Gemini 3.8 Flash Cost for Retail Customer Support at 15K Tokens

Complete Analysis: 16,000 tokens for Gemini 3.8 Flash
⚡ 50% Cached

Complete analysis of pricing, performance, and use cases for Google's Gemini 3.8 Flash model with 50% Cached.

⚡ Caching Optimized (up to 90% savings)
$0.009938 Total Cost
16,000 Total Tokens
50.53 seconds Processing Time
318 Effective Tokens/Sec

Click Recalculate to update after making changes

Select AI Model

Gemini 3.8 Flash
GoogleMax Context: 1,048,576 tokens
$0.75 / $3.75 per 1M tokens
▼
▼
Use Batch API (50% discount)
50%
Provider-specific multipliers applied after all calculations
Enable for cache discounts
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.

Calculate Token Costs

$0.009938 Total Cost
$0.005625 Input Cost
$0.003750 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
16,000Total Tokens
$0.000621Cost per 1K
1,610,063Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

50.53s Processing Time
340 Tokens/Second
105ms Time to First Token
318 Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 Advanced Options

⚡ Optimization
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data
First 50 hours free, $0.05/hour after
🧠 Reasoning & Thinking
Manual thinking tokens (billed at output rate)
🔧 Special Modes
Enable 6.0x Fast Mode multiplier
📚 Research & Citations
Enable $1.00/$4.00 rates + $10.00/1k search
Enable research tier pricing
Fee per source cited
🎤 Realtime Audio & Video
Session length for billing

Gemini 3.8 Flash Google 1048576

$0.009938
Total Cost
⚡ 50% Cached 🔧 Tools
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✓ Available
🎥
Video Analysis
✓ Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.015000 (rounded ~ $0.02) Input: $0.011250 (rounded ~ $0.01)
Output: $0.003750
Optimized Cost $0.009938 Input: $0.011250 (rounded ~ $0.01)
Output: $0.003750
Unit: $0.000000
Fees: $0.000000
Total Savings $0.005063 (rounded ~ $0.01) 33.8% discount

Detailed Cost Analysis (from Plugin)

For 15,000 input tokens and 1,000 output tokens:

  • Input Cost: $0.011250 (rounded ~ $0.01)
  • Output Cost: $0.003750
  • Total Cost: $0.009938
  • Cost per 1K tokens: $0.000621
  • Tokens per dollar: 1,610,063 tokens
  • Context Window: 1048576 tokens

Speed & Performance Analysis

With a processing speed of 340 tokens per second and 105ms time to first token:

  • Processing Time: 50.53 seconds
  • Latency: 105 milliseconds to first token
  • Base Throughput: 340 tokens/second
  • Effective Throughput: 318 tokens/second (temperature-adjusted)

Best Use Cases

Ideal for retail customer support chatbots that require fastcontext-aware document retrieval and reliable instruction following at scale.

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✨ Market Recommendations AI Model Registry

