Gemini 4 Argon vs GPT-6.1 Sol for 500-Invoice Data Extraction (1M Tokens)

Gemini 4 Argon vs GPT-6.1 Sol
Complete Comparison: 1,000,000 input tokens × 2,000 output tokens
Comparison Mode
🖼️ 500 Images ⚡ 50% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 500 Images, 50% Cached.

🖼️ Multimodal Input ⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Gemini 4 Argon
Google
GPT-6.1 Sol
OpenAI
Calculation Results (Current Inputs) (500 images, 50% cached)
Input Tokens 1,000,000 1,000,000
Output Tokens 2,000 2,000
Cost Breakdown
Input Cost $0.629000 (rounded ~ $0.63)Best $2.516000 (rounded ~ $2.52)Worst
Output Cost $0.005000 (rounded ~ $0.01)Best $0.015000 (rounded ~ $0.02)Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.350950 Best Value $1.398800 (rounded ~ $1.40) Most Expensive
Processing Time 1 hour, 59 minutes, 0.18 seconds Fastest 2 hours, 38 minutes, 40.18 seconds Slowest
Tokens per Second 180Fastest 135Slowest
Time to First Token 260ms Best 330ms Worst
Cost per 1K tokens $0.000279Best $0.001110Worst
Tokens per Dollar 3,590,255Best Value 900,772Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.500000Best $2.000000Worst
Output Cost / 1M (Base) $2.500000Best $7.500000Worst
Input Cost / 1M (Optimized) $0.250000Best
Optimizations: 50.0% batch
$1.000000Worst
Optimizations: 50.0% batch
Output Cost / 1M (Optimized) $1.250000Best
Optimizations: 50.0% batch
$3.750000Worst
Optimizations: 50.0% batch
Capabilities & Advanced Features
Images Support
500
✓ Supported ✓ Supported
Video Support ✓ Supported ✗ Not Supported
Audio Support ✓ Supported ✗ Not 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 1,048,576 tokens. Budgeting mode active.

Select AI Model

Gemini 4 Argon

GoogleMax Context: 1,048,576 tokens
$2 / $10 per 1M tokens
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.
Will auto-convert to minutes for Voxtral models (9000 tokens = 1 min)
$0.067 per 1,000 pixels

Calculate Token Costs

$0.350950 Total Cost
$0.314500 Input Cost
$0.005000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
1,260,000Total Tokens
$0.000279Cost per 1K
3,590,255Tokens per $

📊 Advanced Cost Breakdown

Processing Speed

119m 0s Processing Time
180 Tokens/Second
260ms Time to First Token
176 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

📚 Research & Citations

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 4 Argon Google 1048576

$0.350950
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,048,576 tokens. Budgeting mode active.
🖼️ 500 Image (Medium) ⚡ 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) $0.634000 (rounded ~ $0.63) Input: $0.629000 (rounded ~ $0.63)
Output: $0.005000 (rounded ~ $0.01)
Optimized Cost $0.350950 Input: $0.629000 (rounded ~ $0.63)
Output: $0.005000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.283050 (rounded ~ $0.28) 44.6% discount

Advanced Cost Breakdown (from Plugin)

🖼️ Multimodal Input
$0.000000
258,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount

Multimodal Input Details

🖼️ Images
Count: 500
Resolution: Medium
Tokens: 258,000
Cost: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.629000 (rounded ~ $0.63)
  • Output Cost: $0.005000 (rounded ~ $0.01)
  • Total Cost: $0.350950
  • Cost per 1K tokens: $0.000279
  • Tokens per dollar: 3,590,255 tokens
  • Context Window: 1048576 tokens

Speed & Performance Analysis

With a processing speed of 180 tokens per second and 260ms time to first token:

  • Processing Time: 1 hour, 59 minutes, 0.18 seconds
  • Latency: 260 milliseconds to first token
  • Base Throughput: 180 tokens/second
  • Effective Throughput: 176 tokens/second (temperature-adjusted)

Best Use Cases

Gemini 4 Argon is best for complex visual-heavy document parsing; GPT-6.1 Sol is superior for logic-heavymulti-step agentic workflows.

