Mistral Large 3 vs Llama 4 Maverick for 10 Million Tokens Monthly Document Analysis

Mistral Large 3 vs Llama 4 Maverick (400B)
Complete Comparison: 10,000,000 input tokens × 2,500 output tokens
Comparison Mode
⚡ 40% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 40% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Mistral Large 3
Mistral AI
Llama 4 Maverick (400B)
Meta AI
Calculation Results (Current Inputs) (40% cached)
Input Tokens 10,000,000 10,000,000
Output Tokens 2,500 2,500
Cost Breakdown
Input Cost $1.250000Best $1.500000Worst
Output Cost $0.000938Best $0.001500Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.800938 Best Value $1.501500 (rounded ~ $1.50) Most Expensive
Processing Time 5 hours, 50 minutes, 5.43 seconds Fastest 7 hours, 17 minutes, 36.74 seconds Slowest
Tokens per Second 500Fastest 400Slowest
Time to First Token 160ms Worst 150ms Best
Cost per 1K tokens $0.000080Best $0.000150Worst
Tokens per Dollar 12,488,490Best Value 6,661,672Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.125000 (rounded ~ $0.13)Best $0.150000Worst
Output Cost / 1M (Base) $0.375000 (rounded ~ $0.38)Best $0.600000Worst
Input Cost / 1M (Optimized) $0.062500 (rounded ~ $0.06)Best
Optimizations: 50.0% batch
$0.150000Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $0.187500 (rounded ~ $0.19)Best
Optimizations: 50.0% batch
$0.600000Worst
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✓ Supported ✓ Supported
Caching Support
40
✓ Supported ✗ Not Supported requested
Batch API Support ✓ Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
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ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 256,000 tokens. Budgeting mode active.

Select AI Model

Mistral Large 3
Mistral AIMax Context: 256,000 tokens
$0.5 / $1.5 per 1M tokens
▼
▼
Use Batch API (50% discount)
40%
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

$0.800938 Total Cost
$0.750000 Input Cost
$0.000938 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
10,002,500Total Tokens
$0.000080Cost per 1K
12,488,490Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

350m 5s Processing Time
500 Tokens/Second
160ms Time to First Token
476 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.

Mistral Large 3 Mistral AI

$0.800938
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 256,000 tokens. Budgeting mode active.
⚡ 40% 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
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $1.250938 Input: $1.250000
Output: $0.000938
Optimized Cost $0.800938 Input: $1.250000
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Total Savings $0.450000 36.0% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount

Detailed Cost Analysis (from Plugin)

For 10,000,000 input tokens and 2,500 output tokens:

  • Input Cost: $1.250000
  • Output Cost: $0.000938
  • Total Cost: $0.800938
  • Cost per 1K tokens: $0.000080
  • Tokens per dollar: 12,488,490 tokens
  • Context Window: 256000 tokens

Speed & Performance Analysis

With a processing speed of 500 tokens per second and 160ms time to first token:

  • Processing Time: 5 hours, 50 minutes, 5.43 seconds
  • Latency: 160 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 476 tokens/second (temperature-adjusted)

Best Use Cases

Choose Mistral Large 3 for multilingualhigh-performance API tasks; use Llama 4 Maverick for flexibleon-premise or private cloud deployments.

Want this applied to YOUR actual stack?

This calculator shows the math for Mistral Large 3. 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 →

Llama 4 Maverick (400B) Meta AI 1000000

$1.501500 (rounded ~ $1.50)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 40% 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) $1.501500 (rounded ~ $1.50) Input: $1.500000
Output: $0.001500
Optimized Cost $1.501500 (rounded ~ $1.50) Input: $1.500000
Output: $0.001500
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

For 10,000,000 input tokens and 2,500 output tokens:

  • Input Cost: $1.500000
  • Output Cost: $0.001500
  • Total Cost: $1.501500 (rounded ~ $1.50)
  • Cost per 1K tokens: $0.000150
  • Tokens per dollar: 6,661,672 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: 7 hours, 17 minutes, 36.74 seconds
  • Latency: 150 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 381 tokens/second (temperature-adjusted)

Best Use Cases

Choose Mistral Large 3 for multilingualhigh-performance API tasks; use Llama 4 Maverick for flexibleon-premise or private cloud deployments.

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 →

✨ Market Recommendations AI Model Registry

← Back to Mistral Large 3
📋 Active Input Parameters
Input Tokens: 10,000,000
Output Tokens: 2,500
Batch API: Enabled (50% discount)
Cached Tokens: 40%
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.

As growing SaaS companies scale their internal knowledge bases and customer documentation, processing 10 million tokens monthly becomes a standard operational requirement. Choosing between Mistral Large 3 and Llama 4 Maverick often comes down to balancing technical requirements, such as language support and architectural flexibility, against the specific needs of your document processing pipeline.

Mistral Large 3 is highly regarded for its balance of high-end performance and operational efficiency. It is particularly effective for marketing teams that manage multi-language content across international markets, as it maintains high semantic fidelity across different linguistic structures. If your summarization tasks involve translating, localizing, or synthesizing content from diverse sources, its sophisticated handling of global context is a major benefit.

Llama 4 Maverick, on the other hand, provides a powerful, open-weights alternative that allows for greater control over your deployment environment. For teams with strict data privacy requirements or those that need to integrate model performance into custom, on-premise infrastructure, Llama 4 Maverick offers a high-performance path without the lock-in associated with proprietary APIs. It is an excellent choice for teams that are already invested in an open-source ecosystem and require a scalable, transparent foundation for their document analysis tools.

Ultimately, your choice should be driven by your infrastructure strategy. If you prioritize ease of API integration and top-tier multi-language capability, Mistral Large 3 is a strong contender. If your team values the portability and architectural control provided by open-weights models, Llama 4 Maverick is the superior choice for scaling document analysis.

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.