Claude Opus 4.7 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.006250 (rounded ~ $0.01)
Output: $0.006250 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 1,000 output tokens:
- Input Cost: $0.625000 (rounded ~ $0.63)
- Output Cost: $0.006250 (rounded ~ $0.01)
- Total Cost: $0.293750 (rounded ~ $0.29)
- Cost per 1K tokens: $0.000586
- Tokens per dollar: 1,705,532 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 260 tokens per second and 400ms time to first token:
- Processing Time: 32 minutes, 26.37 seconds
- Latency: 400 milliseconds to first token
- Base Throughput: 260 tokens/second
- Effective Throughput: 257 tokens/second (temperature-adjusted)
Best Use Cases
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💰 Total Cost Calculation (from Plugin)
Output: $0.135000 (rounded ~ $0.14)
Output: $0.135000 (rounded ~ $0.14)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 500,000 input tokens and 1,000 output tokens:
- Input Cost: $15.000000
- Output Cost: $0.135000 (rounded ~ $0.14)
- Total Cost: $7.035000 (rounded ~ $7.04)
- Cost per 1K tokens: $0.014042 (rounded ~ $0.01)
- Tokens per dollar: 71,215 tokens
- Context Window: 1024000 tokens
Speed & Performance Analysis
With a processing speed of 350 tokens per second and 250ms time to first token:
- Processing Time: 24 minutes, 5.92 seconds
- Latency: 250 milliseconds to first token
- Base Throughput: 350 tokens/second
- Effective Throughput: 347 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for GPT-5.4 Pro. 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 Opus 4.7| Rank | AI Model & Provider | Total Cost | vs Claude Opus 4.7 | vs GPT-5.4 Pro |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.014750 (rounded ~ $0.01) Best Value | ↓ 95% cheaper | ↓ 99.8% cheaper |
| 🥈 |
Gemini 2.5 Flash
Google
|
$0.017875 (rounded ~ $0.02) | ↓ 93.9% cheaper | ↓ 99.7% cheaper |
| 🥉 |
Grok 4.3
xAI
|
$0.072500 (rounded ~ $0.07) | ↓ 75.3% cheaper | ↓ 99% cheaper |
| #4 |
Gemini 3.5 Flash
Google
|
$0.088500 (rounded ~ $0.09) | ↓ 69.9% cheaper | ↓ 98.7% cheaper |
| #5 |
Grok 4.20 Beta
xAI
|
$0.116500 (rounded ~ $0.12) | ↓ 60.3% cheaper | ↓ 98.3% cheaper |
| #6 |
Gemini 3.1 Flash
Google
|
$0.118000 (rounded ~ $0.12) | ↓ 59.8% cheaper | ↓ 98.3% cheaper |
| #7 |
Claude Sonnet 4.6
Anthropic
|
$0.176250 (rounded ~ $0.18) | ↓ 40% cheaper | ↓ 97.5% cheaper |
| #8 |
Claude Opus 4.8
Anthropic
|
$0.293750 (rounded ~ $0.29) | Same price | ↓ 95.8% cheaper |
| #9 |
Claude Opus 4.6
Anthropic
|
$0.293750 (rounded ~ $0.29) | Same price | ↓ 95.8% cheaper |
| #10 |
Gemini 2.5 Pro
Google
|
$0.295000 (rounded ~ $0.30) | ↑ 0.4% more | ↓ 95.8% cheaper |
| #11 |
Gemini 3.1 Pro
Google
|
$0.469000 | ↑ 59.7% more | ↓ 93.3% cheaper |
| #12 |
GPT-5.4
OpenAI
|
$0.586250 (rounded ~ $0.59) | ↑ 99.6% more | ↓ 91.7% cheaper |
| #13 |
GPT-5.4 Thinking
OpenAI
|
$0.586250 (rounded ~ $0.59) | ↑ 99.6% more | ↓ 91.7% cheaper |
| #14 |
GPT-5.5
OpenAI
|
$1.172500 (rounded ~ $1.17) | ↑ 299.1% more | ↓ 83.3% cheaper |
| #15 |
GPT-5.5
OpenAI
|
$1.172500 (rounded ~ $1.17) | ↑ 299.1% more | ↓ 83.3% cheaper |
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Grok 4.3 xAI
Gemini 3.5 Flash Google
Grok 4.20 Beta xAI
Gemini 3.1 Flash Google
Claude Sonnet 4.6 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
Gemini 2.5 Pro Google
Gemini 3.1 Pro Google
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 OpenAI
GPT-5.5 OpenAI
When comparing Claude Opus 4.7 and GPT-5.4 Pro for 500,000-Token Legal Due Diligence Pipelines, legal technologists must weigh nuanced reasoning against raw architectural speed. Legal review is rarely about simple summarization; it is about comparative analysis—identifying discrepancies between a master services agreement and its associated amendments.
Claude Opus 4.7 is often favored in legal tech for its thinking capabilities, which excel at multi-step logical verification, particularly when the model needs to reason through complex indemnity clauses. It is particularly effective for courses that teach students to build agents that verify clauses against firm-specific playbooks.
Conversely, GPT-5.4 Pro brings a slightly more aggressive optimization for structured extraction. If your curriculum focuses on building high-throughput pipelines where the goal is to turn thousands of unstructured PDFs into structured JSON objects for a dashboard, the efficiency gains here are significant. The decision between these two often comes down to the required depth of analysis: choose Opus for high-stakes, interpretative tasks where the cost of a miss is high, and the Pro variant for high-velocity extraction tasks where consistent output formatting is the primary KPI. Both models offer the context window necessary to hold complete, 50-page agreements in memory, ensuring that legal entities and definitions remain consistent from the preamble to the signature block.