Per-Token Cost: Mistral Large 3 vs DeepSeek V4 Pro for Financial Text Analysis

Mistral Large 3 vs DeepSeek V4 Pro
Complete Comparison: 1,000,000 input tokens × 1,000 output tokens
Comparison Mode
⚡ 80% Cached

Complete comparison of pricing, performance, and capabilities for 2 leading AI models with 80% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
Comparison Criteria Mistral Large 3
Mistral AI
DeepSeek V4 Pro
DeepSeek
Calculation Results (Current Inputs) (80% cached)
Input Tokens 1,000,000 1,000,000
Output Tokens 1,000 1,000
Cost Breakdown
Input Cost $0.125000 (rounded ~ $0.13)Best $0.435000 (rounded ~ $0.44)Worst
Output Cost $0.000375Best $0.000870Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.035375 (rounded ~ $0.04) Best Value $0.122670 (rounded ~ $0.12) Most Expensive
Processing Time 35 minutes, 42.32 seconds Fastest 59 minutes, 30.41 seconds Slowest
Tokens per Second 500Fastest 300Slowest
Time to First Token 160ms Best 180ms Worst
Cost per 1K tokens $0.000035Best $0.000123Worst
Tokens per Dollar 28,296,820Best Value 8,160,104Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.125000 (rounded ~ $0.13)Best $0.435000 (rounded ~ $0.44)Worst
Output Cost / 1M (Base) $0.375000 (rounded ~ $0.38)Best $0.870000Worst
Input Cost / 1M (Optimized) $0.062500 (rounded ~ $0.06)Best
Optimizations: 50.0% batch
$0.435000 (rounded ~ $0.44)Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $0.187500 (rounded ~ $0.19)Best
Optimizations: 50.0% batch
$0.870000Worst
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✓ Supported ✗ Not Supported
Caching Support
80
✓ Supported ✓ 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 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)
80%
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

$0.035375 Total Cost
$0.025000 Input Cost
$0.000375 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
1,001,000Total Tokens
$0.000035Cost per 1K
28,296,820Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

35m 42s Processing Time
500 Tokens/Second
160ms Time to First Token
467 Effective Speed

Model Comparison

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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

$0.035375 (rounded ~ $0.04)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 256,000 tokens. Budgeting mode active.
⚡ 80% Cached 📊 Batch API
👁️
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) $0.125375 (rounded ~ $0.13) Input: $0.125000 (rounded ~ $0.13)
Output: $0.000375
Optimized Cost $0.035375 (rounded ~ $0.04) Input: $0.125000 (rounded ~ $0.13)
Output: $0.000375
Unit: $0.000000
Fees: $0.000000
Total Savings $0.090000 71.8% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.125000 (rounded ~ $0.13)
  • Output Cost: $0.000375
  • Total Cost: $0.035375 (rounded ~ $0.04)
  • Cost per 1K tokens: $0.000035
  • Tokens per dollar: 28,296,820 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: 35 minutes, 42.32 seconds
  • Latency: 160 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 467 tokens/second (temperature-adjusted)

Best Use Cases

These models are excellent for cost-effective analysis of extracted text from financial documentssuitable for tasks like summarizing invoice detailscategorizing expensesor performing sentiment analysis on vendor communications.

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.

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DeepSeek V4 Pro DeepSeek 1000000

$0.122670 (rounded ~ $0.12)
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,000,000 tokens. Budgeting mode active.
⚡ 80% Cached 📊 Batch API
👁️
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) $0.435870 (rounded ~ $0.44) Input: $0.435000 (rounded ~ $0.44)
Output: $0.000870
Optimized Cost $0.122670 (rounded ~ $0.12) Input: $0.435000 (rounded ~ $0.44)
Output: $0.000870
Unit: $0.000000
Fees: $0.000000
Total Savings $0.313200 (rounded ~ $0.31) 71.9% discount

Detailed Cost Analysis (from Plugin)

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

  • Input Cost: $0.435000 (rounded ~ $0.44)
  • Output Cost: $0.000870
  • Total Cost: $0.122670 (rounded ~ $0.12)
  • Cost per 1K tokens: $0.000123
  • Tokens per dollar: 8,160,104 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: 59 minutes, 30.41 seconds
  • Latency: 180 milliseconds to first token
  • Base Throughput: 300 tokens/second
  • Effective Throughput: 280 tokens/second (temperature-adjusted)

Best Use Cases

These models are excellent for cost-effective analysis of extracted text from financial documentssuitable for tasks like summarizing invoice detailscategorizing expensesor performing sentiment analysis on vendor communications.