Want this applied to YOUR actual stack?

This calculator shows the math for Gemini 4 Argon. 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.

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GPT-6.1 Sol OpenAI 1050000 🏔️ Context Cliff

$1.398800 (rounded ~ $1.40)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,050,000 tokens. Budgeting mode active.
🖼️ 500 Image (Medium) ⚡ 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) $2.531000 (rounded ~ $2.53) Input: $2.516000 (rounded ~ $2.52)
Output: $0.015000 (rounded ~ $0.02)
Optimized Cost $1.398800 (rounded ~ $1.40) Input: $2.516000 (rounded ~ $2.52)
Output: $0.015000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Total Savings $1.132200 (rounded ~ $1.13) 44.7% discount

Advanced Cost Breakdown (from Plugin)

🖼️ Multimodal Input
$0.000000
258,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount
🏔️ Context Cliff
Premium Tier
>272,000 tokens triggered premium pricing
📊 Cliff Pricing
Premium
premium pricing (threshold: 272,000)

Multimodal Input Details

🖼️ Images
Count: 500
Resolution: Medium
Tokens: 258,000
Cost: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $2.516000 (rounded ~ $2.52)
  • Output Cost: $0.015000 (rounded ~ $0.02)
  • Total Cost: $1.398800 (rounded ~ $1.40)
  • Cost per 1K tokens: $0.001110
  • Tokens per dollar: 900,772 tokens
  • Context Window: 1050000 tokens

Speed & Performance Analysis

With a processing speed of 135 tokens per second and 330ms time to first token:

  • Processing Time: 2 hours, 38 minutes, 40.18 seconds
  • Latency: 330 milliseconds to first token
  • Base Throughput: 135 tokens/second
  • Effective Throughput: 132 tokens/second (temperature-adjusted)

Best Use Cases

Gemini 4 Argon is best for complex visual-heavy document parsing; GPT-6.1 Sol is superior for logic-heavymulti-step agentic workflows.

Want this applied to YOUR actual stack?

This calculator shows the math for GPT-6.1 Sol. 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 4 Argon
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 2,000
Batch API: Enabled (50% discount)
Cached Tokens: 50%
Images: 500 (Medium Resolution)
Tools: Enabled
Rank AI Model & Provider Total Cost vs Gemini 4 Argon vs GPT-6.1 Sol
🏆 Gemini 3.5 Flash-Lite
Google
 $0.053143 (rounded ~ $0.05) Best Value ↓ 84.9% cheaper ↓ 96.2% cheaper
🥈 GPT-6 Luna
OpenAI
 $0.069940 ↓ 80.1% cheaper ↓ 95% cheaper
🥉 Gemini 3.8 Flash
Google
 $0.131606 (rounded ~ $0.13) ↓ 62.5% cheaper ↓ 90.6% cheaper
#4 Gemini 3.6 Flash
Google
 $0.131606 (rounded ~ $0.13) ↓ 62.5% cheaper ↓ 90.6% cheaper
#5 Gemini 2.5 Pro
Google
 $0.879875 ↑ 150.7% more ↓ 37.1% cheaper
#6 GPT-6.1 Sol
OpenAI
 $1.398800 (rounded ~ $1.40) ↑ 298.6% more Same price
#7 GPT-6 Sol
OpenAI
 $1.398800 (rounded ~ $1.40) ↑ 298.6% more Same price
#8 GPT-5.4
OpenAI
 $1.752250 (rounded ~ $1.75) ↑ 399.3% more ↑ 25.3% more
#9 GPT-5.4 Thinking
OpenAI
 $1.752250 (rounded ~ $1.75) ↑ 399.3% more ↑ 25.3% more
#10 GPT-6 Astra
OpenAI
 $7.019000 (rounded ~ $7.02) ↑ 1900% more ↑ 401.8% more
#11 GPT-6 Astra
OpenAI
 $7.019000 (rounded ~ $7.02) ↑ 1900% more ↑ 401.8% more
🏆

