Gemini 3.5 Flash Google 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.002250
Output: $0.002250
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Multimodal Input Details
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 10,000 input tokens and 1,000 output tokens:
- Input Cost: $43.203750 (rounded ~ $43.20)
- Output Cost: $0.002250
- Total Cost: $23.764313 (rounded ~ $23.76)
- Cost per 1K tokens: $0.000206
- Tokens per dollar: 4,848,068 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 850 tokens per second and 90ms time to first token:
- Processing Time: 40 hours, 17 minutes, 10.50 seconds
- Latency: 90 milliseconds to first token
- Base Throughput: 850 tokens/second
- Effective Throughput: 794 tokens/second (temperature-adjusted)
Best Use Cases
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💰 Total Cost Calculation (from Plugin)
Output: $0.000075
Output: $0.000075
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 10,000 input tokens and 1,000 output tokens:
- Input Cost: $0.000250
- Output Cost: $0.000075
- Total Cost: $0.000213
- Cost per 1K tokens: $0.000019
- Tokens per dollar: 51,764,706 tokens
- Context Window: 32000 tokens
Speed & Performance Analysis
With a processing speed of 400 tokens per second and 150ms time to first token:
- Processing Time: 29.61 seconds
- Latency: 150 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 374 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Voxtral Small 24B. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
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Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to Gemini 3.5 Flash| Rank | AI Model & Provider | Total Cost | vs Gemini 3.5 Flash | vs Voxtral Small 24B |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$3.960719 Best Value | ↓ 83.3% cheaper | ↑ 1863767.6% more |
| 🥈 |
Gemini 2.5 Flash
Google
|
$4.753038 (rounded ~ $4.75) | ↓ 80% cheaper | ↑ 2236623.5% more |
| 🥉 |
Grok 4.3
xAI
|
$19.802344 (rounded ~ $19.80) | ↓ 16.7% cheaper | ↑ 9318650% more |
| #4 |
Gemini 3.1 Flash
Google
|
$31.685750 (rounded ~ $31.69) | ↑ 33.3% more | ↑ 14910841.2% more |
| #5 |
Gemini 2.5 Pro
Google
|
$79.214375 (rounded ~ $79.21) | ↑ 233.3% more | ↑ 37277252.9% more |
| #6 |
Gemini 2.5 Pro
Google
|
$79.214375 (rounded ~ $79.21) | ↑ 233.3% more | ↑ 37277252.9% more |
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Grok 4.3 xAI
Gemini 3.1 Flash Google
Gemini 2.5 Pro Google
Gemini 2.5 Pro Google
Choosing the right transcription engine depends on your primary goal: deep, agentic analysis or streamlined, cost-effective conversion. Gemini 3.5 Flash acts as a comprehensive “reasoning engine,” ideal if your workflow requires more than just text—if you need to summarize, extract data, or generate follow-up emails directly from the audio, this model provides the reasoning depth necessary to bridge the gap between transcription and action. Conversely, Voxtral Small 24B is purpose-built for the transcription itself. It is a highly efficient, lightweight model designed to maximize transcription throughput and minimize latency, making it the preferred choice for teams that already have mature text-processing pipelines and simply need to convert massive quantities of audio into high-fidelity transcripts with precise diarization and word-level timestamps. For a real estate firm, the decision hinges on your current infrastructure. If you are starting from scratch, Gemini’s ability to handle the entire chain—from audio to CRM entry—is unmatched. If you are optimizing a high-volume, specialized pipeline where accuracy, speed, and privacy-first local processing are paramount, Voxtral’s architecture offers a more focused, modular approach. Both models scale effortlessly to 60,000 minutes of audio per month, but they serve different roles in the modern content production stack.