Gemini 3.8 Flash Pricing for 50,000 Hours of Podcast Transcription

Complete Analysis: 6,360,005,000 tokens for Gemini 3.8 Flash
🎧 3000000min Audio ⚡ 50% Cached

Complete analysis of pricing, performance, and use cases for Google's Gemini 3.8 Flash model with 3000000min Audio, 50% Cached.

⚡ Caching Optimized (up to 90% savings) 📊 Batch API
$655.879688 Total Cost
6,360,005,000 Total Tokens
5300 hours, 15.18 seconds Processing Time
333 Effective Tokens/Sec

Click Recalculate to update after making changes

ℹ️ Bulk Calculation: Total volume exceeds single-request limit of 1,048,576 tokens. Budgeting mode active.

Select AI Model

Gemini 3.8 Flash

GoogleMax Context: 1,048,576 tokens
$0.75 / $3.75 per 1M tokens
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.
Will auto-convert to minutes for Voxtral models (9000 tokens = 1 min)
$0.067 per 1,000 pixels

Calculate Token Costs

$596.250000 Input Cost
$0.004688 Output Cost
$0.000000 Unit Cost
$0.000000 Search Cost
$0.000000 Request Fee
$0.000000 Tool Fee
$0.000000 Code Execution
6,360,005,000Total Tokens
$0.000103Cost per 1K
9,696,908Tokens per $

📊 Advanced Cost Breakdown

Processing Speed

318000m 15s Processing Time
340 Tokens/Second
105ms Time to First Token
333 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


📚 Research & Citations

Fee per source cited

🎤 Realtime Audio & Video

Session length for billing

Gemini 3.8 Flash Google 1048576

$655.879688
Total Cost
⚠️ Bulk Calculation: Total volume exceeds single-request limit of 1,048,576 tokens. Budgeting mode active.
🎧 3000000min Audio ⚡ 50% Cached 📊 Batch API
👁️
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) $1192.504688 (rounded ~ $1,192.50) Input: $1192.500000
Output: $0.004688
Optimized Cost $655.879688 Input: $1192.500000
Output: $0.004688
Unit: $0.000000
Fees: $0.000000
Total Savings $536.625000 (rounded ~ $536.63) 45.0% discount

Advanced Cost Breakdown (from Plugin)

🖼️ Multimodal Input
$0.000000
5,760,000,000 tokens
📊 Batch API
50.0% off
Asynchronous processing discount

Multimodal Input Details

🎧 Audio
Duration: 3000000 minutes
Cost: $0.000000

Detailed Cost Analysis (from Plugin)

For 600,000,000 input tokens and 5,000 output tokens:

  • Input Cost: $1192.500000
  • Output Cost: $0.004688
  • Total Cost: $655.879688
  • Cost per 1K tokens: $0.000103
  • Tokens per dollar: 9,696,908 tokens
  • Context Window: 1048576 tokens

Speed & Performance Analysis

With a processing speed of 340 tokens per second and 105ms time to first token:

  • Processing Time: 5300 hours, 15.18 seconds
  • Latency: 105 milliseconds to first token
  • Base Throughput: 340 tokens/second
  • Effective Throughput: 333 tokens/second (temperature-adjusted)

Best Use Cases

Large-scale audio transcription and diarization pipelines requiring native multimodal support.

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✨ Market Recommendations AI Model Registry

← Back to Gemini 3.8 Flash
📋 Active Input Parameters
Input Tokens: 600,000,000
Output Tokens: 5,000
Batch API: Enabled (50% discount)
Cached Tokens: 50%
Audio: 3000000 minutes
🔍
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.

For high-volume media operations, Gemini 3.8 Flash offers a compelling balance of throughput and accuracy for native audio processing. Transcription pipelines operating at enterprise scale—specifically those managing 50,000 hours of content monthly—require models that can ingest raw audio directly without the overhead of external ASR services. Gemini 3.8 Flash excels here, providing a streamlined architecture that reduces latency in production environments.

Document specialists moving from traditional OCR to multimedia archival will find the multimodal capabilities of this model particularly relevant. Unlike text-only models that rely on downstream services, Gemini 3.8 Flash handles the acoustic nuances often found in podcasts, such as overlapping speakers and ambient noise, with a focus on diarization efficiency. For platform leads, this integration simplifies the stack, reducing the number of moving parts in the ingestion pipeline. Choosing this model for audio-heavy workloads allows engineering teams to consolidate their infrastructure, moving away from fragmented service architectures toward a unified multimodal approach. This is the primary driver for adoption in media and publishing, where the volume of content requires predictable latency and consistent performance across diverse audio quality levels.

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 audio billing work?
Audio models are billed by token, not by minute. Voxtral Small 24B costs $0.10 per 1M input tokens and $0.30 per 1M output tokens, matching Mistral Small 3. GPT Realtime Mini uses standard token billing. There are no silence keep-alive surcharges or per-minute duration fees on either provider.
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.