Gemini 3.5 Flash-Lite
Google

$0.053143 (rounded ~ $0.05)
vs Gemini 4 Argon: ↓ 84.9%
vs GPT-6.1 Sol: ↓ 96.2%
🥈

GPT-6 Luna
OpenAI

$0.069940
vs Gemini 4 Argon: ↓ 80.1%
vs GPT-6.1 Sol: ↓ 95%
🥉

Gemini 3.8 Flash
Google

$0.131606 (rounded ~ $0.13)
vs Gemini 4 Argon: ↓ 62.5%
vs GPT-6.1 Sol: ↓ 90.6%
#4

Gemini 3.6 Flash
Google

$0.131606 (rounded ~ $0.13)
vs Gemini 4 Argon: ↓ 62.5%
vs GPT-6.1 Sol: ↓ 90.6%
#5

Gemini 2.5 Pro
Google

$0.879875
vs Gemini 4 Argon: ↑ 150.7%
vs GPT-6.1 Sol: ↓ 37.1%
#6

GPT-6.1 Sol
OpenAI

$1.398800 (rounded ~ $1.40)
vs Gemini 4 Argon: ↑ 298.6%
vs GPT-6.1 Sol: Same
#7

GPT-6 Sol
OpenAI

$1.398800 (rounded ~ $1.40)
vs Gemini 4 Argon: ↑ 298.6%
vs GPT-6.1 Sol: Same
#8

GPT-5.4
OpenAI

$1.752250 (rounded ~ $1.75)
vs Gemini 4 Argon: ↑ 399.3%
vs GPT-6.1 Sol: ↑ 25.3%
#9

GPT-5.4 Thinking
OpenAI

$1.752250 (rounded ~ $1.75)
vs Gemini 4 Argon: ↑ 399.3%
vs GPT-6.1 Sol: ↑ 25.3%
#10

GPT-6 Astra
OpenAI

$7.019000 (rounded ~ $7.02)
vs Gemini 4 Argon: ↑ 1900%
vs GPT-6.1 Sol: ↑ 401.8%
#11

GPT-6 Astra
OpenAI

$7.019000 (rounded ~ $7.02)
vs Gemini 4 Argon: ↑ 1900%
vs GPT-6.1 Sol: ↑ 401.8%
✨ 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.

For studio AI leads tackling invoice processing at scale, the choice between Gemini 4 Argon and GPT-6.1 Sol often comes down to the specific multimodal requirements and reasoning depth needed for your pipeline. Gemini 4 Argon brings frontier-level intelligence with strong spatial reasoning, making it exceptionally effective if your invoice extraction involves reading dense, varied layouts, non-standard tables, or handwritten annotations that standard OCR might struggle to parse accurately. Its native multimodal architecture means text and image processing are tightly integrated, which reduces hallucination rates on visual data points.

Conversely, GPT-6.1 Sol is optimized for dense reasoning and automated tool orchestration, making it a powerful choice if your extraction pipeline is part of a broader, multi-step agentic workflow. If your process requires not just extracting data, but also initiating downstream business logic—such as cross-referencing invoice data with internal project databases, flagging discrepancies, and drafting email responses for missing info—GPT-6.1 Sol’s dynamic prompt caching and reasoning effort levels provide granular control. The decision rests on whether your primary bottleneck is visual interpretation (where Gemini excels) or complex logical orchestration (where GPT-6.1 Sol shines). Both models support large context windows, but their architectural strengths—Gemini’s visual integration versus GPT’s tool-use reliability—will dictate the best fit for your specific studio’s infrastructure.

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 are image tokens calculated?
Images are tokenized based on resolution: Low: 85 tokens, Medium: 170 tokens, High: 255 tokens, Full: 765 tokens per image. Some models (like Llama 4 Maverick) use tile-based encoding with 1,610 tokens/image (standard) or 8,050 tokens/image (high-res).
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 4 Argon currently costs $2.00 / $10.00 per 1M tokens. These are the models worth pricing against it, taken live from the tracked registry.

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