Mistral Large 3 vs Llama 4 Maverick for 100M-Token RAG Pipelines

Mistral Large 3 vs Llama 4 Maverick
Complete Comparison: 200,000 input tokens × 400 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
Meta AI
Calculation Results (Current Inputs) (40% cached)
Input Tokens 200,000 200,000
Output Tokens 400 400
Cost Breakdown
Input Cost $0.025000 (rounded ~ $0.03)Best $0.030000Worst
Output Cost $0.000150Best $0.000240Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.016150 (rounded ~ $0.02) Best Value $0.030240 Most Expensive
Processing Time 6 minutes, 57.01 seconds Fastest 8 minutes, 41.22 seconds Slowest
Tokens per Second 500Fastest 400Slowest
Time to First Token 160ms Worst 150ms Best
Cost per 1K tokens $0.000081Best $0.000151Worst
Tokens per Dollar 12,408,669Best Value 6,626,984Worst 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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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

$0.016150 Total Cost
$0.015000 Input Cost
$0.000150 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
200,400Total Tokens
$0.000081Cost per 1K
12,408,669Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

6m 57s Processing Time
500 Tokens/Second
160ms Time to First Token
481 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

$0.016150 (rounded ~ $0.02)
Total Cost
⚡ 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) $0.025150 (rounded ~ $0.03) Input: $0.025000 (rounded ~ $0.03)
Output: $0.000150
Optimized Cost $0.016150 (rounded ~ $0.02) Input: $0.025000 (rounded ~ $0.03)
Output: $0.000150
Unit: $0.000000
Fees: $0.000000
Total Savings $0.009000 35.8% discount

Advanced Cost Breakdown (from Plugin)

📊 Batch API
50.0% off
Asynchronous processing discount

Detailed Cost Analysis (from Plugin)

For 200,000 input tokens and 400 output tokens:

  • Input Cost: $0.025000 (rounded ~ $0.03)
  • Output Cost: $0.000150
  • Total Cost: $0.016150 (rounded ~ $0.02)
  • Cost per 1K tokens: $0.000081
  • Tokens per dollar: 12,408,669 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: 6 minutes, 57.01 seconds
  • Latency: 160 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 481 tokens/second (temperature-adjusted)

Best Use Cases

Mistral Large 3 for high-precisioninstruction-following RAG; Llama 4 Maverick for long-context document ingestion.

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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Llama 4 Maverick Meta AI 1000000

$0.030240
Total Cost
⚡ 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) $0.030240 Input: $0.030000
Output: $0.000240
Optimized Cost $0.030240 Input: $0.030000
Output: $0.000240
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

For 200,000 input tokens and 400 output tokens:

  • Input Cost: $0.030000
  • Output Cost: $0.000240
  • Total Cost: $0.030240
  • Cost per 1K tokens: $0.000151
  • Tokens per dollar: 6,626,984 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: 8 minutes, 41.22 seconds
  • Latency: 150 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 385 tokens/second (temperature-adjusted)

Best Use Cases

Mistral Large 3 for high-precisioninstruction-following RAG; Llama 4 Maverick for long-context document ingestion.

Want this applied to YOUR actual stack?