← Back to Gemini 3.8 Flash
📋 Active Input Parameters
Input Tokens: 15,000
Output Tokens: 1,000
Cached Tokens: 50%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Gemini 3.8 Flash
🏆 Mistral Small 3
Mistral AI
 $0.001125 Best Value ↓ 88.7% cheaper
🥈 Grok Code Fast 1
xAI
 $0.003150 ↓ 68.3% cheaper
🥉 Gemini 3.1 Flash Lite
Google
 $0.003563 ↓ 64.2% cheaper
#4 Gemini 3.5 Flash-Lite
Google
 $0.004975 ↓ 49.9% cheaper
#5 Gemini 2.5 Flash
Google
 $0.004975 ↓ 49.9% cheaper
#6 Mistral Large 3
Mistral AI
 $0.005625 (rounded ~ $0.01) ↓ 43.4% cheaper
#7 Gemini 3.1 Flash
Google
 $0.007125 (rounded ~ $0.01) ↓ 28.3% cheaper
#8 Kimi K2.5
Moonshot AI
 $0.008265 (rounded ~ $0.01) ↓ 16.8% cheaper
#9 Grok Build 0.1
xAI
 $0.010250 ↑ 3.1% more
#10 GPT-5.4 mini
OpenAI
 $0.010688 ↑ 7.5% more
#11 o4-mini Deep Research
OpenAI
 $0.012250 (rounded ~ $0.01) ↑ 23.3% more
#12 Kimi K2.6
Moonshot AI
 $0.012336 (rounded ~ $0.01) ↑ 24.1% more
#13 Kimi K2.7 Code
Moonshot AI
 $0.012336 (rounded ~ $0.01) ↑ 24.1% more
#14 Grok 4.3
xAI
 $0.012813 (rounded ~ $0.01) ↑ 28.9% more
#15 Grok 4.20 Beta
xAI
 $0.012813 (rounded ~ $0.01) ↑ 28.9% more
#16 Claude Haiku 4.5
Anthropic
 $0.013250 (rounded ~ $0.01) ↑ 33.3% more
#17 o4-mini
OpenAI
 $0.013475 (rounded ~ $0.01) ↑ 35.6% more
#18 GPT-5.6 Luna
OpenAI
 $0.014250 (rounded ~ $0.01) ↑ 43.4% more
#19 Gemini 3.6 Flash
Google
 $0.019875 ↑ 100% more
#20 Gemini 2.5 Pro
Google
 $0.020313 ↑ 104.4% more
#21 Gemini 3.5 Flash
Google
 $0.021375 (rounded ~ $0.02) ↑ 115.1% more
#22 Grok 4.6
xAI
 $0.022500 (rounded ~ $0.02) ↑ 126.4% more
#23 Grok 4.5
xAI
 $0.022500 (rounded ~ $0.02) ↑ 126.4% more
#24 Claude Sonnet 5
Anthropic
 $0.026500 (rounded ~ $0.03) ↑ 166.7% more
#25 GPT-5.3 Codex Spark
OpenAI
 $0.028438 (rounded ~ $0.03) ↑ 186.2% more
#26 GPT-5.3 Instant
OpenAI
 $0.028438 (rounded ~ $0.03) ↑ 186.2% more
#27 Gemini 3.1 Pro
Google
 $0.028500 (rounded ~ $0.03) ↑ 186.8% more
#28 GPT-5.4
OpenAI
 $0.035625 (rounded ~ $0.04) ↑ 258.5% more
#29 GPT-5.4 Thinking
OpenAI
 $0.035625 (rounded ~ $0.04) ↑ 258.5% more
#30 GPT-5.6 Terra
OpenAI
 $0.035625 (rounded ~ $0.04) ↑ 258.5% more
#31 Claude Sonnet 4.6
Anthropic
 $0.039750 ↑ 300% more
#32 Claude Opus 4.7
Anthropic
 $0.066250 (rounded ~ $0.07) ↑ 566.7% more
#33 Claude Opus 5
Anthropic
 $0.066250 (rounded ~ $0.07) ↑ 566.7% more
#34 Claude Opus 4.8
Anthropic
 $0.066250 (rounded ~ $0.07) ↑ 566.7% more
#35 Claude Opus 4.6
Anthropic
 $0.066250 (rounded ~ $0.07) ↑ 566.7% more
#36 GPT-5.5
OpenAI
 $0.071250 (rounded ~ $0.07) ↑ 617% more
#37 GPT-5.5 Instant
OpenAI
 $0.071250 (rounded ~ $0.07) ↑ 617% more
#38 GPT-5.6 Sol
OpenAI
 $0.071250 (rounded ~ $0.07) ↑ 617% more
#39 o3 Deep Research
OpenAI
 $0.122500 (rounded ~ $0.12) ↑ 1132.7% more
#40 Claude Fable 5.1
Anthropic
 $0.126875 (rounded ~ $0.13) ↑ 1176.7% more
#41 Claude Mythos 5.1
Anthropic
 $0.126875 (rounded ~ $0.13) ↑ 1176.7% more
#42 Claude Fable 5
Anthropic
 $0.132500 (rounded ~ $0.13) ↑ 1233.3% more
#43 Claude Mythos 5
Anthropic
 $0.132500 (rounded ~ $0.13) ↑ 1233.3% more
#44 GPT-6 Astra
OpenAI
 $0.132500 (rounded ~ $0.13) ↑ 1233.3% more
#45 o3 Pro
OpenAI
 $0.245000 (rounded ~ $0.25) ↑ 2365.4% more
#46 GPT-5.2 Pro
OpenAI
 $0.341250 (rounded ~ $0.34) ↑ 3334% more
#47 GPT-5.2 Pro
OpenAI
 $0.341250 (rounded ~ $0.34) ↑ 3334% more
🏆

