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: $0.047500 (rounded ~ $0.05)
- Cost per 1K tokens: $0.000466
- Tokens per dollar: 2,147,368 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, 59.95 seconds
- Latency: 400 milliseconds to first token
- Base Throughput: 260 tokens/second
- Effective Throughput: 243 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: $0.040000
- Cost per 1K tokens: $0.000392
- Tokens per dollar: 2,550,000 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: 4 minutes, 33.03 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 Opus 4.7| Rank | AI Model & Provider | Total Cost | vs Claude Opus 4.7 | vs Gemini 3.1 Pro |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.000850 Best Value | ↓ 98.2% cheaper | ↓ 97.9% cheaper |
| 🥈 |
Grok Code Fast 1
xAI
|
$0.002150 | ↓ 95.5% cheaper | ↓ 94.6% cheaper |
| 🥉 |
Gemini 3.1 Flash Lite
Google
|
$0.002500 | ↓ 94.7% cheaper | ↓ 93.8% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.003350 | ↓ 92.9% cheaper | ↓ 91.6% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.004250 | ↓ 91.1% cheaper | ↓ 89.4% cheaper |
| #6 |
GPT-5.4 mini
OpenAI
|
$0.007500 (rounded ~ $0.01) | ↓ 84.2% cheaper | ↓ 81.3% cheaper |
| #7 |
o4-mini Deep Research
OpenAI
|
$0.009000 (rounded ~ $0.01) | ↓ 81.1% cheaper | ↓ 77.5% cheaper |
| #8 |
Claude Haiku 4.5
Anthropic
|
$0.009500 | ↓ 80% cheaper | ↓ 76.3% cheaper |
| #9 |
o4-mini
OpenAI
|
$0.009900 | ↓ 79.2% cheaper | ↓ 75.3% cheaper |
| #10 |
Grok 4.3
xAI
|
$0.010000 | ↓ 78.9% cheaper | ↓ 75% cheaper |
| #11 |
Gemini 3.1 Flash
Google
|
$0.010000 | ↓ 78.9% cheaper | ↓ 75% cheaper |
| #12 |
Gemini 3.5 Flash
Google
|
$0.015000 (rounded ~ $0.02) | ↓ 68.4% cheaper | ↓ 62.5% cheaper |
| #13 |
Grok 4.20 Beta
xAI
|
$0.017000 (rounded ~ $0.02) | ↓ 64.2% cheaper | ↓ 57.5% cheaper |
| #14 |
GPT-5.3 Codex Spark
OpenAI
|
$0.019250 | ↓ 59.5% cheaper | ↓ 51.9% cheaper |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.019250 | ↓ 59.5% cheaper | ↓ 51.9% cheaper |
| #16 |
Gemini 2.5 Pro
Google
|
$0.027500 (rounded ~ $0.03) | ↓ 42.1% cheaper | ↓ 31.3% cheaper |
| #17 |
Claude Sonnet 4.6
Anthropic
|
$0.028500 (rounded ~ $0.03) | ↓ 40% cheaper | ↓ 28.8% cheaper |
| #18 |
Gemini 3.1 Pro
Google
|
$0.040000 | ↓ 15.8% cheaper | Same price |
| #19 |
Claude Opus 4.8
Anthropic
|
$0.047500 (rounded ~ $0.05) | Same price | ↑ 18.8% more |
| #20 |
Claude Opus 4.6
Anthropic
|
$0.047500 (rounded ~ $0.05) | Same price | ↑ 18.8% more |
| #21 |
GPT-5.4
OpenAI
|
$0.050000 | ↑ 5.3% more | ↑ 25% more |
| #22 |
GPT-5.4 Thinking
OpenAI
|
$0.050000 | ↑ 5.3% more | ↑ 25% more |
| #23 |
GPT-5.5 Instant
OpenAI
|
$0.050000 | ↑ 5.3% more | ↑ 25% more |
| #24 |
o3 Deep Research
OpenAI
|
$0.090000 | ↑ 89.5% more | ↑ 125% more |
| #25 |
GPT-5.5
OpenAI
|
$0.100000 | ↑ 110.5% more | ↑ 150% more |
| #26 |
o3 Pro
OpenAI
|
$0.180000 | ↑ 278.9% more | ↑ 350% more |
| #27 |
GPT-5.2 Pro
OpenAI
|
$0.231000 | ↑ 386.3% more | ↑ 477.5% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$0.231000 | ↑ 386.3% more | ↑ 477.5% more |
Mistral Small 3 Mistral AI
Grok Code Fast 1 xAI
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Grok 4.3 xAI
Gemini 3.1 Flash Google
Gemini 3.5 Flash Google
Grok 4.20 Beta xAI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Gemini 3.1 Pro Google
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
o3 Deep Research OpenAI
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Scaling Enterprise Retrieval-Augmented Generation
For organizations managing massive internal knowledge bases, the choice between Claude Opus 4.7 and Gemini 3.1 Pro often comes down to the nature of the retrieval workflow and the specific depth of reasoning required. Claude Opus 4.7 is designed for sustained, high-fidelity reasoning over complex documents. Its architecture excels in multi-step agentic workflows where maintaining strict instruction adherence across large contexts is paramount. It is particularly effective when the retrieval process requires the model to synthesize information across disparate, unstructured data sources to construct a coherent, nuanced response.
Conversely, Gemini 3.1 Pro leverages an expansive context window that facilitates massive-scale retrieval. For pipelines where the primary challenge is the volume of data rather than the complexity of the inference, Gemini’s ability to ingest and reason over immense document sets in a single pass offers significant architectural advantages. It is often the preferred choice for tasks requiring the analysis of vast, interconnected datasets, such as comprehensive compliance reporting or large-scale financial document reviews.
When planning for 100M-token monthly volumes, consider your bottleneck. If your process requires deep, high-precision logical deduction for each retrieved chunk, Claude Opus 4.7 provides the necessary architectural reliability. If your system is focused on high-throughput synthesis of large, varied information archives, Gemini 3.1 Pro’s native capacity for long-context multimodal retrieval is difficult to overlook. Both models offer robust tool-calling, but their strategic fit differs based on whether your primary constraint is reasoning density or raw context capacity.