Claude Sonnet 4.6 vs Gemini 3.1 Pro for 1M-Token RAG Pipelines

Claude Sonnet 4.6 vs Gemini 3.1 Pro
Complete Comparison: 1,000,000 input tokens × 1,000 output tokens
Comparison Mode
⚡ 50% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 50% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Claude Sonnet 4.6
Anthropic
Gemini 3.1 Pro
Google
Calculation Results (Current Inputs) (50% cached)
Input Tokens 1,000,000 1,000,000
Output Tokens 1,000 1,000
Cost Breakdown
Input Cost $0.750000Best $2.000000Worst
Output Cost $0.003750Best $0.009000Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.416250 (rounded ~ $0.42) Best Value $1.109000 (rounded ~ $1.11) Most Expensive
Processing Time 39 minutes, 40.34 seconds Fastest 44 minutes, 37.86 seconds Slowest
Tokens per Second 450Fastest 400Slowest
Time to First Token 200ms Best 220ms Worst
Cost per 1K tokens $0.000416Best $0.001108Worst
Tokens per Dollar 2,404,805Best Value 902,615Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.750000Best $2.000000Worst
Output Cost / 1M (Base) $3.750000Best $9.000000Worst
Input Cost / 1M (Optimized) $0.375000 (rounded ~ $0.38)Best
Optimizations: 50.0% batch
$1.000000Worst
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) $1.875000 (rounded ~ $1.88)Best
Optimizations: 50.0% batch
$4.500000Worst
Optimizations: 50.0% batch
Capabilities & Advanced Features
Images Support ✓ Supported ✓ Supported
Video Support ✗ Not Supported ✓ Supported
Audio Support ✗ Not Supported ✓ Supported
Caching Support
50
✓ Supported ✓ Supported
Batch API Support ✓ Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
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ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.

Select AI Model

Claude Sonnet 4.6
AnthropicMax Context: 1,000,000 tokens
$3 / $15 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

$0.416250 Total Cost
$0.375000 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
1,001,000Total Tokens
$0.000416Cost per 1K
2,404,805Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

39m 40s Processing Time
450 Tokens/Second
200ms Time to First Token
421 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.

Claude Sonnet 4.6 Anthropic 1000000

$0.416250 (rounded ~ $0.42)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 50% Cached 📊 Batch API 🔧 Tools
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.753750 (rounded ~ $0.75) Input: $0.750000
Output: $0.003750
Optimized Cost $0.416250 (rounded ~ $0.42) Input: $0.750000
Output: $0.003750
Unit: $0.000000
Fees: $0.000000
Total Savings $0.337500 (rounded ~ $0.34) 44.8% 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 1,000 output tokens:

  • Input Cost: $0.750000
  • Output Cost: $0.003750
  • Total Cost: $0.416250 (rounded ~ $0.42)
  • Cost per 1K tokens: $0.000416
  • Tokens per dollar: 2,404,805 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 450 tokens per second and 200ms time to first token:

  • Processing Time: 39 minutes, 40.34 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 421 tokens/second (temperature-adjusted)

Best Use Cases

Use Claude for consistent instruction following in text-heavy RAG; use Gemini for multimodal RAG pipelines incorporating video/audio.

Want this applied to YOUR actual stack?

This calculator shows the math for Claude Sonnet 4.6. 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 →

Gemini 3.1 Pro Google 2000000

$1.109000 (rounded ~ $1.11)
Total Cost
⚡ 50% 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) $2.009000 Input: $2.000000
Output: $0.009000
Optimized Cost $1.109000 (rounded ~ $1.11) Input: $2.000000
Output: $0.009000
Unit: $0.000000
Fees: $0.000000
Total Savings $0.900000 44.8% 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 1,000 output tokens:

  • Input Cost: $2.000000
  • Output Cost: $0.009000
  • Total Cost: $1.109000 (rounded ~ $1.11)
  • Cost per 1K tokens: $0.001108
  • Tokens per dollar: 902,615 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, 37.86 seconds
  • Latency: 220 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 374 tokens/second (temperature-adjusted)

Best Use Cases

Use Claude for consistent instruction following in text-heavy RAG; use Gemini for multimodal RAG pipelines incorporating video/audio.

