Code Assist Pricing: Llama 4 Maverick vs Gemini 3.1 Pro for 5,000 Token Context

Llama 4 Maverick (400B) vs Gemini 3.1 Pro
Complete Comparison: 5,000 input tokens × 1,000 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)
Comparison Criteria Llama 4 Maverick (400B)
Meta AI
Gemini 3.1 Pro
Google
Calculation Results (Current Inputs) (40% cached)
Input Tokens 5,000 5,000
Output Tokens 1,000 1,000
Cost Breakdown
Input Cost $0.000750Best $0.010000Worst
Output Cost $0.000600Best $0.012000 (rounded ~ $0.01)Worst
Unit Cost (Audio/OCR) $0.000000 $0.000000
Service Fees $0.000000 $0.000000
Total Cost $0.001350 Best Value $0.018400 (rounded ~ $0.02) Most Expensive
Processing Time 16.08 seconds 16.08 seconds
Tokens per Second 400 400
Time to First Token 150ms Best 220ms Worst
Cost per 1K tokens $0.000225Best $0.003067Worst
Tokens per Dollar 4,444,444Best Value 326,087Worst Value
Cost per 1 Million Tokens (Informational)
Input Cost / 1M (Base) $0.150000Best $2.000000Worst
Output Cost / 1M (Base) $0.600000Best $12.000000Worst
Input Cost / 1M (Optimized) $0.150000Best
Optimizations: No optimizations applied
$2.000000Worst
Optimizations: No optimizations applied
Output Cost / 1M (Optimized) $0.600000Best
Optimizations: No optimizations applied
$12.000000Worst
Optimizations: No optimizations applied
Capabilities & Advanced Features
Images Support ✓ Supported ✓ Supported
Video Support ✗ Not Supported ✓ Supported
Audio Support ✗ Not Supported ✓ Supported
Caching Support
40
✗ Not Supported requested ✓ Supported
Batch API Support ✓ Supported ✓ Supported
Tool Usage Support ✓ Supported ✓ Supported
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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)
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

$0.001350 Total Cost
$0.000750 Input Cost
$0.000600 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
6,000Total Tokens
$0.000225Cost per 1K
4,444,444Tokens per $
📊 Advanced Cost Breakdown

Processing Speed

16.08s Processing Time
400 Tokens/Second
150ms Time to First Token
377 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

$0.001350
Total Cost
⚡ 40% Cached 🔧 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) $0.001350 Input: $0.000750
Output: $0.000600
Optimized Cost $0.001350 Input: $0.000750
Output: $0.000600
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis (from Plugin)

For 5,000 input tokens and 1,000 output tokens:

  • Input Cost: $0.000750
  • Output Cost: $0.000600
  • Total Cost: $0.001350
  • Cost per 1K tokens: $0.000225
  • Tokens per dollar: 4,444,444 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: 16.08 seconds
  • Latency: 150 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 377 tokens/second (temperature-adjusted)

Best Use Cases

These models are strong contenders for advanced code generationoffering large context windows and multimodal capabilities. Llama 4 Maverick excels in open-source flexibility and broad understandingwhile Gemini 3.1 Pro brings Google's powerful multimodal reasoning and integration ecosystem to the table.

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 →

Gemini 3.1 Pro Google 2000000

$0.018400 (rounded ~ $0.02)
Total Cost
⚡ 40% Cached 🔧 Tools
👁️
Vision/Images
✓ Available
🎧
Audio Processing
✓ Available
🎥
Video Analysis
✓ Available
🔧
Tool Usage
✓ Available
📄
OCR Support
✗ Not Available
📊
Batch API
✓ Available
⚡
Caching
✓ Available
90% savings

💰 Total Cost Calculation (from Plugin)

Base Cost (No Optimizations) $0.022000 (rounded ~ $0.02) Input: $0.010000
Output: $0.012000 (rounded ~ $0.01)
Optimized Cost $0.018400 (rounded ~ $0.02) Input: $0.010000
Output: $0.012000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Total Savings $0.003600 16.4% discount

Detailed Cost Analysis (from Plugin)

For 5,000 input tokens and 1,000 output tokens:

  • Input Cost: $0.010000
  • Output Cost: $0.012000 (rounded ~ $0.01)
  • Total Cost: $0.018400 (rounded ~ $0.02)
  • Cost per 1K tokens: $0.003067
  • Tokens per dollar: 326,087 tokens
  • Context Window: 2000000 tokens

