Llama 4 Scout: Managing 10-Million Token Context Windows

Complete Analysis: 2,000,000 tokens for Llama 4 Scout (10M context)

Complete analysis of pricing, performance, and use cases for Meta AI's Llama 4 Scout (10M context) model .

$0.380000 Total Cost
2,000,000 Total Tokens
59 minutes, 26.00 seconds Processing Time
561 Effective Tokens/Sec

Click Recalculate to update after making changes

Select AI Model

Llama 4 Scout
Meta AIMax Context: 10,000,000 tokens
$0.08 / $0.3 per 1M tokens
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Use Batch API (50% discount)
0%
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

$0.380000 Total Cost
$0.080000 Input Cost
$0.300000 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
2,000,000Total Tokens
$0.000190Cost per 1K
5,263,158Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

59m 26s Processing Time
600 Tokens/Second
120ms Time to First Token
561 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
Apply 1.5x multiplier to output tokens (GPT-5.4, Claude 4.6)
Manual thinking tokens (billed at output rate)
🔧 Special Modes
Enable 4x Tunnel Multiplier (applied after markup)
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

Llama 4 Scout (10M context) Meta AI 10000000

$0.380000
Total Cost
🔧 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
✗ Not Available

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.380000 Input: $0.080000
Output: $0.300000
Optimized Cost $0.380000 Input: $0.080000
Output: $0.300000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.080000
  • Output Cost: $0.300000
  • Total Cost: $0.380000
  • Cost per 1K tokens: $0.000190
  • Tokens per dollar: 5,263,158 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: 59 minutes, 26.00 seconds
  • Latency: 120 milliseconds to first token
  • Base Throughput: 600 tokens/second
  • Effective Throughput: 561 tokens/second (temperature-adjusted)

Best Use Cases

Legal DiscoveryArchive SearchMassive Ingestion

✨ Market Recommendations AI Model Registry

← Back to Llama 4 Scout (10M context)
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000,000
Tools: Enabled
Rank AI Model & Provider Total Cost vs Llama 4 Scout (10M context)
🏆 Grok 5
xAI
 $18.000000 Best Value ↑ 4636.8% more
🥈 Grok 5
xAI
 $18.000000 ↑ 4636.8% more
🏆

Grok 5
xAI

$18.000000
vs Llama 4 Scout (10M context): ↑ 4636.8%
🥈

Grok 5
xAI

$18.000000
vs Llama 4 Scout (10M context): ↑ 4636.8%
✨ 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.

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Industrial-Scale Information Ingestion

In 2026, Llama 4 Scout defines the ‘Ultra-Long Context’ market with its massive 10-million token window. Priced at just $0.38 for 1M/1M tokens, it is the most efficient way to process entire technical libraries or the full history of a Slack workspace. It is the industrial-scale scanner of the AI world, identifying needle-in-a-haystack information across gigabytes of text in seconds.

The Economics of Scale

For legal firms conducting massive discovery, Scout allows for the ingestion of tens of thousands of documents in a single query. While its reasoning is ‘Scout’ level (meant for identification and summarization), it is the essential first step in any large-scale data analysis pipeline. Once Scout identifies the critical information, a more powerful model like Maverick or Opus can be used for final analysis.

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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 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.