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 →

✨ Market Recommendations AI Model Registry

← Back to Claude Sonnet 4.6
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000
Batch API: Enabled (50% discount)
Cached Tokens: 50%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Claude Sonnet 4.6 vs Gemini 3.1 Pro
🏆 Grok 4.20 Beta
xAI
 $0.276500 (rounded ~ $0.28) Best Value ↓ 33.6% cheaper ↓ 75.1% cheaper
🥈 Gemini 2.5 Pro
Google
 $0.695000 (rounded ~ $0.70) ↑ 67% more ↓ 37.3% cheaper
🥉 Gemini 3.1 Pro
Google
 $1.109000 (rounded ~ $1.11) ↑ 166.4% more Same price
#4 GPT-5.4
OpenAI
 $1.386250 (rounded ~ $1.39) ↑ 233% more ↑ 25% more
#5 GPT-5.4 Thinking
OpenAI
 $1.386250 (rounded ~ $1.39) ↑ 233% more ↑ 25% more
#6 GPT-5.4 Thinking
OpenAI
 $1.386250 (rounded ~ $1.39) ↑ 233% more ↑ 25% more
🏆

Grok 4.20 Beta
xAI

$0.276500 (rounded ~ $0.28)
vs Claude Sonnet 4.6: ↓ 33.6%
vs Gemini 3.1 Pro: ↓ 75.1%
🥈

Gemini 2.5 Pro
Google

$0.695000 (rounded ~ $0.70)
vs Claude Sonnet 4.6: ↑ 67%
vs Gemini 3.1 Pro: ↓ 37.3%
🥉

Gemini 3.1 Pro
Google

$1.109000 (rounded ~ $1.11)
vs Claude Sonnet 4.6: ↑ 166.4%
vs Gemini 3.1 Pro: Same
#4

GPT-5.4
OpenAI

$1.386250 (rounded ~ $1.39)
vs Claude Sonnet 4.6: ↑ 233%
vs Gemini 3.1 Pro: ↑ 25%
#5

GPT-5.4 Thinking
OpenAI

$1.386250 (rounded ~ $1.39)
vs Claude Sonnet 4.6: ↑ 233%
vs Gemini 3.1 Pro: ↑ 25%
#6

GPT-5.4 Thinking
OpenAI

$1.386250 (rounded ~ $1.39)
vs Claude Sonnet 4.6: ↑ 233%
vs Gemini 3.1 Pro: ↑ 25%
✨ 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.

Choosing Between Claude Sonnet 4.6 and Gemini 3.1 Pro

For RAG systems managing large-scale document indexing, selecting the right model involves balancing instruction following and contextual accuracy. Both models operate effectively at the 1-million token scale, making them ideal for enterprise-grade retrieval workflows.

Claude Sonnet 4.6 is frequently the preferred choice for teams that prioritize strict adherence to system prompts and structured formatting. In RAG architectures, this consistency is vital; when your system retrieves complex technical documents, you need a model that maintains a consistent tone and doesn’t stray from provided citations. Its architecture is particularly well-suited for developers who need reliability in complex multi-step instructions.

Conversely, Gemini 3.1 Pro offers distinct advantages if your pipeline integrates multimodal data. Its ability to natively process video and audio alongside text makes it a more versatile asset for companies dealing with unstructured data variety. If your RAG chatbot needs to summarize call transcripts or video meeting logs alongside standard text documents, the integrated architecture of Gemini often reduces latency compared to piping data through separate specialized models.

From a deployment perspective, evaluate your dependency on tool-calling ecosystems. If your infrastructure relies heavily on complex function calling or autonomous agent behavior, Claude’s performance remains industry-leading for stability. However, teams looking for a unified multimodal solution for high-density document analysis may find Gemini’s broader capability set better suited for long-term scalability across diverse data types.

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.