Claude Sonnet 5.5 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 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.050000
- Output Cost: $0.005000 (rounded ~ $0.01)
- Total Cost: $0.031250 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000306
- Tokens per dollar: 3,264,000 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 300 tokens per second and 300ms time to first token:
- Processing Time: 5 minutes, 50.38 seconds
- Latency: 300 milliseconds to first token
- Base Throughput: 300 tokens/second
- Effective Throughput: 291 tokens/second (temperature-adjusted)
Best Use Cases
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This calculator shows the math for Claude Sonnet 5.5. 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: $0.001200
Output: $0.001200
Unit: $0.000000
Fees: $0.000000
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.015000 (rounded ~ $0.02)
- Output Cost: $0.001200
- Total Cost: $0.008850 (rounded ~ $0.01)
- Cost per 1K tokens: $0.000087
- Tokens per dollar: 11,525,424 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 650 tokens per second and 95ms time to first token:
- Processing Time: 2 minutes, 41.81 seconds
- Latency: 95 milliseconds to first token
- Base Throughput: 650 tokens/second
- Effective Throughput: 631 tokens/second (temperature-adjusted)
Best Use Cases
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Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to Claude Sonnet 5.5| Rank | AI Model & Provider | Total Cost | vs Claude Sonnet 5.5 | vs DeepSeek V4 Flash |
|---|---|---|---|---|
| 🏆 |
Claude Haiku 5.5
Anthropic
|
$0.003250 Best Value | ↓ 89.6% cheaper | ↓ 63.3% cheaper |
| 🥈 |
GPT-6 Luna
OpenAI
|
$0.003250 | ↓ 89.6% cheaper | ↓ 63.3% cheaper |
| 🥉 |
GPT-5.6 Luna
OpenAI
|
$0.003350 | ↓ 89.3% cheaper | ↓ 62.1% cheaper |
| #4 |
Gemini 3.1 Flash Lite
Google
|
$0.004188 | ↓ 86.6% cheaper | ↓ 52.7% cheaper |
| #5 |
Gemini 3.5 Flash-Lite
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 82.8% cheaper | ↓ 39.3% cheaper |
| #6 |
Gemini 2.5 Flash
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 82.8% cheaper | ↓ 39.3% cheaper |
| #7 |
Mistral Large 3
Mistral AI
|
$0.007625 (rounded ~ $0.01) | ↓ 75.6% cheaper | ↓ 13.8% cheaper |
| #8 |
Gemini 3.8 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↓ 61% cheaper | ↑ 37.7% more |
| #9 |
Gemini 3.6 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↓ 61% cheaper | ↑ 37.7% more |
| #10 |
GPT-5.4 mini
OpenAI
|
$0.012563 (rounded ~ $0.01) | ↓ 59.8% cheaper | ↑ 41.9% more |
| #11 |
Claude Haiku 4.5
Anthropic
|
$0.016250 (rounded ~ $0.02) | ↓ 48% cheaper | ↑ 83.6% more |
| #12 |
Gemini 3.1 Flash
Google
|
$0.016750 (rounded ~ $0.02) | ↓ 46.4% cheaper | ↑ 89.3% more |
| #13 |
Mistral Large 4
Mistral AI
|
$0.020790 | ↓ 33.5% cheaper | ↑ 134.9% more |
| #14 |
GPT-5.3 Codex Spark
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 0.6% cheaper | ↑ 251% more |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 0.6% cheaper | ↑ 251% more |
| #16 |
Claude Sonnet 5
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↑ 4% more | ↑ 267.2% more |
| #17 |
Gemini 4 Argon
Google
|
$0.032500 (rounded ~ $0.03) | ↑ 4% more | ↑ 267.2% more |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.033500 (rounded ~ $0.03) | ↑ 7.2% more | ↑ 278.5% more |
| #19 |
Gemini 2.5 Pro
Google
|
$0.044375 (rounded ~ $0.04) | ↑ 42% more | ↑ 401.4% more |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.048750 (rounded ~ $0.05) | ↑ 56% more | ↑ 450.8% more |
| #21 |
Grok 4.3
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 88.8% more | ↑ 566.7% more |
| #22 |
Grok 4.20 Beta
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 88.8% more | ↑ 566.7% more |
| #23 |
Claude Opus 5.5
Anthropic
|
$0.062500 (rounded ~ $0.06) | ↑ 100% more | ↑ 606.2% more |
| #24 |
GPT-6.1 Sol
OpenAI
|
$0.065000 (rounded ~ $0.07) | ↑ 108% more | ↑ 634.5% more |
| #25 |
GPT-6 Sol
OpenAI
|
$0.065000 (rounded ~ $0.07) | ↑ 108% more | ↑ 634.5% more |
