Claude Sonnet 5 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.005000 (rounded ~ $0.01)
Output: $0.005000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 200,000 input tokens and 2,000 output tokens:
- Input Cost: $0.100000
- Output Cost: $0.005000 (rounded ~ $0.01)
- Total Cost: $0.060000
- Cost per 1K tokens: $0.000297
- Tokens per dollar: 3,366,667 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: 7 minutes, 28.09 seconds
- Latency: 195 milliseconds to first token
- Base Throughput: 460 tokens/second
- Effective Throughput: 451 tokens/second (temperature-adjusted)
Best Use Cases
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💰 Total Cost Calculation (from Plugin)
Output: $0.018000 (rounded ~ $0.02)
Output: $0.018000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 200,000 input tokens and 2,000 output tokens:
- Input Cost: $0.400000
- Output Cost: $0.018000 (rounded ~ $0.02)
- Total Cost: $0.238000 (rounded ~ $0.24)
- Cost per 1K tokens: $0.001178
- Tokens per dollar: 848,739 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: 8 minutes, 35.28 seconds
- Latency: 220 milliseconds to first token
- Base Throughput: 400 tokens/second
- Effective Throughput: 392 tokens/second (temperature-adjusted)
Best Use Cases
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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.
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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 3.1 Pro |
|---|---|---|---|---|
| 🏆 |
Gemini 3.1 Flash Lite
Google
|
$0.007625 (rounded ~ $0.01) Best Value | ↓ 87.3% cheaper | ↓ 96.8% cheaper |
| 🥈 |
Gemini 3.5 Flash-Lite
Google
|
$0.009500 | ↓ 84.2% cheaper | ↓ 96% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.009500 | ↓ 84.2% cheaper | ↓ 96% cheaper |
| #4 |
Mistral Large 3
Mistral AI
|
$0.014500 (rounded ~ $0.01) | ↓ 75.8% cheaper | ↓ 93.9% cheaper |
| #5 |
Gemini 3.8 Flash
Google
|
$0.022500 (rounded ~ $0.02) | ↓ 62.5% cheaper | ↓ 90.5% cheaper |
| #6 |
GPT-5.4 mini
OpenAI
|
$0.022875 (rounded ~ $0.02) | ↓ 61.9% cheaper | ↓ 90.4% cheaper |
| #7 |
Claude Haiku 4.5
Anthropic
|
$0.030000 | ↓ 50% cheaper | ↓ 87.4% cheaper |
| #8 |
GPT-5.6 Luna
OpenAI
|
$0.030500 | ↓ 49.2% cheaper | ↓ 87.2% cheaper |
| #9 |
Gemini 3.6 Flash
Google
|
$0.045000 (rounded ~ $0.05) | ↓ 25% cheaper | ↓ 81.1% cheaper |
| #10 |
Gemini 3.5 Flash
Google
|
$0.045750 (rounded ~ $0.05) | ↓ 23.8% cheaper | ↓ 80.8% cheaper |
| #11 |
Gemini 3.1 Flash
Google
|
$0.061000 (rounded ~ $0.06) | ↑ 1.7% more | ↓ 74.4% cheaper |
| #12 |
GPT-5.6 Terra
OpenAI
|
$0.076250 (rounded ~ $0.08) | ↑ 27.1% more | ↓ 68% cheaper |
| #13 |
Claude Sonnet 4.6
Anthropic
|
$0.090000 | ↑ 50% more | ↓ 62.2% cheaper |
| #14 |
Claude Opus 4.7
Anthropic
|
$0.150000 | ↑ 150% more | ↓ 37% cheaper |
| #15 |
Claude Opus 5
Anthropic
|
$0.150000 | ↑ 150% more | ↓ 37% cheaper |
| #16 |
Claude Opus 4.8
Anthropic
|
$0.150000 | ↑ 150% more | ↓ 37% cheaper |
| #17 |
Claude Opus 4.6
Anthropic
|
$0.150000 | ↑ 150% more | ↓ 37% cheaper |
| #18 |
GPT-5.4
OpenAI
|
$0.152500 (rounded ~ $0.15) | ↑ 154.2% more | ↓ 35.9% cheaper |
| #19 |
GPT-5.4 Thinking
OpenAI
|
$0.152500 (rounded ~ $0.15) | ↑ 154.2% more | ↓ 35.9% cheaper |
