Open-Source vs Cloud API Cost: Llama 4 vs GPT-5

llama-4-scout-17b vs gpt-5
Complete Comparison: 100,000 input tokens × 50,000 output tokens
Comparison Mode (Custom field comparison)

Complete comparison of pricing, performance, and capabilities for 2 leading AI models .

Comparison Criteria llama-4-scout-17b
Meta AI
gpt-5
OpenAI
Input Parameters Applied
Input Tokens 100,000 100,000
Output Tokens 50,000 50,000
Calculation Results
Input Cost $0.100000 Best $0.175000 (rounded ~ 0.18) Worst
Output Cost $0.250000 Best $0.700000 Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.350000 Best Value $0.875000 (rounded ~ 0.88) Most Expensive
Processing Time 4 minutes, 22.00 seconds Fastest 5 minutes, 50.00 seconds Slowest
Tokens per Second 600 Fastest 450 Slowest
Time to First Token 120ms Best 200ms Worst
Cost per 1K tokens $0.002333 (rounded ~ 0.00) Best $0.005833 (rounded ~ 0.01) Worst
Tokens per Dollar 428,571 Best Value 171,429 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $1.000000 Best $1.750000 Worst
Output Cost / 1M (Base) $5.000000 Best $14.000000 Worst
Input Cost / 1M (Optimized) $1.000000 Best
Optimizations: No optimizations applied
$1.750000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $5.000000 Best
Optimizations: No optimizations applied
$14.000000 Worst
Optimizations: No optimizations applied
Capabilities
Caching Support ✗ Not Supported ✓ Supported
Batch API Support ✗ Not Supported Available
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
Scroll horizontally to see all data

🔄 Compare Different AI Models

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First Model

2

Second Model

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All other parameters will be preserved from the current comparison.

Select AI Model

Llama 4 Scout 17b
Meta AIMax Context: 10,000,000 tokens
Input: $1.000000 / 1M
Output: $5.000000 / 1M

Calculate Token Costs

Provider-specific multipliers applied after all calculations
Enable for Haiku 4.5 hard cap bypass
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.
Multiply total cost by quantity for project budgeting
$0.100000Input Cost
$0.250000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
150,000Total Tokens
$0.002333Cost per 1K
428,571Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

4m 22sProcessing Time
600Tokens/Second
120msTime to First Token
571Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

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🔄 Advanced Options

⚡ Optimization
0%
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data (Pro: $4.50/1M/hr, Flash: $1.00/1M/hr)
First 50 hours free, $0.05/hour after (reset at 00:00 UTC)

🧠 Specialized Modes
Enable Thinking Mode (Google models)
Manual thinking tokens (billed at output rate, disabled by default)
Adaptive thinking token estimation for DeepSeek models
30% output surcharge (Vertex AI priority)
Billed at output rate × reasoning multiplier
Global 2x multiplier for priority processing
Enable Reasoning/Thinking Mode (DeepSeek R1, Grok Deep Reason)
Enable Agentic Swarm

🔧 Automated Service Fees
Enable for DeepSeek V4 ($0.01 per 1M tokens)
Enable code execution (adds $0.05 flat fee)
$0.01 per query (auto-applied based on Search Queries input)

🤖 xAI Agent Tools (Unified $5.00/1k)
Real-time X data access calls
Standard internet search calls
Python sandbox execution calls (overrides flat fee if set)

📚 xAI RAG Tools (Unified $2.50/1k)
File search tool access
Collections/RAG knowledge base access - aggregated with File Search at $2.50/1k
ℹ️ Updated xAI Tool Pricing: Agent tools (web, X, code) at $5.00/1k calls. RAG tools (collections, file) at $2.50/1k calls. Integer code_execution_calls overrides boolean.

🎤 Realtime Audio & Deep Research
Enable Deep Research ($2.00/$8.00 rates)
Session length for billing ($0.01 per minute, rounded up)
Active speech time within session

📄 Mistral AI - Unit-Based Options
Number of pages to process with OCR (tiered pricing auto-applied)
Enable HTML table reconstruction surcharge
Duration-based audio processing (not token-based)
Enable speaker diarization (Voxtral models only)
Enable context biasing (Voxtral models only)

🔬 Research & Citation
Enable research tier pricing ($2.00/$8.00 + $0.005/query)
Enable reasoning with 1,000 token floor ($0.015 min)
Fee per source cited when research mode is enabled

⚙️ Performance Tuning
Low = Fast
High = Creative
📊 Advanced Cost Breakdown
📊 Multiple Models Detected: This page contains data for 2 models. See the detailed comparison table above, and switch between models using tabs below.

llama-4-scout-17b Meta AI 10000000

$0.350000
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

Base Cost (No Optimizations) $0.350000 Input: $0.100000
Output: $0.250000
Optimized Cost $0.350000 Input: $0.100000
Output: $0.250000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 100,000 input tokens and 50,000 output tokens:

  • Input Cost: $0.100000
  • Output Cost: $0.250000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $0.350000
  • Cost per 1K tokens: $0.002333 (rounded ~ 0.00)
  • Tokens per dollar: 428,571 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: 4 minutes, 22.00 seconds
  • Latency: 120 milliseconds to first token
  • Base Throughput: 600 tokens/second
  • Effective Throughput: 571 tokens/second

Best Use Cases

Enterprise deploymentCost optimizationScaling

gpt-5 OpenAI

$0.875000 (rounded ~ 0.88)
Total Cost
👁️
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

Base Cost (No Optimizations) $0.875000 (rounded ~ 0.88) Input: $0.175000 (rounded ~ 0.18)
Output: $0.700000
Optimized Cost $0.875000 (rounded ~ 0.88) Input: $0.175000 (rounded ~ 0.18)
Output: $0.700000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 100,000 input tokens and 50,000 output tokens:

  • Input Cost: $0.175000 (rounded ~ 0.18)
  • Output Cost: $0.700000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $0.875000 (rounded ~ 0.88)
  • Cost per 1K tokens: $0.005833 (rounded ~ 0.01)
  • Tokens per dollar: 171,429 tokens
  • Context Window: 400000 tokens

Speed & Performance Analysis

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

  • Processing Time: 5 minutes, 50.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 450 tokens/second
  • Effective Throughput: 429 tokens/second

Best Use Cases

Enterprise deploymentCost optimizationScaling

Deployment Cost Analysis

Comparing self-hosted open-source models vs cloud API costs. Includes infrastructure considerations beyond just token pricing.

Cost Components

  • Cloud API: Pay-per-token, no infrastructure
  • Self-hosted: GPU costs, maintenance, expertise
  • Llama 4 Scout: $0.08/$0.30 per 1M (API)
  • GPT-5: $1.25/$10.00 per 1M (API)
  • Break-even analysis for different scales

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.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 38 AI models. It calculates token-based pricing, analyzes multimodal processing, and provides optimization recommendations.