| #26 |
GPT-5.6 Sol
OpenAI
|
$0.065000 (rounded ~ $0.07) | ↑ 108% more | ↑ 634.5% more |
| #27 |
Gemini 3.1 Pro
Google
|
$0.067000 (rounded ~ $0.07) | ↑ 114.4% more | ↑ 657.1% more |
| #28 |
Claude Opus 4.7
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 160% more | ↑ 818.1% more |
| #29 |
Claude Opus 5
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 160% more | ↑ 818.1% more |
| #30 |
Claude Opus 4.8
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 160% more | ↑ 818.1% more |
| #31 |
Claude Opus 4.6
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 160% more | ↑ 818.1% more |
| #32 |
GPT-5.4
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 168% more | ↑ 846.3% more |
| #33 |
GPT-5.4 Thinking
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 168% more | ↑ 846.3% more |
| #34 |
GPT-5.5 Instant
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 168% more | ↑ 846.3% more |
| #35 |
Claude Fable 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 390% more | ↑ 1630.2% more |
| #36 |
Claude Mythos 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 390% more | ↑ 1630.2% more |
| #37 |
Claude Fable 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 420% more | ↑ 1736.2% more |
| #38 |
Claude Mythos 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 420% more | ↑ 1736.2% more |
| #39 |
GPT-5.5
OpenAI
|
$0.167500 (rounded ~ $0.17) | ↑ 436% more | ↑ 1792.7% more |
| #40 |
GPT-6 Astra
OpenAI
|
$0.325000 (rounded ~ $0.33) | ↑ 940% more | ↑ 3572.3% more |
| #41 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 1092.8% more | ↑ 4111.9% more |
| #42 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 1092.8% more | ↑ 4111.9% more |
Claude Haiku 5.5 Anthropic
GPT-6 Luna OpenAI
GPT-5.6 Luna OpenAI
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
Gemini 3.6 Flash Google
GPT-5.4 mini OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
Mistral Large 4 Mistral AI
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
Gemini 4 Argon Google
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
Claude Opus 5.5 Anthropic
GPT-6.1 Sol OpenAI
GPT-6 Sol OpenAI
GPT-5.6 Sol OpenAI
Gemini 3.1 Pro Google
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
GPT-5.5 Instant OpenAI
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-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Multi-agent orchestration requires a strong balance between the orchestrator’s reasoning depth and the worker agents’ throughput. Claude Sonnet 5.5 often serves as the “brain,” capable of decomposing complex, multi-page document archives into actionable sub-tasks. Its architectural ability to handle nuanced instructions and maintain state makes it ideal for the orchestrator role in legacy paper digitization, where layout complexity and handwriting ambiguity are constant challenges.
In contrast, DeepSeek V4 Flash acts as a high-efficiency worker, perfect for executing repetitive tasks—such as specific field extraction, table parsing, or simple OCR clean-up—at scale. By offloading bulk processing to the faster, more cost-efficient worker agent while keeping the orchestration logic with the more capable model, teams can optimize for both accuracy and latency. When planning a pipeline handling 100K-token tasks, the critical decision involves balancing the orchestrator’s token budget against the worker’s operational speed to ensure the system remains responsive. This orchestration pattern is particularly effective for teams scaling features that require deep document analysis without incurring the overhead of using a top-tier model for every single step of the process. The synergy between a reasoning-heavy lead and a throughput-optimized worker is the gold standard for robust document processing pipelines in production environments. Choosing between these models depends on whether your bottleneck is the reasoning complexity of the orchestration layer or the sheer volume of data being passed to the worker nodes.