Claude Opus 4.7 vs Gemini 3.1 Pro for 1M-Token Financial RAG Pipelines

Claude Opus 4.7 vs Gemini 3.1 Pro
Complete Comparison: 1,000,000 input tokens × 5,000 output tokens
Comparison Mode
⚡ 30% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 30% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Claude Opus 4.7
Anthropic
Gemini 3.1 Pro
Google
Calculation Results (Current Inputs) (30% cached)
Input Tokens 1,000,000 1,000,000
Output Tokens 5,000 5,000
Cost Breakdown
Input Cost $1.250000Best $2.000000Worst
Output Cost $0.031250 (rounded ~ $0.03)Best $0.045000 (rounded ~ $0.05)Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.943750 (rounded ~ $0.94) Best Value $1.505000 (rounded ~ $1.51) Most Expensive
Processing Time 1 hour, 7 minutes, 38.83 seconds Slowest 43 minutes, 58.30 seconds Fastest
Tokens per Second 260Slowest 400Fastest
Time to First Token 400ms Worst 220ms Best
Cost per 1K tokens $0.000939Best $0.001498Worst
Tokens per Dollar 1,064,901Best Value 667,774Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $1.250000Best $2.000000Worst
Output Cost / 1M (Base) $6.250000Best $9.000000Worst
Input Cost / 1M (Optimized) $0.625000 (rounded ~ $0.63)Best
Optimizations: 50.0% batch
$1.000000Worst
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) $3.125000 (rounded ~ $3.13)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
30
✓ 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 Opus 4.7
AnthropicMax Context: 1,000,000 tokens
$5 / $25 per 1M tokens
▼
▼
Use Batch API (50% discount)
30%
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

$0.943750 Total Cost
$0.875000 Input Cost
$0.031250 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
1,005,000Total Tokens
$0.000939Cost per 1K
1,064,901Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

67m 38s Processing Time
260 Tokens/Second
400ms Time to First Token
248 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 Opus 4.7 Anthropic 1000000

$0.943750 (rounded ~ $0.94)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 30% 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) $1.281250 (rounded ~ $1.28) Input: $1.250000
Output: $0.031250 (rounded ~ $0.03)
Optimized Cost $0.943750 (rounded ~ $0.94) Input: $1.250000
Output: $0.031250 (rounded ~ $0.03)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.337500 (rounded ~ $0.34) 26.3% 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 5,000 output tokens:

  • Input Cost: $1.250000
  • Output Cost: $0.031250 (rounded ~ $0.03)
  • Total Cost: $0.943750 (rounded ~ $0.94)
  • Cost per 1K tokens: $0.000939
  • Tokens per dollar: 1,064,901 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 260 tokens per second and 400ms time to first token:

  • Processing Time: 1 hour, 7 minutes, 38.83 seconds
  • Latency: 400 milliseconds to first token
  • Base Throughput: 260 tokens/second
  • Effective Throughput: 248 tokens/second (temperature-adjusted)

Best Use Cases

Ideal for large-scale financial analysis pipelines requiring either extreme structural precision or massive multi-document context.

Want this applied to YOUR actual stack?

This calculator shows the math for Claude Opus 4.7. 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

$1.505000 (rounded ~ $1.51)
Total Cost
⚡ 30% 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) $2.045000 (rounded ~ $2.05) Input: $2.000000
Output: $0.045000 (rounded ~ $0.05)
Optimized Cost $1.505000 (rounded ~ $1.51) Input: $2.000000
Output: $0.045000 (rounded ~ $0.05)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.540000 26.4% 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 5,000 output tokens:

  • Input Cost: $2.000000
  • Output Cost: $0.045000 (rounded ~ $0.05)
  • Total Cost: $1.505000 (rounded ~ $1.51)
  • Cost per 1K tokens: $0.001498
  • Tokens per dollar: 667,774 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: 43 minutes, 58.30 seconds
  • Latency: 220 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 381 tokens/second (temperature-adjusted)

Best Use Cases

Ideal for large-scale financial analysis pipelines requiring either extreme structural precision or massive multi-document context.

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 Opus 4.7
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 5,000
Batch API: Enabled (50% discount)
Cached Tokens: 30%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Claude Opus 4.7 vs Gemini 3.1 Pro
🏆 Grok 4.20 Beta
xAI
 $0.372500 (rounded ~ $0.37) Best Value ↓ 60.5% cheaper ↓ 75.2% cheaper
🥈 Gemini 2.5 Pro
Google
 $0.950000 ↑ 0.7% more ↓ 36.9% cheaper
🥉 Gemini 3.1 Pro
Google
 $1.505000 (rounded ~ $1.51) ↑ 59.5% more Same price
#4 GPT-5.4
OpenAI
 $1.881250 (rounded ~ $1.88) ↑ 99.3% more ↑ 25% more
#5 GPT-5.4 Thinking
OpenAI
 $1.881250 (rounded ~ $1.88) ↑ 99.3% more ↑ 25% more
#6 GPT-5.4 Thinking
OpenAI
 $1.881250 (rounded ~ $1.88) ↑ 99.3% more ↑ 25% more
🏆

Grok 4.20 Beta
xAI

$0.372500 (rounded ~ $0.37)
vs Claude Opus 4.7: ↓ 60.5%
vs Gemini 3.1 Pro: ↓ 75.2%
🥈

Gemini 2.5 Pro
Google

$0.950000
vs Claude Opus 4.7: ↑ 0.7%
vs Gemini 3.1 Pro: ↓ 36.9%
🥉

Gemini 3.1 Pro
Google

$1.505000 (rounded ~ $1.51)
vs Claude Opus 4.7: ↑ 59.5%
vs Gemini 3.1 Pro: Same
#4

GPT-5.4
OpenAI

$1.881250 (rounded ~ $1.88)
vs Claude Opus 4.7: ↑ 99.3%
vs Gemini 3.1 Pro: ↑ 25%
#5

GPT-5.4 Thinking
OpenAI

$1.881250 (rounded ~ $1.88)
vs Claude Opus 4.7: ↑ 99.3%
vs Gemini 3.1 Pro: ↑ 25%
#6

GPT-5.4 Thinking
OpenAI

$1.881250 (rounded ~ $1.88)
vs Claude Opus 4.7: ↑ 99.3%
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.

Scaling Financial RAG Pipelines

Comparing these two flagship models is essential for researchers designing large-scale pipelines for automated financial auditing or competitive intelligence. In this scale of extraction, Claude Opus 4.7 is often preferred for its exceptional instruction-following and its ability to output perfectly formatted JSON or SQL without hallucinating structural artifacts. This precision is a critical factor for analysts who need to pipe extracted data directly into downstream analytics tools without extensive manual cleaning.

On the other hand, Gemini 3.1 Pro offers an expansive context window that allows for analyzing multiple filings or extremely long documents simultaneously. This is particularly advantageous for year-over-year trend analysis where the model needs to see several hundred pages of data at once to identify shifting metrics. While Claude excels at the structural integrity of a single complex extraction, Gemini provides a broader contextual reach that can simplify multi-document synthesis. Choosing between them often comes down to the specific architecture of your data pipeline: pick the former for precise, atomic data extraction and the latter for holistic, multi-document synthesis. Both models represent the frontier of large-scale document processing, offering the reliability needed for high-volume financial research where data fidelity is the top priority for stakeholders and auditors alike.

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.