This calculator shows the math for Llama 4 Maverick. 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: 200,000
Output Tokens: 400
Batch API: Enabled (50% discount)
Cached Tokens: 40%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Mistral Large 3 vs Llama 4 Maverick
🏆 Gemini 3.1 Flash Lite
Google
 $0.008150 (rounded ~ $0.01) Best Value ↓ 49.5% cheaper ↓ 73% cheaper
🥈 Gemini 3.5 Flash-Lite
Google
 $0.009850 ↓ 39% cheaper ↓ 67.4% cheaper
🥉 Gemini 2.5 Flash
Google
 $0.009850 ↓ 39% cheaper ↓ 67.4% cheaper
#4 Gemini 3.8 Flash
Google
 $0.024375 (rounded ~ $0.02) ↑ 50.9% more ↓ 19.4% cheaper
#5 GPT-5.4 mini
OpenAI
 $0.024450 (rounded ~ $0.02) ↑ 51.4% more ↓ 19.1% cheaper
#6 Claude Haiku 4.5
Anthropic
 $0.032500 (rounded ~ $0.03) ↑ 101.2% more ↑ 7.5% more
#7 GPT-5.6 Luna
OpenAI
 $0.032600 (rounded ~ $0.03) ↑ 101.9% more ↑ 7.8% more
#8 Gemini 3.6 Flash
Google
 $0.048750 (rounded ~ $0.05) ↑ 201.9% more ↑ 61.2% more
#9 Gemini 3.5 Flash
Google
 $0.048900 (rounded ~ $0.05) ↑ 202.8% more ↑ 61.7% more
#10 Claude Sonnet 5
Anthropic
 $0.065000 (rounded ~ $0.07) ↑ 302.5% more ↑ 114.9% more
#11 Gemini 3.1 Flash
Google
 $0.065200 (rounded ~ $0.07) ↑ 303.7% more ↑ 115.6% more
#12 GPT-5.6 Terra
OpenAI
 $0.081500 (rounded ~ $0.08) ↑ 404.6% more ↑ 169.5% more
#13 Claude Sonnet 4.6
Anthropic
 $0.097500 (rounded ~ $0.10) ↑ 503.7% more ↑ 222.4% more
#14 Claude Opus 4.7
Anthropic
 $0.162500 (rounded ~ $0.16) ↑ 906.2% more ↑ 437.4% more
#15 Claude Opus 5
Anthropic
 $0.162500 (rounded ~ $0.16) ↑ 906.2% more ↑ 437.4% more
#16 Claude Opus 4.8
Anthropic
 $0.162500 (rounded ~ $0.16) ↑ 906.2% more ↑ 437.4% more
#17 Claude Opus 4.6
Anthropic
 $0.162500 (rounded ~ $0.16) ↑ 906.2% more ↑ 437.4% more
#18 GPT-5.4
OpenAI
 $0.163000 (rounded ~ $0.16) ↑ 909.3% more ↑ 439% more
#19 GPT-5.4 Thinking
OpenAI
 $0.163000 (rounded ~ $0.16) ↑ 909.3% more ↑ 439% more
#20 Gemini 2.5 Pro
Google
 $0.163000 (rounded ~ $0.16) ↑ 909.3% more ↑ 439% more
#21 GPT-5.5 Instant
OpenAI
 $0.163000 (rounded ~ $0.16) ↑ 909.3% more ↑ 439% more
#22 GPT-5.6 Sol
OpenAI
 $0.163000 (rounded ~ $0.16) ↑ 909.3% more ↑ 439% more
#23 Grok 4.3
xAI
 $0.257600 (rounded ~ $0.26) ↑ 1495% more ↑ 751.9% more
#24 Grok 4.20 Beta
xAI
 $0.257600 (rounded ~ $0.26) ↑ 1495% more ↑ 751.9% more
#25 Gemini 3.1 Pro
Google
 $0.259600 ↑ 1507.4% more ↑ 758.5% more
#26 Claude Fable 5.1
Anthropic
 $0.310000 ↑ 1819.5% more ↑ 925.1% more
#27 Claude Mythos 5.1
Anthropic
 $0.310000 ↑ 1819.5% more ↑ 925.1% more
#28 Claude Fable 5
Anthropic
 $0.325000 (rounded ~ $0.33) ↑ 1912.4% more ↑ 974.7% more
#29 Claude Mythos 5
Anthropic
 $0.325000 (rounded ~ $0.33) ↑ 1912.4% more ↑ 974.7% more
#30 GPT-5.5
OpenAI
 $0.649000 (rounded ~ $0.65) ↑ 3918.6% more ↑ 2046.2% more
#31 GPT-6 Astra
OpenAI
 $1.300000 ↑ 7949.5% more ↑ 4198.9% more
#32 GPT-6 Astra
OpenAI
 $1.300000 ↑ 7949.5% more ↑ 4198.9% more
🏆

Gemini 3.1 Flash Lite
Google

$0.008150 (rounded ~ $0.01)
vs Mistral Large 3: ↓ 49.5%
vs Llama 4 Maverick: ↓ 73%
🥈

Gemini 3.5 Flash-Lite
Google

$0.009850
vs Mistral Large 3: ↓ 39%
vs Llama 4 Maverick: ↓ 67.4%
🥉

Gemini 2.5 Flash
Google

$0.009850
vs Mistral Large 3: ↓ 39%
vs Llama 4 Maverick: ↓ 67.4%
#4

Gemini 3.8 Flash
Google

$0.024375 (rounded ~ $0.02)
vs Mistral Large 3: ↑ 50.9%
vs Llama 4 Maverick: ↓ 19.4%
#5

GPT-5.4 mini
OpenAI

$0.024450 (rounded ~ $0.02)
vs Mistral Large 3: ↑ 51.4%
vs Llama 4 Maverick: ↓ 19.1%
#6

Claude Haiku 4.5
Anthropic

$0.032500 (rounded ~ $0.03)
vs Mistral Large 3: ↑ 101.2%
vs Llama 4 Maverick: ↑ 7.5%
#7

GPT-5.6 Luna
OpenAI

$0.032600 (rounded ~ $0.03)
vs Mistral Large 3: ↑ 101.9%
vs Llama 4 Maverick: ↑ 7.8%
#8

Gemini 3.6 Flash
Google

$0.048750 (rounded ~ $0.05)
vs Mistral Large 3: ↑ 201.9%
vs Llama 4 Maverick: ↑ 61.2%
#9

Gemini 3.5 Flash
Google

$0.048900 (rounded ~ $0.05)
vs Mistral Large 3: ↑ 202.8%
vs Llama 4 Maverick: ↑ 61.7%
#10

Claude Sonnet 5
Anthropic

$0.065000 (rounded ~ $0.07)
vs Mistral Large 3: ↑ 302.5%
vs Llama 4 Maverick: ↑ 114.9%
#11

Gemini 3.1 Flash
Google

$0.065200 (rounded ~ $0.07)
vs Mistral Large 3: ↑ 303.7%
vs Llama 4 Maverick: ↑ 115.6%
#12

