Cost per 1M Tokens: Gemini 3.1 Pro vs Nemotron 3 Super for Orchestration

Gemini 3.1 Pro vs Nemotron 3 Super
Complete Comparison: 1,000,000 input tokens × 2,000 output tokens
Comparison Mode
⚡ 10% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 10% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Gemini 3.1 Pro
Google
Nemotron 3 Super
Mistral AI
Calculation Results (Current Inputs) (10% cached)
Input Tokens 1,000,000 1,000,000
Output Tokens 2,000 2,000
Cost Breakdown
Input Cost $2.000000Worst $0.075000 (rounded ~ $0.08)Best
Output Cost $0.018000 (rounded ~ $0.02)Worst $0.000410Best
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $1.838000 (rounded ~ $1.84) Most Expensive $0.068660 (rounded ~ $0.07) Best Value
Processing Time 44 minutes, 40.53 seconds Slowest 25 minutes, 31.81 seconds Fastest
Tokens per Second 400Slowest 700Fastest
Time to First Token 220ms Worst 120ms Best
Cost per 1K tokens $0.001834Worst $0.000069Best
Tokens per Dollar 545,158Worst Value 14,593,650Best Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $2.000000Worst $0.075000 (rounded ~ $0.08)Best
Output Cost / 1M (Base) $9.000000Worst $0.205000 (rounded ~ $0.21)Best
Input Cost / 1M (Optimized) $1.000000Worst
Optimizations: 50.0% batch
$0.037500 (rounded ~ $0.04)Best
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) $4.500000Worst
Optimizations: 50.0% batch
$0.102500 (rounded ~ $0.10)Best
Optimizations: 50.0% batch
Capabilities & Advanced Features
Images Support ✓ Supported ✗ Not Supported
Video Support ✓ Supported ✗ Not Supported
Audio Support ✓ Supported ✗ Not Supported
Caching Support
10
✓ Supported ✓ Supported
Batch API Support ✓ Supported ✓ Supported
Tool Usage Support ✓ Supported ✗ Not Supported
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2

Second Model

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All other parameters will be preserved from the current comparison.

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Select AI Model

Gemini 3.1 Pro
GoogleMax Context: 2,000,000 tokens
$2 / $12 per 1M tokens (Tier 1)
State-dependent pricing active. Current tier: Standard
▼
▼
Use Batch API (50% discount)
10%
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

$1.838000 Total Cost
$1.800000 Input Cost
$0.018000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
1,002,000Total Tokens
$0.001834Cost per 1K
545,158Tokens per $
🔄 Dynamic Tier Pricing Active: Using Premium pricing (tier2) based on token volume.
📊 Advanced Cost Breakdown

Processing Speed

44m 40s Processing Time
400 Tokens/Second
220ms Time to First Token
374 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
📊 Multiple Models Detected: This page contains data for 2 models. See the detailed comparison table above, and switch between models using tabs below.

Gemini 3.1 Pro Google 2000000

$1.838000 (rounded ~ $1.84)
Total Cost
⚡ 10% Cached 📊 Batch API 🔧 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) $2.018000 (rounded ~ $2.02) Input: $2.000000
Output: $0.018000 (rounded ~ $0.02)
Optimized Cost $1.838000 (rounded ~ $1.84) Input: $2.000000
Output: $0.018000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.180000 8.9% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount
📊 Dynamic Tier
Premium
tier2 pricing based on 0 tokens

Detailed Cost Analysis (from Plugin)

For 1,000,000 input tokens and 2,000 output tokens:

  • Input Cost: $2.000000
  • Output Cost: $0.018000 (rounded ~ $0.02)
  • Total Cost: $1.838000 (rounded ~ $1.84)
  • Cost per 1K tokens: $0.001834
  • Tokens per dollar: 545,158 tokens
  • Context Window: 2000000 tokens

Speed & Performance Analysis

With a processing speed of 400 tokens per second and 220ms time to first token:

  • Processing Time: 44 minutes, 40.53 seconds
  • Latency: 220 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 374 tokens/second (temperature-adjusted)

Best Use Cases

This comparison is vital for agencies seeking a balance between advanced multimodal capabilities and aggressive cost-efficiency in their AI orchestration layers.

Want this applied to YOUR actual stack?

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

Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.

