Claude Opus 4.7 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.093750 (rounded ~ $0.09)
Output: $0.093750 (rounded ~ $0.09)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 15,000 output tokens:
- Input Cost: $0.062500 (rounded ~ $0.06)
- Output Cost: $0.093750 (rounded ~ $0.09)
- Total Cost: $0.128125 (rounded ~ $0.13)
- Cost per 1K tokens: $0.001971
- Tokens per dollar: 507,317 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: 4 minutes, 15.18 seconds
- Latency: 400 milliseconds to first token
- Base Throughput: 260 tokens/second
- Effective Throughput: 255 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
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: $0.675000 (rounded ~ $0.68)
Output: $0.675000 (rounded ~ $0.68)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 15,000 output tokens:
- Input Cost: $0.375000 (rounded ~ $0.38)
- Output Cost: $0.675000 (rounded ~ $0.68)
- Total Cost: $1.050000
- Cost per 1K tokens: $0.016154 (rounded ~ $0.02)
- Tokens per dollar: 61,905 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 340 tokens per second and 260ms time to first token:
- Processing Time: 3 minutes, 15.18 seconds
- Latency: 260 milliseconds to first token
- Base Throughput: 340 tokens/second
- Effective Throughput: 333 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for GPT-5.5 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 GPT-5.5 Pro |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001813 Best Value | ↓ 98.6% cheaper | ↓ 99.8% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.007344 (rounded ~ $0.01) | ↓ 94.3% cheaper | ↓ 99.3% cheaper |
| 🥉 |
Mistral Large 3
Mistral AI
|
$0.009063 | ↓ 92.9% cheaper | ↓ 99.1% cheaper |
| #4 |
Gemini 3.5 Flash-Lite
Google
|
$0.011438 (rounded ~ $0.01) | ↓ 91.1% cheaper | ↓ 98.9% cheaper |
| #5 |
Gemini 2.5 Flash
Google
|
$0.011438 (rounded ~ $0.01) | ↓ 91.1% cheaper | ↓ 98.9% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.019219 | ↓ 85% cheaper | ↓ 98.2% cheaper |
| #7 |
o4-mini Deep Research
OpenAI
|
$0.021875 (rounded ~ $0.02) | ↓ 82.9% cheaper | ↓ 97.9% cheaper |
| #8 |
GPT-5.4 mini
OpenAI
|
$0.022031 (rounded ~ $0.02) | ↓ 82.8% cheaper | ↓ 97.9% cheaper |
| #9 |
o4-mini
OpenAI
|
$0.024063 (rounded ~ $0.02) | ↓ 81.2% cheaper | ↓ 97.7% cheaper |
| #10 |
Claude Haiku 4.5
Anthropic
|
$0.025625 (rounded ~ $0.03) | ↓ 80% cheaper | ↓ 97.6% cheaper |
| #11 |
Gemini 3.1 Flash
Google
|
$0.029375 | ↓ 77.1% cheaper | ↓ 97.2% cheaper |
| #12 |
GPT-5.6 Luna
OpenAI
|
$0.029375 | ↓ 77.1% cheaper | ↓ 97.2% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.038438 (rounded ~ $0.04) | ↓ 70% cheaper | ↓ 96.3% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.044063 (rounded ~ $0.04) | ↓ 65.6% cheaper | ↓ 95.8% cheaper |
| #15 |
Claude Sonnet 5
Anthropic
|
$0.051250 (rounded ~ $0.05) | ↓ 60% cheaper | ↓ 95.1% cheaper |
| #16 |
Grok 4.3
xAI
|
$0.057500 (rounded ~ $0.06) | ↓ 55.1% cheaper | ↓ 94.5% cheaper |
| #17 |
Grok 4.20 Beta
xAI
|
$0.057500 (rounded ~ $0.06) | ↓ 55.1% cheaper | ↓ 94.5% cheaper |
| #18 |
GPT-5.3 Codex Spark
OpenAI
|
$0.064531 (rounded ~ $0.06) | ↓ 49.6% cheaper | ↓ 93.9% cheaper |
| #19 |
GPT-5.3 Instant
OpenAI
|
$0.064531 (rounded ~ $0.06) | ↓ 49.6% cheaper | ↓ 93.9% cheaper |
| #20 |
GPT-5.6 Terra
OpenAI
|
$0.073438 (rounded ~ $0.07) | ↓ 42.7% cheaper | ↓ 93% cheaper |
| #21 |
Claude Sonnet 4.6
Anthropic
|
$0.076875 (rounded ~ $0.08) | ↓ 40% cheaper | ↓ 92.7% cheaper |
| #22 |
Gemini 2.5 Pro
Google
|
$0.092188 (rounded ~ $0.09) | ↓ 28% cheaper | ↓ 91.2% cheaper |
| #23 |
Gemini 3.1 Pro
Google
|
$0.117500 (rounded ~ $0.12) | ↓ 8.3% cheaper | ↓ 88.8% cheaper |
| #24 |
Claude Opus 5
Anthropic
|
$0.128125 (rounded ~ $0.13) | Same price | ↓ 87.8% cheaper |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.128125 (rounded ~ $0.13) | Same price | ↓ 87.8% cheaper |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.128125 (rounded ~ $0.13) | Same price | ↓ 87.8% cheaper |