Speed & Performance Analysis

With a processing speed of 400 tokens per second and 220ms time to first token:

  • Processing Time: 16.08 seconds
  • Latency: 220 milliseconds to first token
  • Base Throughput: 400 tokens/second
  • Effective Throughput: 377 tokens/second (temperature-adjusted)

Best Use Cases

These models are strong contenders for advanced code generationoffering large context windows and multimodal capabilities. Llama 4 Maverick excels in open-source flexibility and broad understandingwhile Gemini 3.1 Pro brings Google's powerful multimodal reasoning and integration ecosystem to the table.

Want this applied to YOUR actual stack?

This calculator shows the math for Gemini 3.1 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: 5,000
Output Tokens: 1,000
Cached Tokens: 40%
Tools: Enabled
Rank AI Model & Provider Total Cost vs Llama 4 Maverick (400B) vs Gemini 3.1 Pro
🏆 Mistral Small 3
Mistral AI
 $0.000620 Best Value ↓ 54.1% cheaper ↓ 96.6% cheaper
🥈 Grok Code Fast 1
xAI
 $0.002140 ↑ 58.5% more ↓ 88.4% cheaper
🥉 Gemini 3.1 Flash Lite
Google
 $0.002300 ↑ 70.4% more ↓ 87.5% cheaper
#4 Mistral Large 3
Mistral AI
 $0.003100 ↑ 129.6% more ↓ 83.2% cheaper
#5 Gemini 2.5 Flash
Google
 $0.003460 ↑ 156.3% more ↓ 81.2% cheaper
#6 Gemini 3.1 Flash
Google
 $0.004600 ↑ 240.7% more ↓ 75% cheaper
#7 Kimi K2.5
Moonshot AI
 $0.005004 (rounded ~ $0.01) ↑ 270.7% more ↓ 72.8% cheaper
#8 Grok 4.3
xAI
 $0.006500 (rounded ~ $0.01) ↑ 381.5% more ↓ 64.7% cheaper
#9 GPT-5.4 mini
OpenAI
 $0.006900 (rounded ~ $0.01) ↑ 411.1% more ↓ 62.5% cheaper
#10 Kimi K2.6
Moonshot AI
 $0.007173 (rounded ~ $0.01) ↑ 431.3% more ↓ 61% cheaper
#11 o4-mini Deep Research
OpenAI
 $0.007200 (rounded ~ $0.01) ↑ 433.3% more ↓ 60.9% cheaper
#12 o4-mini
OpenAI
 $0.007920 (rounded ~ $0.01) ↑ 486.7% more ↓ 57% cheaper
#13 Claude Haiku 4.5
Anthropic
 $0.008200 (rounded ~ $0.01) ↑ 507.4% more ↓ 55.4% cheaper
#14 Grok 4.20 Beta
xAI
 $0.012400 (rounded ~ $0.01) ↑ 818.5% more ↓ 32.6% cheaper
#15 Gemini 3.5 Flash
Google
 $0.013800 (rounded ~ $0.01) ↑ 922.2% more ↓ 25% cheaper
#16 Gemini 2.5 Pro
Google
 $0.014000 (rounded ~ $0.01) ↑ 937% more ↓ 23.9% cheaper
#17 Gemini 3.1 Pro
Google
 $0.018400 (rounded ~ $0.02) ↑ 1263% more Same price
#18 GPT-5.3 Codex Spark
OpenAI
 $0.019600 ↑ 1351.9% more ↑ 6.5% more
#19 GPT-5.3 Instant
OpenAI
 $0.019600 ↑ 1351.9% more ↑ 6.5% more
#20 GPT-5.4
OpenAI
 $0.023000 (rounded ~ $0.02) ↑ 1603.7% more ↑ 25% more
#21 GPT-5.4 Thinking
OpenAI
 $0.023000 (rounded ~ $0.02) ↑ 1603.7% more ↑ 25% more
#22 Claude Sonnet 4.6
Anthropic
 $0.024600 (rounded ~ $0.02) ↑ 1722.2% more ↑ 33.7% more
#23 Claude Opus 4.7
Anthropic
 $0.041000 (rounded ~ $0.04) ↑ 2937% more ↑ 122.8% more
#24 Claude Opus 4.8
Anthropic
 $0.041000 (rounded ~ $0.04) ↑ 2937% more ↑ 122.8% more
#25 Claude Opus 4.6
Anthropic
 $0.041000 (rounded ~ $0.04) ↑ 2937% more ↑ 122.8% more
#26 GPT-5.5
OpenAI
 $0.046000 (rounded ~ $0.05) ↑ 3307.4% more ↑ 150% more
#27 GPT-5.5 Instant
OpenAI
 $0.046000 (rounded ~ $0.05) ↑ 3307.4% more ↑ 150% more
#28 o3 Deep Research
OpenAI
 $0.072000 (rounded ~ $0.07) ↑ 5233.3% more ↑ 291.3% more
#29 o3 Pro
OpenAI
 $0.144000 (rounded ~ $0.14) ↑ 10566.7% more ↑ 682.6% more
#30 GPT-5.2 Pro
OpenAI
 $0.235200 (rounded ~ $0.24) ↑ 17322.2% more ↑ 1178.3% more
#31 GPT-5.2 Pro
OpenAI
 $0.235200 (rounded ~ $0.24) ↑ 17322.2% more ↑ 1178.3% more
🏆

