Gemini 3.8 Flash Google 1048576
💰 Total Cost Calculation (from Plugin)
Output: $0.004688
Output: $0.004688
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Multimodal Input Details
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 150,000 input tokens and 5,000 output tokens:
- Input Cost: $0.114525 (rounded ~ $0.11)
- Output Cost: $0.004688
- Total Cost: $0.098598 (rounded ~ $0.10)
- Cost per 1K tokens: $0.000160
- Tokens per dollar: 6,245,563 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: 30 minutes, 47.58 seconds
- Latency: 105 milliseconds to first token
- Base Throughput: 340 tokens/second
- Effective Throughput: 333 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to Gemini 3.8 Flash| Rank | AI Model & Provider | Total Cost | vs Gemini 3.8 Flash |
|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.033179 (rounded ~ $0.03) Best Value | ↓ 66.3% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.040689 | ↓ 58.7% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.040689 | ↓ 58.7% cheaper |
| #4 |
Gemini 3.6 Flash
Google
|
$0.098598 (rounded ~ $0.10) | Same price |
| #5 |
Gemini 4 Argon
Google
|
$0.262928 (rounded ~ $0.26) | ↑ 166.7% more |
| #6 |
Gemini 3.1 Flash
Google
|
$0.265428 (rounded ~ $0.27) | ↑ 169.2% more |
| #7 |
Gemini 2.5 Pro
Google
|
$0.663570 (rounded ~ $0.66) | ↑ 573% more |
| #8 |
Grok 4.3
xAI
|
$1.021712 (rounded ~ $1.02) | ↑ 936.2% more |
| #9 |
Grok 4.3
xAI
|
$1.021712 (rounded ~ $1.02) | ↑ 936.2% more |
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.6 Flash Google
Gemini 4 Argon Google
Gemini 3.1 Flash Google
Gemini 2.5 Pro Google
Grok 4.3 xAI
Grok 4.3 xAI
Optimizing Audio Pipelines for Game Studios
For AAA game studios, podcast transcription is a vital tool for content creation, internal lore management, and community engagement. Whether you are transcribing internal developer diaries, community podcasts, or marketing content, high-accuracy diarization is essential to distinguish between multiple speakers and maintain continuity in both narrative and brand voice. Gemini 3.8 Flash stands out for this specific workload due to its native multimodal capabilities.
Unlike older, fragmented pipelines that required separate speech-to-text models followed by secondary LLM analysis, this model handles audio ingestion directly. This architecture significantly reduces the complexity of your asset pipeline and minimizes latency, allowing for rapid ingestion of long-form audio files. The diarization accuracy is particularly critical for game studios where distinct character voices or developer personalities must be correctly attributed in the final transcript.
Beyond simple transcription, the ability to feed audio into a reasoning-capable model allows for immediate summarization, key-point extraction, and content repurposing for different social platforms without intermediate processing steps. This seamless integration streamlines the transition from raw audio to polished, searchable game studio assets. When evaluating your AI stack, consider the model’s performance on dense audio inputs and its ability to maintain structural context over the full 240-minute duration. The efficiency of handling this volume in one unified step significantly lowers technical overhead compared to segmenting audio files, ensuring that the final output maintains the integrity required for your internal database and lore wikis.