Claude Sonnet 4.6 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.018750 (rounded ~ $0.02)
Output: $0.018750 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 5,000 output tokens:
- Input Cost: $0.750000
- Output Cost: $0.018750 (rounded ~ $0.02)
- Total Cost: $0.633750 (rounded ~ $0.63)
- Cost per 1K tokens: $0.000631
- Tokens per dollar: 1,585,799 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 450 tokens per second and 200ms time to first token:
- Processing Time: 39 minutes, 49.85 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 421 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Claude Sonnet 4.6. 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
💰 Total Cost Calculation (from Plugin)
Output: $0.045000 (rounded ~ $0.05)
Output: $0.045000 (rounded ~ $0.05)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 5,000 output tokens:
- Input Cost: $2.000000
- Output Cost: $0.045000 (rounded ~ $0.05)
- Total Cost: $1.685000 (rounded ~ $1.69)
- Cost per 1K tokens: $0.001677
- Tokens per dollar: 596,439 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: 44 minutes, 48.56 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 374 tokens/second (temperature-adjusted)
Best Use Cases
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 Claude Sonnet 4.6| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 4.6 | vs Gemini 3.1 Pro |
|---|---|---|---|---|
| 🏆 |
Grok 4.20 Beta
xAI
|
$0.417500 (rounded ~ $0.42) Best Value | ↓ 34.1% cheaper | ↓ 75.2% cheaper |
| 🥈 |
Gemini 2.5 Pro
Google
|
$1.062500 (rounded ~ $1.06) | ↑ 67.7% more | ↓ 36.9% cheaper |
| 🥉 |
Gemini 3.1 Pro
Google
|
$1.685000 (rounded ~ $1.69) | ↑ 165.9% more | Same price |
| #4 |
GPT-5.4
OpenAI
|
$2.106250 (rounded ~ $2.11) | ↑ 232.3% more | ↑ 25% more |
| #5 |
GPT-5.4 Thinking
OpenAI
|
$2.106250 (rounded ~ $2.11) | ↑ 232.3% more | ↑ 25% more |
| #6 |
GPT-5.4 Thinking
OpenAI
|
$2.106250 (rounded ~ $2.11) | ↑ 232.3% more | ↑ 25% more |
Grok 4.20 Beta xAI
Gemini 2.5 Pro Google
Gemini 3.1 Pro Google
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.4 Thinking OpenAI
Evaluating Mid-Tier Efficiency: Claude Sonnet 4.6 vs Gemini 3.1 Pro
For EdTech product managers, generating storyboard descriptions for video lessons requires a balance of creative output and operational scale. When evaluating models for 1-million-token storyboarding workloads, Claude Sonnet 4.6 and Gemini 3.1 Pro emerge as leading options. These models provide the “intelligence sweet spot”—high enough reasoning for pedagogical accuracy without the extreme costs of top-tier flagship models.
Claude Sonnet 4.6 is favored for its exceptional instruction-following and safety alignment. In a K-12 environment, ensuring that storyboard descriptions remain age-appropriate and focused on the learning objective is critical. Sonnet’s ability to maintain a consistent “voice” across hundreds of scene descriptions makes it ideal for building cohesive curricula. Gemini 3.1 Pro, meanwhile, is optimized for massive context and multimodal breadth. Its 2-million-token window allows it to reference entire textbooks while generating storyboards, ensuring every scene is visually grounded in the source material.
- Claude Sonnet 4.6: Best for complex, logic-driven scene descriptions where pedagogical precision and safety are the top priorities.
- Gemini 3.1 Pro: Preferred for large-scale projects requiring the model to ingest and maintain consistency across massive amounts of curricular data.
Choosing between these models often depends on your specific context needs. While Sonnet offers a higher degree of creative steerability, Gemini’s vast context window and multimodal features make it a formidable choice for data-intensive AI tutoring applications.