
Batch API: not used
Real-time replies.

These are stated assumptions for illustration, not measurements. Cached parts are assumed to be read from the prompt cache on every request. Token counts are the same for every model, although providers count tokens differently. Use the calculator to try your own figures.

Your traffic looks different? Enter your own figures in the calculator.

Sources

Sources: aistudio.google.com (checked ); platform.claude.com (checked )

Prices are list prices as each provider publishes them, used unchanged. How the figures are calculated: methodology.