DeepSeek-V3 vs Llama-4: Self-Hosted Enterprise ROI

deepseek-v3.1 vs llama-4-scout-17b
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 deepseek-v3.1
DeepSeek
llama-4-scout-17b
Meta AI
Input Parameters Applied
Input Tokens 100,000 100,000
Output Tokens 50,000 50,000
Calculation Results
Input Cost $0.015000 (rounded ~ 0.02) Best $0.100000 Worst
Output Cost $0.030000 Best $0.250000 Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.045000 (rounded ~ 0.05) Best Value $0.350000 Most Expensive
Processing Time 5 minutes, 9.00 seconds Slowest 4 minutes, 17.00 seconds Fastest
Tokens per Second 500 Slowest 600 Fastest
Time to First Token 200ms Worst 120ms Best
Cost per 1K tokens $0.000300 Best $0.002333 (rounded ~ 0.00) Worst
Tokens per Dollar 3,333,333 Best Value 428,571 Worst Value
Cost per 1 Million Tokens
Input Cost / 1M (Base) $0.150000 Best $1.000000 Worst
Output Cost / 1M (Base) $0.600000 Best $5.000000 Worst
Input Cost / 1M (Optimized) $0.150000 Best
Optimizations: No optimizations applied
$1.000000 Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $0.600000 Best
Optimizations: No optimizations applied
$5.000000 Worst
Optimizations: No optimizations applied
Capabilities
Caching Support ✗ Not Supported ✗ Not Supported
Batch API Support ✗ Not Supported ✗ Not Supported
Fine-Tuning Mode Standard Standard
Research Mode Not Enabled Not Enabled
Thinking Enabled Not Enabled Not Enabled
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🔄 Compare Different AI Models

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Second Model

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All other parameters will be preserved from the current comparison.

Select AI Model

Deepseek V3 1
DeepSeekMax Context: 1,000,000 tokens
Input: $0.150000 / 1M
Output: $0.600000 / 1M

Calculate Token Costs

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▼
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
$0.045000Total Cost
$0.015000Input Cost
$0.030000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
150,000Total Tokens
$0.000300Cost per 1K
3,333,333Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

▼
5m 9sProcessing Time
500Tokens/Second
200msTime to First Token
485Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 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.

deepseek-v3.1 DeepSeek 1000000

$0.045000 (rounded ~ 0.05)
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) $0.045000 (rounded ~ 0.05) Input: $0.015000 (rounded ~ 0.02)
Output: $0.030000
Optimized Cost $0.045000 (rounded ~ 0.05) Input: $0.015000 (rounded ~ 0.02)
Output: $0.030000
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

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

  • Input Cost: $0.015000 (rounded ~ 0.02)
  • Output Cost: $0.030000
  • Unit Cost: $0.000000
  • Service Fees: $0.000000
  • Total Cost: $0.045000 (rounded ~ 0.05)
  • Cost per 1K tokens: $0.000300
  • Tokens per dollar: 3,333,333 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 500 tokens per second and 200ms time to first token:

  • Processing Time: 5 minutes, 9.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 485 tokens/second

Best Use Cases

EnterpriseSelf-hostingData SovereigntyProprietary Workflows

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, 17.00 seconds
  • Latency: 120 milliseconds to first token
  • Base Throughput: 600 tokens/second
  • Effective Throughput: 583 tokens/second

Best Use Cases

EnterpriseSelf-hostingData SovereigntyProprietary Workflows

Open-Weights Infrastructure Costs & Total Ownership Economics

Comparing the comprehensive total cost of ownership (TCO) for running DeepSeek-V3.1 vs Meta’s Llama-4 models on private cloud infrastructure. This analysis goes beyond API pricing to include GPU cluster costs, power consumption, maintenance overhead, and the strategic value of data sovereignty in regulated industries and proprietary workflows.

Inference Specs & Infrastructure Economics

  • Model Comparison: DeepSeek V3.1 (671B MoE) vs Llama 4 Scout 17B
  • Throughput Requirements: 5M tokens per day enterprise-scale processing
  • GPU Cluster: 8x H200 instances with associated cloud/hosting costs
  • Effective Cost: ~$0.12 per 1K tokens for self-hosted infrastructure
  • Batch Processing: Native support in both models for efficiency
  • Fine-tuning: Domain-specific adapter training capabilities
  • Cache Strategy: Model-level caching for repeated enterprise queries

Enterprise Strategy & Sovereign AI Value

Data sovereignty and compliance requirements, internal tool development pipelines, private knowledge base implementations, high-volume automation without external API dependencies. This calculator helps CTOs make informed decisions between open-weight models, factoring in not just inference costs but also development flexibility, customization potential, and long-term strategic positioning in the AI landscape.

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.