Get my instant AI audit — $39 →

Nemotron 3 Super Mistral AI 1000000

$0.068660 (rounded ~ $0.07)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 10% Cached 📊 Batch API 🔧 Tools
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available requested
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.075410 (rounded ~ $0.08) Input: $0.075000 (rounded ~ $0.08)
Output: $0.000410
Optimized Cost $0.068660 (rounded ~ $0.07) Input: $0.075000 (rounded ~ $0.08)
Output: $0.000410
Unit: $0.000000
Fees: $0.000000
Total Savings $0.006750 (rounded ~ $0.01) 9.0% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount

Detailed Cost Analysis (from Plugin)

For 1,000,000 input tokens and 2,000 output tokens:

  • Input Cost: $0.075000 (rounded ~ $0.08)
  • Output Cost: $0.000410
  • Total Cost: $0.068660 (rounded ~ $0.07)
  • Cost per 1K tokens: $0.000069
  • Tokens per dollar: 14,593,650 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 700 tokens per second and 120ms time to first token:

  • Processing Time: 25 minutes, 31.81 seconds
  • Latency: 120 milliseconds to first token
  • Base Throughput: 700 tokens/second
  • Effective Throughput: 654 tokens/second (temperature-adjusted)

Best Use Cases

This comparison is vital for agencies seeking a balance between advanced multimodal capabilities and aggressive cost-efficiency in their AI orchestration layers.

Want this applied to YOUR actual stack?

This calculator shows the math for Nemotron 3 Super. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.

Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.

Get my instant AI audit — $39 →

✨ Market Recommendations AI Model Registry

← Back to Gemini 3.1 Pro
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 2,000
Batch API: Enabled (50% discount)
Cached Tokens: 10%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Gemini 3.1 Pro vs Nemotron 3 Super
🏆 Grok 4.20 Beta
xAI
 $0.458000 (rounded ~ $0.46) Best Value ↓ 75.1% cheaper ↑ 567.1% more
🥈 Gemini 2.5 Pro
Google
 $1.152500 (rounded ~ $1.15) ↓ 37.3% cheaper ↑ 1578.6% more
🥉 GPT-5.4
OpenAI
 $2.297500 (rounded ~ $2.30) ↑ 25% more ↑ 3246.2% more
#4 GPT-5.4 Thinking
OpenAI
 $2.297500 (rounded ~ $2.30) ↑ 25% more ↑ 3246.2% more
#5 GPT-5.4 Thinking
OpenAI
 $2.297500 (rounded ~ $2.30) ↑ 25% more ↑ 3246.2% more
🏆

Grok 4.20 Beta
xAI

$0.458000 (rounded ~ $0.46)
vs Gemini 3.1 Pro: ↓ 75.1%
vs Nemotron 3 Super: ↑ 567.1%
🥈

Gemini 2.5 Pro
Google

$1.152500 (rounded ~ $1.15)
vs Gemini 3.1 Pro: ↓ 37.3%
vs Nemotron 3 Super: ↑ 1578.6%
🥉

GPT-5.4
OpenAI

$2.297500 (rounded ~ $2.30)
vs Gemini 3.1 Pro: ↑ 25%
vs Nemotron 3 Super: ↑ 3246.2%
#4

GPT-5.4 Thinking
OpenAI

$2.297500 (rounded ~ $2.30)
vs Gemini 3.1 Pro: ↑ 25%
vs Nemotron 3 Super: ↑ 3246.2%
#5

GPT-5.4 Thinking
OpenAI

$2.297500 (rounded ~ $2.30)
vs Gemini 3.1 Pro: ↑ 25%
vs Nemotron 3 Super: ↑ 3246.2%
✨ 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.

Balancing Cost and Capability in Orchestration

For translation agencies building AI-driven orchestration layers, selecting models that balance performance and cost is key. This comparison highlights Google’s Gemini 3.1 Pro against Mistral AI’s Nemotron 3 Super, offering distinct value propositions for orchestrator and worker agent patterns. Gemini 3.1 Pro provides advanced multimodal capabilities and a substantial 2 million token context window, making it versatile for diverse orchestration needs that might involve more than just text processing. Its broad understanding can be an asset for complex tasks. Nemotron 3 Super, on the other hand, offers remarkable cost-efficiency for text-based reasoning, a common requirement in AI orchestration. Its 1 million token context window and strong performance on reasoning tasks make it a highly competitive option for agencies focused on maximizing throughput for text-centric agent workflows. Evaluating these two allows for a strategic decision: whether Gemini’s extended multimodal features and larger context justify its pricing, or if Nemotron’s aggressive pricing for robust reasoning power offers a more pragmatic path to scaling sophisticated agent 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.