Llama 4 Scout Meta 10000000
$0.008300 (rounded ~ 0.01)
Total Cost
Vision/Images
✗ Not Available
Audio Processing
✗ Not Available
Video Analysis
✗ Not Available
Tool Usage
✗ Not Available
OCR Support
✗ Not Available
Batch API
✗ Not Available
Caching
✗ Not Available
💰 Total Cost Calculation (from Plugin)
Base Cost (No Optimizations)
$0.008300 (rounded ~ 0.01)
Input: $0.008000 (rounded ~ 0.01)
Output: $0.000300
Output: $0.000300
Optimized Cost
$0.008300 (rounded ~ 0.01)
Input: $0.008000 (rounded ~ 0.01)
Output: $0.000300
Unit: $0.000000
Fees: $0.000000
Output: $0.000300
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 1,000 output tokens:
- Input Cost: $0.008000 (rounded ~ 0.01)
- Output Cost: $0.000300
- Total Cost: $0.008300 (rounded ~ 0.01)
- Cost per 1K tokens: $0.000082
- Tokens per dollar: 12,168,675 tokens
- Context Window: 10000000 tokens
Speed & Performance Analysis
With a processing speed of 600 tokens per second and 120ms time to first token:
- Processing Time: 2 minutes, 55.00 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 600 tokens/second
- Effective Throughput: 577 tokens/second (temperature-adjusted)
Best Use Cases
Technical Manual SearchVisual RAGArchitecture Review
✨ Market Recommendations AI Model Registry
← Back to Llama 4 Scout
📋 Active Input Parameters
Input Tokens:
100,000
Output Tokens:
1,000
Batch API:
Enabled (50% discount)
Images:
25 (Medium Resolution)
Tools:
Enabled
| Rank | AI Model & Provider | Total Cost | vs Llama 4 Scout |
|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.005845 (rounded ~ 0.01) Best Value | ↓ 29.6% cheaper |
| 🥈 |
Llama 4 Maverick (400B)
Meta AI
|
$0.038718 (rounded ~ 0.04) | ↑ 366.5% more |
| 🥉 |
GPT-5.3 Codex Spark
OpenAI
|
$0.105788 (rounded ~ 0.11) | ↑ 1174.5% more |
| #4 |
Gemini 3.1 Pro
Google
|
$0.118900 (rounded ~ 0.12) | ↑ 1332.5% more |
| #5 |
GPT-5.4 Thinking
OpenAI
|
$0.148625 (rounded ~ 0.15) | ↑ 1690.7% more |
| #6 |
Claude Sonnet 4.6
Anthropic
|
$0.176850 (rounded ~ 0.18) | ↑ 2030.7% more |
| #7 |
Claude Opus 4.6
Anthropic
|
$0.294750 (rounded ~ 0.29) | ↑ 3451.2% more |
| #8 |
GPT-5.2 Pro
OpenAI
|
$1.269450 | ↑ 15194.6% more |
| #9 |
GPT-5.2 Pro
OpenAI
|
$1.269450 | ↑ 15194.6% more |
🏆
Gemini 3.1 Flash Lite
Gemini 3.1 Flash Lite Google
$0.005845 (rounded ~ 0.01)
vs Llama 4 Scout:
↓ 29.6%
🥈
Llama 4 Maverick (400B)
Llama 4 Maverick (400B) Meta AI
$0.038718 (rounded ~ 0.04)
vs Llama 4 Scout:
↑ 366.5%
🥉
GPT-5.3 Codex Spark
GPT-5.3 Codex Spark OpenAI
$0.105788 (rounded ~ 0.11)
vs Llama 4 Scout:
↑ 1174.5%
#4
Gemini 3.1 Pro
Gemini 3.1 Pro Google
$0.118900 (rounded ~ 0.12)
vs Llama 4 Scout:
↑ 1332.5%
#5
GPT-5.4 Thinking
GPT-5.4 Thinking OpenAI
$0.148625 (rounded ~ 0.15)
vs Llama 4 Scout:
↑ 1690.7%
#6
Claude Sonnet 4.6
Claude Sonnet 4.6 Anthropic
$0.176850 (rounded ~ 0.18)
vs Llama 4 Scout:
↑ 2030.7%
#7
Claude Opus 4.6
Claude Opus 4.6 Anthropic
$0.294750 (rounded ~ 0.29)
vs Llama 4 Scout:
↑ 3451.2%
#8
GPT-5.2 Pro
GPT-5.2 Pro OpenAI
$1.269450
vs Llama 4 Scout:
↑ 15194.6%
#9
GPT-5.2 Pro
GPT-5.2 Pro OpenAI
$1.269450
vs Llama 4 Scout:
↑ 15194.6%
✨ How recommendations work: We scan all active models in the registry that support your current inputs (🖼️ Images), calculate costs with all your parameters, and sort by total cost (cheapest first).
Vision-First Knowledge Retrieval
Scout is optimized for searching through visual databases. Calculate the cost of building a RAG system that understands diagrams, charts, and blueprints.
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.
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 do Market Recommendations work?
Our recommendation engine scans the entire model registry for alternatives that support all your current input parameters (images, video, audio, OCR, tools, etc.). It calculates exact costs with your settings and sorts by price, showing you the best value options available in the market.
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.