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 Mistral Large 3
📋 Active Input Parameters
Input Tokens: 1,000,000
Output Tokens: 1,000
Batch API: Enabled (50% discount)
Cached Tokens: 80%
Rank AI Model & Provider Total Cost vs Mistral Large 3 vs DeepSeek V4 Pro
🏆 Grok 4.20 Beta
xAI
 $0.141500 (rounded ~ $0.14) Best Value ↑ 300% more ↑ 15.4% more
🥈 Gemini 2.5 Pro
Google
 $0.357500 (rounded ~ $0.36) ↑ 910.6% more ↑ 191.4% more
🥉 Gemini 3.1 Pro
Google
 $0.569000 (rounded ~ $0.57) ↑ 1508.5% more ↑ 363.8% more
#4 GPT-5.4
OpenAI
 $0.711250 (rounded ~ $0.71) ↑ 1910.6% more ↑ 479.8% more
#5 GPT-5.4 Thinking
OpenAI
 $0.711250 (rounded ~ $0.71) ↑ 1910.6% more ↑ 479.8% more
#6 GPT-5.4 Thinking
OpenAI
 $0.711250 (rounded ~ $0.71) ↑ 1910.6% more ↑ 479.8% more
🏆

Grok 4.20 Beta
xAI

$0.141500 (rounded ~ $0.14)
vs Mistral Large 3: ↑ 300%
vs DeepSeek V4 Pro: ↑ 15.4%
🥈

Gemini 2.5 Pro
Google

$0.357500 (rounded ~ $0.36)
vs Mistral Large 3: ↑ 910.6%
vs DeepSeek V4 Pro: ↑ 191.4%
🥉

Gemini 3.1 Pro
Google

$0.569000 (rounded ~ $0.57)
vs Mistral Large 3: ↑ 1508.5%
vs DeepSeek V4 Pro: ↑ 363.8%
#4

GPT-5.4
OpenAI

$0.711250 (rounded ~ $0.71)
vs Mistral Large 3: ↑ 1910.6%
vs DeepSeek V4 Pro: ↑ 479.8%
#5

GPT-5.4 Thinking
OpenAI

$0.711250 (rounded ~ $0.71)
vs Mistral Large 3: ↑ 1910.6%
vs DeepSeek V4 Pro: ↑ 479.8%
#6

GPT-5.4 Thinking
OpenAI

$0.711250 (rounded ~ $0.71)
vs Mistral Large 3: ↑ 1910.6%
vs DeepSeek V4 Pro: ↑ 479.8%
✨ 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.

Cost-Effective Text Analysis for Financial Documents

For financial analysts focused on analyzing the text content extracted from invoices, understanding the per-token cost of models like Mistral Large 3 and DeepSeek V4 Pro is essential for budget planning. Both models offer strong text processing and reasoning capabilities, making them suitable for tasks such as summarizing invoice details, identifying key financial terms, or even performing sentiment analysis on vendor notes. Mistral Large 3, known for its robust performance and multilingual capabilities, provides a strong foundation for analyzing diverse financial documents. DeepSeek V4 Pro, often praised for its efficiency and competitive pricing, offers a compelling alternative for high-volume text analysis where cost-per-token is a primary driver. When comparing these two for analyzing extracted financial data, consider their respective strengths in natural language understanding, logical inference, and their overall efficiency at scale. Evaluating their performance on a benchmark of one million tokens allows for a direct comparison of their analytical output quality versus their cost, helping organizations make informed decisions for their document intelligence platforms.

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.