Gemini 3.1 Flash Lite 1M input/output tokens price and performance

Complete Analysis: 2,000,000 tokens for Gemini 3.1 Flash Lite

Complete analysis of pricing, performance, and use cases for Google's Gemini 3.1 Flash Lite model .

$1.750000 Total Cost
2,000,000 Total Tokens
35 minutes, 40.18 seconds Processing Time
935 Effective Tokens/Sec

Click Recalculate to update after making changes

ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.

Select AI Model

Gemini 3.1 Flash Lite
GoogleMax Context: 1,000,000 tokens
$0.25 / $1.5 per 1M tokens
▼
▼
Use Batch API (50% discount)
0%
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

$1.750000 Total Cost
$0.250000 Input Cost
$1.500000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
2,000,000Total Tokens
$0.000875Cost per 1K
1,142,857Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

35m 40s Processing Time
1,000 Tokens/Second
80ms Time to First Token
935 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 3.1 Flash Lite Google 1000000

$1.750000
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✓ Available
🎥
Video Analysis
✓ Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✓ Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $1.750000 Input: $0.250000
Output: $1.500000
Optimized Cost $1.750000 Input: $0.250000
Output: $1.500000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.250000
  • Output Cost: $1.500000
  • Total Cost: $1.750000
  • Cost per 1K tokens: $0.000875
  • Tokens per dollar: 1,142,857 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 1,000 tokens per second and 80ms time to first token:

  • Processing Time: 35 minutes, 40.18 seconds
  • Latency: 80 milliseconds to first token
  • Base Throughput: 1,000 tokens/second
  • Effective Throughput: 935 tokens/second (temperature-adjusted)

Best Use Cases

Cost-effective APIHigh-volume Micro-tasks

Want this applied to YOUR actual stack?

This calculator shows the math for Gemini 3.1 Flash Lite. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

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✨ Market Recommendations AI Model Registry

← Back to Gemini 3.1 Flash Lite
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000,000
Rank AI Model & Provider Total Cost vs Gemini 3.1 Flash Lite
🏆 Llama 4 Scout
Meta AI
 $0.380000 Best Value ↓ 78.3% cheaper
🥈 Grok 4.1 Fast
xAI
 $0.700000 ↓ 60% cheaper
🥉 Grok 4.20 Beta
xAI
 $8.000000 ↑ 357.1% more
#4 Gemini 2.5 Pro
Google
 $17.500000 ↑ 900% more
#5 Gemini 2.5 Pro
Google
 $17.500000 ↑ 900% more
🏆

Llama 4 Scout
Meta AI

$0.380000
vs Gemini 3.1 Flash Lite: ↓ 78.3%
🥈

Grok 4.1 Fast
xAI

$0.700000
vs Gemini 3.1 Flash Lite: ↓ 60%
🥉

Grok 4.20 Beta
xAI

$8.000000
vs Gemini 3.1 Flash Lite: ↑ 357.1%
#4

Gemini 2.5 Pro
Google

$17.500000
vs Gemini 3.1 Flash Lite: ↑ 900%
#5

Gemini 2.5 Pro
Google

$17.500000
vs Gemini 3.1 Flash Lite: ↑ 900%
✨ 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.

Next-Generation Gemini 3.1 Flash Lite Intelligence

Gemini 3.1 Flash Lite is a frontier model from Google optimized for the 2026 AI landscape.

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 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.