Claude Sonnet 4.6 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.009375
Output: $0.009375
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 2,500 output tokens:
- Input Cost: $0.375000 (rounded ~ $0.38)
- Output Cost: $0.009375
- Total Cost: $0.283125 (rounded ~ $0.28)
- Cost per 1K tokens: $0.000563
- Tokens per dollar: 1,774,834 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: 18 minutes, 59.18 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 441 tokens/second (temperature-adjusted)
Best Use Cases
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💰 Total Cost Calculation (from Plugin)
Output: $0.002813
Output: $0.002813
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 2,500 output tokens:
- Input Cost: $0.093750 (rounded ~ $0.09)
- Output Cost: $0.002813
- Total Cost: $0.071250 (rounded ~ $0.07)
- Cost per 1K tokens: $0.000142
- Tokens per dollar: 7,052,632 tokens
- Context Window: 400000 tokens
Speed & Performance Analysis
With a processing speed of 500 tokens per second and 180ms time to first token:
- Processing Time: 17 minutes, 5.28 seconds
- Latency: 180 milliseconds to first token
- Base Throughput: 500 tokens/second
- Effective Throughput: 490 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for GPT-5.4 mini. 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 Claude Sonnet 4.6| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 4.6 | vs GPT-5.4 mini |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.023750 (rounded ~ $0.02) Best Value | ↓ 91.6% cheaper | ↓ 66.7% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.028938 (rounded ~ $0.03) | ↓ 89.8% cheaper | ↓ 59.4% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.028938 (rounded ~ $0.03) | ↓ 89.8% cheaper | ↓ 59.4% cheaper |
| #4 |
Gemini 3.8 Flash
Google
|
$0.070781 | ↓ 75% cheaper | ↓ 0.7% cheaper |
| #5 |
GPT-5.6 Luna
OpenAI
|
$0.095000 (rounded ~ $0.10) | ↓ 66.4% cheaper | ↑ 33.3% more |
| #6 |
Gemini 3.6 Flash
Google
|
$0.141563 (rounded ~ $0.14) | ↓ 50% cheaper | ↑ 98.7% more |
| #7 |
Gemini 3.5 Flash
Google
|
$0.142500 (rounded ~ $0.14) | ↓ 49.7% cheaper | ↑ 100% more |
| #8 |
Claude Sonnet 5
Anthropic
|
$0.188750 (rounded ~ $0.19) | ↓ 33.3% cheaper | ↑ 164.9% more |
| #9 |
Gemini 3.1 Flash
Google
|
$0.190000 | ↓ 32.9% cheaper | ↑ 166.7% more |
| #10 |
GPT-5.6 Terra
OpenAI
|
$0.237500 (rounded ~ $0.24) | ↓ 16.1% cheaper | ↑ 233.3% more |
| #11 |
Claude Opus 4.7
Anthropic
|
$0.471875 (rounded ~ $0.47) | ↑ 66.7% more | ↑ 562.3% more |
| #12 |
Claude Opus 5
Anthropic
|
$0.471875 (rounded ~ $0.47) | ↑ 66.7% more | ↑ 562.3% more |
| #13 |
Claude Opus 4.8
Anthropic
|
$0.471875 (rounded ~ $0.47) | ↑ 66.7% more | ↑ 562.3% more |
| #14 |
Claude Opus 4.6
Anthropic
|
$0.471875 (rounded ~ $0.47) | ↑ 66.7% more | ↑ 562.3% more |
| #15 |
Gemini 2.5 Pro
Google
|
$0.475000 (rounded ~ $0.48) | ↑ 67.8% more | ↑ 566.7% more |
| #16 |
GPT-5.6 Sol
OpenAI
|
$0.475000 (rounded ~ $0.48) | ↑ 67.8% more | ↑ 566.7% more |
| #17 |
Grok 4.3
xAI
|
$0.740000 | ↑ 161.4% more | ↑ 938.6% more |
| #18 |
Grok 4.20 Beta
xAI
|
$0.740000 | ↑ 161.4% more | ↑ 938.6% more |
| #19 |
Gemini 3.1 Pro
Google
|
$0.752500 (rounded ~ $0.75) | ↑ 165.8% more | ↑ 956.1% more |
| #20 |
Claude Fable 5.1
Anthropic
|
$0.915625 (rounded ~ $0.92) | ↑ 223.4% more | ↑ 1185.1% more |
| #21 |
Claude Mythos 5.1
Anthropic
|
$0.915625 (rounded ~ $0.92) | ↑ 223.4% more | ↑ 1185.1% more |
| #22 |
GPT-5.4
OpenAI
|
$0.940625 | ↑ 232.2% more | ↑ 1220.2% more |
| #23 |
GPT-5.4 Thinking
OpenAI
|
$0.940625 | ↑ 232.2% more | ↑ 1220.2% more |
| #24 |
Claude Fable 5
Anthropic
|
$0.943750 (rounded ~ $0.94) | ↑ 233.3% more | ↑ 1224.6% more |
| #25 |
Claude Mythos 5
Anthropic
|
$0.943750 (rounded ~ $0.94) | ↑ 233.3% more | ↑ 1224.6% more |
| #26 |
GPT-5.5
OpenAI
|
$1.881250 (rounded ~ $1.88) | ↑ 564.5% more | ↑ 2540.4% more |
| #27 |
GPT-6 Astra
OpenAI
|
$3.775000 (rounded ~ $3.78) | ↑ 1233.3% more | ↑ 5198.2% more |
| #28 |
GPT-6 Astra
OpenAI
|
$3.775000 (rounded ~ $3.78) | ↑ 1233.3% more | ↑ 5198.2% more |
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
Gemini 2.5 Pro Google
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
Choosing the Right Model for Legal Contract Review
Legal contract review requires a balance between precision and operational efficiency. When processing 500,000 tokens of legal documentation—roughly 20 to 30 dense, 50-page agreements—the choice of model fundamentally changes your workflow architecture. Legal teams must prioritize models that excel at structured extraction, clause classification, and risk flagging, as even minor hallucinations in legal extraction can lead to significant downstream liability.
Claude Sonnet 4.6 for Complex Analysis
Claude Sonnet 4.6 is frequently the preferred model for high-stakes, nuanced review. Its architectural strengths lie in instruction following and maintaining structural integrity across long-form documents. For tasks involving complex indemnification triggers, nested liability clauses, or multi-jurisdictional compliance checks, the model demonstrates a superior ability to adhere to strict extraction schemas. This makes it a reliable choice for the initial, deep-dive review phase where accuracy is non-negotiable.
GPT-5.4 mini for High-Volume Extraction
GPT-5.4 mini offers a distinct advantage for high-throughput pipelines. If your workload involves routine clause extraction—such as scanning thousands of standard NDAs or MSAs for expiration dates and renewal terms—this model provides the speed and efficiency required to scale. It is particularly well-suited for preliminary screenings, where the goal is to quickly filter documents for human review. While it may require more robust prompt engineering to match the reasoning depth of larger models, its performance in token-efficient, standardized tasks makes it a cost-effective workhorse for legal operations managers focusing on volume.