Claude Opus 4.7 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.012500 (rounded ~ $0.01)
Output: $0.012500 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.125000 (rounded ~ $0.13)
- Output Cost: $0.012500 (rounded ~ $0.01)
- Total Cost: $0.081250 (rounded ~ $0.08)
- Cost per 1K tokens: $0.000797
- Tokens per dollar: 1,255,385 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: 6 minutes, 40.33 seconds
- Latency: 400 milliseconds to first token
- Base Throughput: 260 tokens/second
- Effective Throughput: 255 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Claude Opus 4.7. 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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💰 Total Cost Calculation (from Plugin)
Output: $0.012000 (rounded ~ $0.01)
Output: $0.012000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.100000
- Output Cost: $0.012000 (rounded ~ $0.01)
- Total Cost: $0.067000 (rounded ~ $0.07)
- Cost per 1K tokens: $0.000657
- Tokens per dollar: 1,522,388 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 400 tokens per second and 220ms time to first token:
- Processing Time: 4 minutes, 20.28 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 392 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 Opus 4.7| Rank | AI Model & Provider | Total Cost | vs Claude Opus 4.7 | vs Gemini 3.1 Pro |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001525 Best Value | ↓ 98.1% cheaper | ↓ 97.7% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.004188 | ↓ 94.8% cheaper | ↓ 93.8% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 93.4% cheaper | ↓ 92% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 93.4% cheaper | ↓ 92% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.007625 (rounded ~ $0.01) | ↓ 90.6% cheaper | ↓ 88.6% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↓ 85% cheaper | ↓ 81.8% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.012563 (rounded ~ $0.01) | ↓ 84.5% cheaper | ↓ 81.3% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.015750 (rounded ~ $0.02) | ↓ 80.6% cheaper | ↓ 76.5% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.016250 (rounded ~ $0.02) | ↓ 80% cheaper | ↓ 75.7% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.016750 (rounded ~ $0.02) | ↓ 79.4% cheaper | ↓ 75% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.016750 (rounded ~ $0.02) | ↓ 79.4% cheaper | ↓ 75% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.017325 (rounded ~ $0.02) | ↓ 78.7% cheaper | ↓ 74.1% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.024375 (rounded ~ $0.02) | ↓ 70% cheaper | ↓ 63.6% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.025125 (rounded ~ $0.03) | ↓ 69.1% cheaper | ↓ 62.5% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 61.8% cheaper | ↓ 53.6% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 61.8% cheaper | ↓ 53.6% cheaper |
| #17 |
Claude Sonnet 5
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↓ 60% cheaper | ↓ 51.5% cheaper |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.041875 (rounded ~ $0.04) | ↓ 48.5% cheaper | ↓ 37.5% cheaper |
| #19 |
Gemini 2.5 Pro
Google
|
$0.044375 (rounded ~ $0.04) | ↓ 45.4% cheaper | ↓ 33.8% cheaper |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.048750 (rounded ~ $0.05) | ↓ 40% cheaper | ↓ 27.2% cheaper |
| #21 |
Grok 4.3
xAI
|
$0.059000 (rounded ~ $0.06) | ↓ 27.4% cheaper | ↓ 11.9% cheaper |
| #22 |
Grok 4.20 Beta
xAI
|
$0.059000 (rounded ~ $0.06) | ↓ 27.4% cheaper | ↓ 11.9% cheaper |
| #23 |
Gemini 3.1 Pro
Google
|
$0.067000 (rounded ~ $0.07) | ↓ 17.5% cheaper | Same price |
| #24 |
Claude Opus 5
Anthropic
|
$0.081250 (rounded ~ $0.08) | Same price | ↑ 21.3% more |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.081250 (rounded ~ $0.08) | Same price | ↑ 21.3% more |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.081250 (rounded ~ $0.08) | Same price | ↑ 21.3% more |
| #27 |
GPT-5.4
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 3.1% more | ↑ 25% more |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 3.1% more | ↑ 25% more |
| #29 |
GPT-5.5 Instant
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 3.1% more | ↑ 25% more |
| #30 |
GPT-5.6 Sol
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 3.1% more | ↑ 25% more |
| #31 |
Claude Fable 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 88.5% more | ↑ 128.5% more |
| #32 |
Claude Mythos 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 88.5% more | ↑ 128.5% more |
| #33 |
o3 Deep Research
OpenAI
|
$0.157500 (rounded ~ $0.16) | ↑ 93.8% more | ↑ 135.1% more |
| #34 |
Claude Fable 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 100% more | ↑ 142.5% more |
| #35 |
Claude Mythos 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 100% more | ↑ 142.5% more |
| #36 |
GPT-5.5
OpenAI
|
$0.167500 (rounded ~ $0.17) | ↑ 106.2% more | ↑ 150% more |
| #37 |
o3 Pro
OpenAI
|
$0.315000 (rounded ~ $0.32) | ↑ 287.7% more | ↑ 370.1% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.325000 (rounded ~ $0.33) | ↑ 300% more | ↑ 385.1% more |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 358.8% more | ↑ 456.3% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 358.8% more | ↑ 456.3% more |
Mistral Small 3 Mistral AI
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Choosing Between Frontier Reasoning and Multimodal Integration
For a startup handling legal contract review at scale, the decision between Claude Opus 4.7 and Gemini 3.1 Pro hinges on your team’s existing infrastructure and the complexity of your document pipeline. Claude Opus 4.7 consistently demonstrates superior nuance in clause-level interpretation, making it a strong candidate for high-stakes M&A due diligence where subtle shifts in liability language carry immense risk. Its reasoning architecture tends to handle open-ended legal inquiries with greater reliability, reducing the need for repetitive human oversight on complex, non-standard agreements.
Conversely, Gemini 3.1 Pro offers distinct advantages if your workflow is already entrenched in a cloud-native ecosystem. Its native ability to ingest diverse document layouts, including scanned PDFs with complex tables and handwritten marginalia, often outpaces competitors that rely on separate OCR steps. For teams managing high-volume contract intake, the latency improvements and deep integration with cloud data pipelines can create a smoother, more automated operational loop. The primary trade-off is often architectural; choosing Gemini might lead to tighter platform dependency, whereas Claude offers a more modular, albeit potentially more manual, integration path. For a 20-person team, the decision often comes down to whether you prioritize the deepest possible semantic accuracy for individual complex documents or the fastest end-to-end processing of diverse document formats at enterprise scale.