| #27 |
GPT-5.4
OpenAI
|
$0.146875 (rounded ~ $0.15) | ↑ 14.6% more | ↓ 86% cheaper |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.146875 (rounded ~ $0.15) | ↑ 14.6% more | ↓ 86% cheaper |
| #29 |
GPT-5.5 Instant
OpenAI
|
$0.146875 (rounded ~ $0.15) | ↑ 14.6% more | ↓ 86% cheaper |
| #30 |
GPT-5.6 Sol
OpenAI
|
$0.146875 (rounded ~ $0.15) | ↑ 14.6% more | ↓ 86% cheaper |
| #31 |
o3 Deep Research
OpenAI
|
$0.218750 (rounded ~ $0.22) | ↑ 70.7% more | ↓ 79.2% cheaper |
| #32 |
Claude Fable 5.1
Anthropic
|
$0.251563 (rounded ~ $0.25) | ↑ 96.3% more | ↓ 76% cheaper |
| #33 |
Claude Mythos 5.1
Anthropic
|
$0.251563 (rounded ~ $0.25) | ↑ 96.3% more | ↓ 76% cheaper |
| #34 |
Claude Fable 5
Anthropic
|
$0.256250 (rounded ~ $0.26) | ↑ 100% more | ↓ 75.6% cheaper |
| #35 |
Claude Mythos 5
Anthropic
|
$0.256250 (rounded ~ $0.26) | ↑ 100% more | ↓ 75.6% cheaper |
| #36 |
GPT-5.5
OpenAI
|
$0.293750 (rounded ~ $0.29) | ↑ 129.3% more | ↓ 72% cheaper |
| #37 |
o3 Pro
OpenAI
|
$0.437500 (rounded ~ $0.44) | ↑ 241.5% more | ↓ 58.3% cheaper |
| #38 |
GPT-6 Astra
OpenAI
|
$0.512500 (rounded ~ $0.51) | ↑ 300% more | ↓ 51.2% cheaper |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.774375 (rounded ~ $0.77) | ↑ 504.4% more | ↓ 26.3% cheaper |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.774375 (rounded ~ $0.77) | ↑ 504.4% more | ↓ 26.3% cheaper |
Mistral Small 3 Mistral AI
Gemini 3.1 Flash Lite Google
Mistral Large 3 Mistral AI
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Gemini 3.8 Flash Google
o4-mini Deep Research OpenAI
GPT-5.4 mini OpenAI
o4-mini OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Claude Sonnet 5 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Gemini 2.5 Pro Google
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
o3 Deep Research OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
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
For healthcare administrators and clinical research teams, the choice between Claude Opus 4.7 and GPT-5.5 Pro hinges on the balance between nuanced reasoning and instruction adherence. Literature reviews require extreme precision; the model must synthesize complex biomedical findings without hallucinating citations or misinterpreting study endpoints. Claude Opus 4.7 has earned a reputation for superior performance in long-form academic drafting, often maintaining a more consistent tone for formal publication when provided with extensive source materials. It excels at following multi-step instructions, which is critical when enforcing strict PRISMA guidelines or specific formatting requirements for medical journals.
GPT-5.5 Pro, conversely, offers distinct advantages in data-heavy analysis. Its integration with search tools and reasoning capabilities makes it highly effective for rapid landscape scans, especially when the goal is to cross-reference findings across disparate clinical guidelines or regulatory updates. For research teams that require a mix of drafting and data extraction, GPT-5.5 Pro’s ability to function as an agent—performing iterative research and refining its own results—can significantly reduce the time spent on manual synthesis. When scaling research pipelines, the decision often comes down to the primary bottleneck: if the constraint is consistent, high-register drafting, Claude is frequently the preferred partner. If the bottleneck is broad evidence discovery and cross-source validation, GPT-5.5 Pro often provides a more robust research workflow. Both models provide the necessary audit trails to ensure clinical transparency, provided they are deployed within an environment that supports comprehensive logging and oversight.