Mistral Small 3
Mistral AI

$0.000620
vs Llama 4 Maverick (400B): ↓ 54.1%
vs Gemini 3.1 Pro: ↓ 96.6%
🥈

Grok Code Fast 1
xAI

$0.002140
vs Llama 4 Maverick (400B): ↑ 58.5%
vs Gemini 3.1 Pro: ↓ 88.4%
🥉

Gemini 3.1 Flash Lite
Google

$0.002300
vs Llama 4 Maverick (400B): ↑ 70.4%
vs Gemini 3.1 Pro: ↓ 87.5%
#4

Mistral Large 3
Mistral AI

$0.003100
vs Llama 4 Maverick (400B): ↑ 129.6%
vs Gemini 3.1 Pro: ↓ 83.2%
#5

Gemini 2.5 Flash
Google

$0.003460
vs Llama 4 Maverick (400B): ↑ 156.3%
vs Gemini 3.1 Pro: ↓ 81.2%
#6

Gemini 3.1 Flash
Google

$0.004600
vs Llama 4 Maverick (400B): ↑ 240.7%
vs Gemini 3.1 Pro: ↓ 75%
#7

Kimi K2.5
Moonshot AI

$0.005004 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 270.7%
vs Gemini 3.1 Pro: ↓ 72.8%
#8

Grok 4.3
xAI

$0.006500 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 381.5%
vs Gemini 3.1 Pro: ↓ 64.7%
#9

GPT-5.4 mini
OpenAI

$0.006900 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 411.1%
vs Gemini 3.1 Pro: ↓ 62.5%
#10

Kimi K2.6
Moonshot AI

$0.007173 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 431.3%
vs Gemini 3.1 Pro: ↓ 61%
#11

o4-mini Deep Research
OpenAI

$0.007200 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 433.3%
vs Gemini 3.1 Pro: ↓ 60.9%
#12

o4-mini
OpenAI

$0.007920 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 486.7%
vs Gemini 3.1 Pro: ↓ 57%
#13

Claude Haiku 4.5
Anthropic

$0.008200 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 507.4%
vs Gemini 3.1 Pro: ↓ 55.4%
#14

Grok 4.20 Beta
xAI

$0.012400 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 818.5%
vs Gemini 3.1 Pro: ↓ 32.6%
#15

Gemini 3.5 Flash
Google

$0.013800 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 922.2%
vs Gemini 3.1 Pro: ↓ 25%
#16

Gemini 2.5 Pro
Google

$0.014000 (rounded ~ $0.01)
vs Llama 4 Maverick (400B): ↑ 937%
vs Gemini 3.1 Pro: ↓ 23.9%
#17

Gemini 3.1 Pro
Google

$0.018400 (rounded ~ $0.02)
vs Llama 4 Maverick (400B): ↑ 1263%
vs Gemini 3.1 Pro: Same
#18