| #20 |
Gemini 2.5 Pro
Google
|
$0.152500 (rounded ~ $0.15) | ↑ 154.2% more | ↓ 35.9% cheaper |
| #21 |
GPT-5.5 Instant
OpenAI
|
$0.152500 (rounded ~ $0.15) | ↑ 154.2% more | ↓ 35.9% cheaper |
| #22 |
GPT-5.6 Sol
OpenAI
|
$0.152500 (rounded ~ $0.15) | ↑ 154.2% more | ↓ 35.9% cheaper |
| #23 |
Grok 4.3
xAI
|
$0.228000 (rounded ~ $0.23) | ↑ 280% more | ↓ 4.2% cheaper |
| #24 |
Grok 4.20 Beta
xAI
|
$0.228000 (rounded ~ $0.23) | ↑ 280% more | ↓ 4.2% cheaper |
| #25 |
Gemini 3.1 Pro
Google
|
$0.238000 (rounded ~ $0.24) | ↑ 296.7% more | Same price |
| #26 |
Claude Fable 5.1
Anthropic
|
$0.281250 (rounded ~ $0.28) | ↑ 368.8% more | ↑ 18.2% more |
| #27 |
Claude Mythos 5.1
Anthropic
|
$0.281250 (rounded ~ $0.28) | ↑ 368.8% more | ↑ 18.2% more |
| #28 |
Claude Fable 5
Anthropic
|
$0.300000 | ↑ 400% more | ↑ 26.1% more |
| #29 |
Claude Mythos 5
Anthropic
|
$0.300000 | ↑ 400% more | ↑ 26.1% more |
| #30 |
GPT-5.5
OpenAI
|
$0.595000 (rounded ~ $0.60) | ↑ 891.7% more | ↑ 150% more |
| #31 |
GPT-6 Astra
OpenAI
|
$1.200000 | ↑ 1900% more | ↑ 404.2% more |
| #32 |
GPT-6 Astra
OpenAI
|
$1.200000 | ↑ 1900% more | ↑ 404.2% more |
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
Claude Haiku 4.5 Anthropic
GPT-5.6 Luna OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
Gemini 3.1 Flash Google
GPT-5.6 Terra OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Gemini 2.5 Pro Google
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
Legal contract review requires high precision and an understanding of nuanced clauses. When processing 200K-token documents for clause extraction, the choice between model providers often comes down to internal reasoning capabilities and instruction following. Developers building legal-tech MVPs must weigh how each model handles structured output versus long-range document context.
Claude Sonnet 5 is frequently favored in the legal technology space for its ability to adhere to complex formatting constraints. In contract review, where you often need to output structured JSON identifying specific dates, parties, and liabilities, its tendency to prioritize instruction adherence makes it a highly reliable choice for pipeline integration. It is particularly adept at maintaining consistency across long documents, which is essential for ensuring that clause definitions remain unified from the preamble to the signature page.
Gemini 3.1 Pro offers a different advantage, particularly with its massive context windows and multimodal capabilities. For firms that need to process scanned PDFs or hybrid documents where tables and text interact, its architectural approach to handling long-range dependencies is effective. It excels when you need to maintain a global understanding of a document while performing granular extraction tasks. For creators building legal tech MVPs, the decision usually hinges on the specific data structure required. If your workflow relies heavily on strict, schema-compliant JSON extraction, the refined reasoning of the Claude family offers consistency. Conversely, if your pipeline involves extracting data from diverse document formats, Gemini provides robust utility for high-stakes legal document review.