Mistral Small 3
Mistral AI

$0.001125
vs Gemini 3.8 Flash: ↓ 88.7%
🥈

Grok Code Fast 1
xAI

$0.003150
vs Gemini 3.8 Flash: ↓ 68.3%
🥉

Gemini 3.1 Flash Lite
Google

$0.003563
vs Gemini 3.8 Flash: ↓ 64.2%
#4

Gemini 3.5 Flash-Lite
Google

$0.004975
vs Gemini 3.8 Flash: ↓ 49.9%
#5

Gemini 2.5 Flash
Google

$0.004975
vs Gemini 3.8 Flash: ↓ 49.9%
#6

Mistral Large 3
Mistral AI

$0.005625 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↓ 43.4%
#7

Gemini 3.1 Flash
Google

$0.007125 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↓ 28.3%
#8

Kimi K2.5
Moonshot AI

$0.008265 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↓ 16.8%
#9

Grok Build 0.1
xAI

$0.010250
vs Gemini 3.8 Flash: ↑ 3.1%
#10

GPT-5.4 mini
OpenAI

$0.010688
vs Gemini 3.8 Flash: ↑ 7.5%
#11

o4-mini Deep Research
OpenAI

$0.012250 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 23.3%
#12

Kimi K2.6
Moonshot AI

$0.012336 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 24.1%
#13

Kimi K2.7 Code
Moonshot AI

$0.012336 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 24.1%
#14

Grok 4.3
xAI

$0.012813 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 28.9%
#15

Grok 4.20 Beta
xAI

$0.012813 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 28.9%
#16

Claude Haiku 4.5
Anthropic

$0.013250 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 33.3%
#17

o4-mini
OpenAI

$0.013475 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 35.6%
#18

GPT-5.6 Luna
OpenAI

$0.014250 (rounded ~ $0.01)
vs Gemini 3.8 Flash: ↑ 43.4%
#19

Gemini 3.6 Flash
Google

$0.019875
vs Gemini 3.8 Flash: ↑ 100%
#20

Gemini 2.5 Pro
Google

$0.020313
vs Gemini 3.8 Flash: ↑ 104.4%
#21

Gemini 3.5 Flash
Google

$0.021375 (rounded ~ $0.02)
vs Gemini 3.8 Flash: ↑ 115.1%
#22

Grok 4.6
xAI

$0.022500 (rounded ~ $0.02)
vs Gemini 3.8 Flash: ↑ 126.4%
#23

Grok 4.5
xAI

$0.022500 (rounded ~ $0.02)
vs Gemini 3.8 Flash: ↑ 126.4%
#24

Claude Sonnet 5
Anthropic

$0.026500 (rounded ~ $0.03)
vs Gemini 3.8 Flash: ↑ 166.7%
#25

GPT-5.3 Codex Spark
OpenAI

$0.028438 (rounded ~ $0.03)
vs Gemini 3.8 Flash: ↑ 186.2%
#26

GPT-5.3 Instant
OpenAI

$0.028438 (rounded ~ $0.03)
vs Gemini 3.8 Flash: ↑ 186.2%
#27

Gemini 3.1 Pro
Google

$0.028500 (rounded ~ $0.03)
vs Gemini 3.8 Flash: ↑ 186.8%
#28

GPT-5.4
OpenAI

$0.035625 (rounded ~ $0.04)
vs Gemini 3.8 Flash: ↑ 258.5%
#29

GPT-5.4 Thinking
OpenAI

$0.035625 (rounded ~ $0.04)
vs Gemini 3.8 Flash: ↑ 258.5%
#30

GPT-5.6 Terra
OpenAI

$0.035625 (rounded ~ $0.04)
vs Gemini 3.8 Flash: ↑ 258.5%
#31

Claude Sonnet 4.6
Anthropic

$0.039750
vs Gemini 3.8 Flash: ↑ 300%
#32

Claude Opus 4.7
Anthropic

$0.066250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 566.7%
#33

Claude Opus 5
Anthropic

$0.066250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 566.7%
#34

Claude Opus 4.8
Anthropic

$0.066250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 566.7%
#35

Claude Opus 4.6
Anthropic

$0.066250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 566.7%
#36

GPT-5.5
OpenAI

$0.071250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 617%
#37

GPT-5.5 Instant
OpenAI

$0.071250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 617%
#38

GPT-5.6 Sol
OpenAI

$0.071250 (rounded ~ $0.07)
vs Gemini 3.8 Flash: ↑ 617%
#39

o3 Deep Research
OpenAI

$0.122500 (rounded ~ $0.12)
vs Gemini 3.8 Flash: ↑ 1132.7%
#40

Claude Fable 5.1
Anthropic

$0.126875 (rounded ~ $0.13)
vs Gemini 3.8 Flash: ↑ 1176.7%
#41

Claude Mythos 5.1
Anthropic

$0.126875 (rounded ~ $0.13)
vs Gemini 3.8 Flash: ↑ 1176.7%
#42

Claude Fable 5
Anthropic

$0.132500 (rounded ~ $0.13)
vs Gemini 3.8 Flash: ↑ 1233.3%
#43

Claude Mythos 5
Anthropic

$0.132500 (rounded ~ $0.13)
vs Gemini 3.8 Flash: ↑ 1233.3%
#44

GPT-6 Astra
OpenAI

$0.132500 (rounded ~ $0.13)
vs Gemini 3.8 Flash: ↑ 1233.3%
#45

o3 Pro
OpenAI

$0.245000 (rounded ~ $0.25)
vs Gemini 3.8 Flash: ↑ 2365.4%
#46

GPT-5.2 Pro
OpenAI

$0.341250 (rounded ~ $0.34)
vs Gemini 3.8 Flash: ↑ 3334%
#47

GPT-5.2 Pro
OpenAI