GPT-5.6 Terra
OpenAI

$0.081500 (rounded ~ $0.08)
vs Mistral Large 3: ↑ 404.6%
vs Llama 4 Maverick: ↑ 169.5%
#13

Claude Sonnet 4.6
Anthropic

$0.097500 (rounded ~ $0.10)
vs Mistral Large 3: ↑ 503.7%
vs Llama 4 Maverick: ↑ 222.4%
#14

Claude Opus 4.7
Anthropic

$0.162500 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 906.2%
vs Llama 4 Maverick: ↑ 437.4%
#15

Claude Opus 5
Anthropic

$0.162500 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 906.2%
vs Llama 4 Maverick: ↑ 437.4%
#16

Claude Opus 4.8
Anthropic

$0.162500 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 906.2%
vs Llama 4 Maverick: ↑ 437.4%
#17

Claude Opus 4.6
Anthropic

$0.162500 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 906.2%
vs Llama 4 Maverick: ↑ 437.4%
#18

GPT-5.4
OpenAI

$0.163000 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 909.3%
vs Llama 4 Maverick: ↑ 439%
#19

GPT-5.4 Thinking
OpenAI

$0.163000 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 909.3%
vs Llama 4 Maverick: ↑ 439%
#20

Gemini 2.5 Pro
Google

$0.163000 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 909.3%
vs Llama 4 Maverick: ↑ 439%
#21

GPT-5.5 Instant
OpenAI

$0.163000 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 909.3%
vs Llama 4 Maverick: ↑ 439%
#22

GPT-5.6 Sol
OpenAI

$0.163000 (rounded ~ $0.16)
vs Mistral Large 3: ↑ 909.3%
vs Llama 4 Maverick: ↑ 439%
#23

Grok 4.3
xAI

$0.257600 (rounded ~ $0.26)
vs Mistral Large 3: ↑ 1495%
vs Llama 4 Maverick: ↑ 751.9%
#24

Grok 4.20 Beta
xAI

$0.257600 (rounded ~ $0.26)
vs Mistral Large 3: ↑ 1495%
vs Llama 4 Maverick: ↑ 751.9%
#25

Gemini 3.1 Pro
Google

$0.259600
vs Mistral Large 3: ↑ 1507.4%
vs Llama 4 Maverick: ↑ 758.5%
#26

Claude Fable 5.1
Anthropic

$0.310000
vs Mistral Large 3: ↑ 1819.5%
vs Llama 4 Maverick: ↑ 925.1%
#27

Claude Mythos 5.1
Anthropic

$0.310000
vs Mistral Large 3: ↑ 1819.5%
vs Llama 4 Maverick: ↑ 925.1%
#28

Claude Fable 5
Anthropic

$0.325000 (rounded ~ $0.33)
vs Mistral Large 3: ↑ 1912.4%
vs Llama 4 Maverick: ↑ 974.7%
#29

Claude Mythos 5
Anthropic

$0.325000 (rounded ~ $0.33)
vs Mistral Large 3: ↑ 1912.4%
vs Llama 4 Maverick: ↑ 974.7%
#30

GPT-5.5
OpenAI

$0.649000 (rounded ~ $0.65)
vs Mistral Large 3: ↑ 3918.6%
vs Llama 4 Maverick: ↑ 2046.2%
#31

GPT-6 Astra
OpenAI

$1.300000
vs Mistral Large 3: ↑ 7949.5%
vs Llama 4 Maverick: ↑ 4198.9%
#32

GPT-6 Astra
OpenAI

$1.300000
vs Mistral Large 3: ↑ 7949.5%
vs Llama 4 Maverick: ↑ 4198.9%
✨ 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.

For massive RAG pipelines hitting 100M tokens monthly, architecture and data efficiency are paramount. Mistral Large 3 and Llama 4 Maverick represent two distinct schools of thought in high-scale AI deployment. Mistral Large 3 is often favored for its precision and instruction-following capabilities in multi-step RAG workflows. When your Q&A system needs to route queries across multiple document categories, its ability to handle complex logic with lower latency can improve the overall throughput of your system.

Llama 4 Maverick, with its 1M context window, offers a different advantage: the ability to process massive inputs without aggressive chunking. In some RAG architectures, being able to pass entire documents or larger context blocks directly to the model can actually reduce the complexity of the retrieval layer, potentially leading to more accurate ‘holistic’ answers. If your organization’s internal knowledge base is composed of long-form, highly dense technical documentation, the ability to ingest larger context chunks can reduce the ‘lost in the middle’ phenomenon common in naive RAG systems.

Choosing between these two depends on your infrastructure’s existing investments. Mistral models generally integrate well into pipelines requiring specific European data compliance or those favoring a concise, high-density reasoning style. Llama 4 Maverick appeals to teams building on open-weights infrastructure who want the flexibility to optimize the model’s behavior at a deeper level. Both are highly cost-effective at the 100M-token scale, but the decision should hinge on whether your documents are better served by surgical retrieval (Mistral) or expansive, long-context ingestion (Llama).

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.

Related model pricing

Mistral Large 3 currently costs $0.50 / $1.50 per 1M tokens. These are the models worth pricing against it, taken live from the tracked registry.

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