GPT-5.3 Codex Spark
OpenAI

$0.019600
vs Llama 4 Maverick (400B): ↑ 1351.9%
vs Gemini 3.1 Pro: ↑ 6.5%
#19

GPT-5.3 Instant
OpenAI

$0.019600
vs Llama 4 Maverick (400B): ↑ 1351.9%
vs Gemini 3.1 Pro: ↑ 6.5%
#20

GPT-5.4
OpenAI

$0.023000 (rounded ~ $0.02)
vs Llama 4 Maverick (400B): ↑ 1603.7%
vs Gemini 3.1 Pro: ↑ 25%
#21

GPT-5.4 Thinking
OpenAI

$0.023000 (rounded ~ $0.02)
vs Llama 4 Maverick (400B): ↑ 1603.7%
vs Gemini 3.1 Pro: ↑ 25%
#22

Claude Sonnet 4.6
Anthropic

$0.024600 (rounded ~ $0.02)
vs Llama 4 Maverick (400B): ↑ 1722.2%
vs Gemini 3.1 Pro: ↑ 33.7%
#23

Claude Opus 4.7
Anthropic

$0.041000 (rounded ~ $0.04)
vs Llama 4 Maverick (400B): ↑ 2937%
vs Gemini 3.1 Pro: ↑ 122.8%
#24

Claude Opus 4.8
Anthropic

$0.041000 (rounded ~ $0.04)
vs Llama 4 Maverick (400B): ↑ 2937%
vs Gemini 3.1 Pro: ↑ 122.8%
#25

Claude Opus 4.6
Anthropic

$0.041000 (rounded ~ $0.04)
vs Llama 4 Maverick (400B): ↑ 2937%
vs Gemini 3.1 Pro: ↑ 122.8%
#26

GPT-5.5
OpenAI

$0.046000 (rounded ~ $0.05)
vs Llama 4 Maverick (400B): ↑ 3307.4%
vs Gemini 3.1 Pro: ↑ 150%
#27

GPT-5.5 Instant
OpenAI

$0.046000 (rounded ~ $0.05)
vs Llama 4 Maverick (400B): ↑ 3307.4%
vs Gemini 3.1 Pro: ↑ 150%
#28

o3 Deep Research
OpenAI

$0.072000 (rounded ~ $0.07)
vs Llama 4 Maverick (400B): ↑ 5233.3%
vs Gemini 3.1 Pro: ↑ 291.3%
#29

o3 Pro
OpenAI

$0.144000 (rounded ~ $0.14)
vs Llama 4 Maverick (400B): ↑ 10566.7%
vs Gemini 3.1 Pro: ↑ 682.6%
#30

GPT-5.2 Pro
OpenAI

$0.235200 (rounded ~ $0.24)
vs Llama 4 Maverick (400B): ↑ 17322.2%
vs Gemini 3.1 Pro: ↑ 1178.3%
#31

GPT-5.2 Pro
OpenAI

$0.235200 (rounded ~ $0.24)
vs Llama 4 Maverick (400B): ↑ 17322.2%
vs Gemini 3.1 Pro: ↑ 1178.3%
✨ 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.

Comparing Llama 4 Maverick and Gemini 3.1 Pro for Code Generation

When evaluating AI models for code generation IDEs, especially those handling context windows around 5,000 tokens, Llama 4 Maverick and Gemini 3.1 Pro represent powerful, albeit different, choices. UX designers must weigh their respective strengths for providing intelligent inline code suggestions and assistance.

Llama 4 Maverick, from Meta AI, offers the advantage of an open-weight model, providing flexibility and potential for fine-tuning within your specific development environment. It’s known for robust text understanding and reasoning, making it adept at comprehending complex code structures and generating relevant continuations. Its large context window is a significant asset for analyzing more extensive code files.

Google’s Gemini 3.1 Pro, on the other hand, brings strong multimodal capabilities and a vast, integrated ecosystem. While code generation is primarily text-based, Gemini’s ability to process various data types can be beneficial for understanding project contexts that involve diagrams, specifications, or even visual debugging aids. Its pricing structure is tiered, and it excels at complex reasoning tasks.

For UX designers, the choice hinges on priorities: the open-source nature and adaptability of Llama 4 Maverick versus the comprehensive multimodal features and ecosystem integration of Gemini 3.1 Pro. Both can deliver high-quality code suggestions, but the decision might be influenced by factors like deployment strategy, existing cloud infrastructure, and the need for advanced reasoning beyond pure code.

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.