$0.341250 (rounded ~ $0.34)
vs Gemini 3.8 Flash: ↑ 3334%
✨ How recommendations work (v8.6.0): We scan all active models in the registry and only include those that support ALL your current inputs. For token-based models, we check if they can handle your token counts. For special pricing models (OCR, video, audio), we verify they have the correct pricing structure. Features marked requested were in your inputs but not supported by that model. Now using official provider pricing without reseller markups.

Retail customer support teams frequently face a balancing act: providing accurate, context-aware responses to product inquiries while managing the high costs of real-time AI interactions. Gemini 3.8 Flash has emerged as a compelling choice for these RAG (retrieval-augmented generation) workloads, particularly for chatbots that must ingest large amounts of product documentation, size guides, and return policies per query.

What makes this model particularly effective for retail environments is its optimized attention mechanism, which is designed to handle the multi-step reasoning often required to navigate complex return policies or inventory status checks. Unlike earlier flash-tier models that might struggle with the nuances of brand tone or specific policy exceptions, this iteration demonstrates a marked improvement in instruction following and output reliability. When a user asks about a specific size or fit, the model can effectively parse retrieved documentation, verify against current inventory metadata, and maintain a consistent, helpful tone.

For marketing and support managers, the decision to pivot to this model often centers on its latency-to-performance ratio. Because retail support requires near-instant gratification to prevent customer churn, the model’s ability to handle 15K-token input windows without significant latency spikes is a distinct advantage. Furthermore, its proficiency with tool calling makes it a natural fit for connecting to existing e-commerce databases, allowing the chatbot to do more than just summarize text—it can act as a bridge between the customer and the store’s backend systems.

Frequently Asked Questions

How accurate are these AI model cost calculations?
Our calculations are based on official pricing from each provider (Google, OpenAI, Anthropic, Meta, xAI, Perplexity, DeepSeek, Mistral) and are updated regularly. We account for all factors including multimodal inputs, caching discounts, batch API pricing, tool usage multipliers, OCR processing, audio minutes, silence fees, and research mode pricing. Note: Reseller markups and dedicated instance multipliers have been removed to reflect official provider pricing.
How does prompt caching work?
Caching discounts vary by provider: Google and OpenAI offer 90% discounts on cached input tokens. Anthropic uses write (1.25x) and read (0.10x) multipliers. Savings are applied to the token portion only, not unit-based fees.
How do Market Recommendations work (v8.6.0)?
Our recommendation engine scans the entire model registry and only includes models that support ALL your current input parameters (tokens, images, video, audio, OCR, tools, batch API, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options that can handle your complete workflow. Special pricing models (OCR, video, audio, image generation) are properly handled and only appear when their specific input types are requested. v8.6.0 removes reseller markups (20% buffer) and dedicated instance multipliers to reflect official provider pricing.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 50+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), provides optimization recommendations, and now offers intelligent market matching to find the best alternatives for your specific needs.

Related model pricing

Gemini 3.8 Flash currently costs $0.75 / $3.75 per 1M tokens. These are the models worth pricing against it, taken live from the tracked registry.

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