Claude Sonnet 5 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.001250
Output: $0.001250
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 500 output tokens:
- Input Cost: $0.500000
- Output Cost: $0.001250
- Total Cost: $0.276250 (rounded ~ $0.28)
- Cost per 1K tokens: $0.000276
- Tokens per dollar: 3,621,719 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 460 tokens per second and 195ms time to first token:
- Processing Time: 38 minutes, 3.93 seconds
- Latency: 195 milliseconds to first token
- Base Throughput: 460 tokens/second
- Effective Throughput: 438 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Claude Sonnet 5. 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: $0.000938
Output: $0.000938
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 500 output tokens:
- Input Cost: $0.375000 (rounded ~ $0.38)
- Output Cost: $0.000938
- Total Cost: $0.207188 (rounded ~ $0.21)
- Cost per 1K tokens: $0.000207
- Tokens per dollar: 4,828,959 tokens
- Context Window: 1048576 tokens
Speed & Performance Analysis
With a processing speed of 304 tokens per second and 120ms time to first token:
- Processing Time: 57 minutes, 35.85 seconds
- Latency: 120 milliseconds to first token
- Base Throughput: 304 tokens/second
- Effective Throughput: 290 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Gemini 3.6 Flash. 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 5| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 5 | vs Gemini 3.6 Flash |
|---|---|---|---|---|
| 🏆 |
Gemini 3.5 Flash-Lite
Google
|
$0.041563 (rounded ~ $0.04) Best Value | ↓ 85% cheaper | ↓ 79.9% cheaper |
| 🥈 |
Gemini 3.8 Flash
Google
|
$0.103594 (rounded ~ $0.10) | ↓ 62.5% cheaper | ↓ 50% cheaper |
| 🥉 |
Gemini 3.6 Flash
Google
|
$0.207188 (rounded ~ $0.21) | ↓ 25% cheaper | Same price |
| #4 |
Gemini 2.5 Pro
Google
|
$0.691250 (rounded ~ $0.69) | ↑ 150.2% more | ↑ 233.6% more |
| #5 |
GPT-5.4
OpenAI
|
$1.380625 | ↑ 399.8% more | ↑ 566.4% more |
| #6 |
GPT-5.4 Thinking
OpenAI
|
$1.380625 | ↑ 399.8% more | ↑ 566.4% more |
| #7 |
GPT-6 Astra
OpenAI
|
$5.525000 (rounded ~ $5.53) | ↑ 1900% more | ↑ 2566.7% more |
| #8 |
GPT-6 Astra
OpenAI
|
$5.525000 (rounded ~ $5.53) | ↑ 1900% more | ↑ 2566.7% more |
Gemini 3.5 Flash-Lite Google
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
Gemini 2.5 Pro Google
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
Choosing the Right Engine for High-Volume RAG
When architecting a 100M-token RAG pipeline, the choice between Claude Sonnet 5 and Gemini 3.6 Flash often comes down to the specific demands of your retrieval workflow—whether you prioritize deep reasoning and code-like precision or throughput efficiency for vast multimodal datasets.
Claude Sonnet 5: Precision and Logic
Claude Sonnet 5 is the choice for teams where the quality of the answer is non-negotiable. Its architecture is particularly adept at handling dense, unstructured text and maintaining strict adherence to provided source material. For financial analysts or compliance officers extracting insights from lengthy reports, Sonnet 5 provides a level of instructional following that minimizes hallucination, effectively functioning as a high-fidelity reasoning engine. It excels when your Q&A system must interpret nuanced intent or synthesize conflicting information across multiple internal sources.
Gemini 3.6 Flash: Throughput and Multimodality
Conversely, Gemini 3.6 Flash is engineered for efficiency at scale. Its strength lies in its ability to handle extremely high request volumes with consistent latency, making it the superior option for real-time internal chatbots or pipelines that process diverse media types alongside text. If your knowledge base includes significant amounts of charts, diagrams, or video content, Gemini’s native multimodal capabilities streamline your pipeline, removing the need for separate OCR or transcription layers. For teams where cost-per-request and infrastructure throughput are the primary KPIs, Gemini 3.6 Flash provides a highly capable, optimized path for scaling to massive token volumes.