Per-Unit Benchmark: Llama 4 Maverick (400B) vs DeepSeek V4 Pro for 100M-Token Workloads

Llama 4 Maverick (400B) vs DeepSeek V4 Pro
Complete Comparison: 100,000,000 input tokens × 4,000 output tokens
Comparison Mode
⚡ 50% Cached

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

⚡ Caching Optimized (up to 90% savings)
Comparison Criteria Llama 4 Maverick (400B)
Meta AI
DeepSeek V4 Pro
DeepSeek
Calculation Results (Current Inputs) (50% cached)
Input Tokens 100,000,000 100,000,000
Output Tokens 4,000 4,000
Cost Breakdown
Input Cost $15.000000Best $43.500000Worst
Output Cost $0.002400Best $0.003480Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $15.002400 (rounded ~ $15.00) Best Value $23.928480 (rounded ~ $23.93) Most Expensive
Processing Time 72 hours, 13 minutes, 30.58 seconds Fastest 96 hours, 18 minutes, 0.71 seconds Slowest
Tokens per Second 400Fastest 300Slowest
Time to First Token 150ms Best 180ms Worst
Cost per 1K tokens $0.000150Best $0.000239Worst
Tokens per Dollar 6,665,867Best Value 4,179,288Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.150000Best $0.435000 (rounded ~ $0.44)Worst
Output Cost / 1M (Base) $0.600000Best $0.870000Worst
Input Cost / 1M (Optimized) $0.150000Best
Optimizations: No optimizations applied
$0.435000 (rounded ~ $0.44)Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $0.600000Best
Optimizations: No optimizations applied
$0.870000Worst
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✓ Supported ✗ Not Supported
Caching Support
50
✗ Not Supported requested ✓ Supported
Batch API Support ✓ Supported ✗ Not Supported
Tool Usage Support ✓ Supported ✓ Supported
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ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.

Select AI Model

Llama 4 Maverick (400B)
Meta AIMax Context: 1,000,000 tokens
$0.15 / $0.6 per 1M tokens
▼
▼
Use Batch API (50% discount)
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.

Calculate Token Costs

$15.002400 Total Cost
$15.000000 Input Cost
$0.002400 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
100,004,000Total Tokens
$0.000150Cost per 1K
6,665,867Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

4333m 30s Processing Time
400 Tokens/Second
150ms Time to First Token
385 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
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
📊 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 Maverick (400B) Meta AI 1000000

$15.002400 (rounded ~ $15.00)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 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
✗ Not Available

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $15.002400 (rounded ~ $15.00) Input: $15.000000
Output: $0.002400
Optimized Cost $15.002400 (rounded ~ $15.00) Input: $15.000000
Output: $0.002400
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

For 100,000,000 input tokens and 4,000 output tokens:

  • Input Cost: $15.000000
  • Output Cost: $0.002400
  • Total Cost: $15.002400 (rounded ~ $15.00)
  • Cost per 1K tokens: $0.000150
  • Tokens per dollar: 6,665,867 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 400 tokens per second and 150ms time to first token:

  • Processing Time: 72 hours, 13 minutes, 30.58 seconds
  • Latency: 150 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 385 tokens/second (temperature-adjusted)

Best Use Cases

Ideal for high-volume RAG and private cloud deployments where data sovereignty and reasoning efficiency are prioritized.

Want this applied to YOUR actual stack?

This calculator shows the math for Llama 4 Maverick (400B). 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 →

DeepSeek V4 Pro DeepSeek 1000000

$23.928480 (rounded ~ $23.93)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 50% Cached 📊 Batch API 🔧 Tools
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✗ Not Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $43.503480 (rounded ~ $43.50) Input: $43.500000
Output: $0.003480
Optimized Cost $23.928480 (rounded ~ $23.93) Input: $43.500000
Output: $0.003480
Unit: $0.000000
Fees: $0.000000
Total Savings $19.575000 (rounded ~ $19.58) 45.0% discount

Detailed Cost Analysis (from Plugin)

For 100,000,000 input tokens and 4,000 output tokens:

  • Input Cost: $43.500000
  • Output Cost: $0.003480
  • Total Cost: $23.928480 (rounded ~ $23.93)
  • Cost per 1K tokens: $0.000239
  • Tokens per dollar: 4,179,288 tokens
  • Context Window: 1000000 tokens

Speed & Performance Analysis

With a processing speed of 300 tokens per second and 180ms time to first token:

  • Processing Time: 96 hours, 18 minutes, 0.71 seconds
  • Latency: 180 milliseconds to first token
  • Base Throughput: 300 tokens/second
  • Effective Throughput: 288 tokens/second (temperature-adjusted)

Best Use Cases

Ideal for high-volume RAG and private cloud deployments where data sovereignty and reasoning efficiency are prioritized.

Want this applied to YOUR actual stack?

This calculator shows the math for DeepSeek V4 Pro. 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 Llama 4 Maverick (400B)
📋 Active Input Parameters
Input Tokens: 100,000,000
Output Tokens: 4,000
Batch API: Enabled (50% discount)
Cached Tokens: 50%
Tools: Enabled
🔍
No Alternatives Found
No other models in the registry support all your current input parameters. Try adjusting some parameters to see more options.
Remove Images Remove Video Remove Audio Remove OCR Remove Tools
✨ 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.

Evaluating Open-Weight Efficiency

For legal tech infrastructure leads, the shift toward high-performance open-weight models offers a strategic path to escape vendor lock-in while maintaining the reasoning density required for complex document analysis. When evaluating workloads at the 100 million token scale, the primary decision factor often shifts from simple API availability to the long-term sustainability of inference costs and specialized performance in structured data extraction.

  • Llama 4 Maverick (400B) represents a standard for enterprise-grade open weights, offering a massive context window essential for cross-referencing hundreds of clauses across an entire contract portfolio. Its ecosystem support ensures that engineers can deploy with confidence across diverse private cloud environments, maintaining strict data sovereignty for sensitive legal materials.
  • DeepSeek V4 Pro challenges this dominance by focusing on architectural optimizations for thinking and reasoning tasks. For legal pipelines that require a model to ‘think through’ the implications of specific indemnification clauses across multiple jurisdictions, its specialized training can provide a significant advantage in structured output quality.

CTOs must weigh the robust community support and hardware optimization of the Meta ecosystem against the aggressive efficiency benchmarks seen in the DeepSeek series. Both models provide the high-context capabilities necessary for modern RAG-based legal discovery, but their performance on proprietary legal datasets should be the ultimate arbiter of selection for production-grade pipelines.

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 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.