GPT-5.5 OpenAI 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.030000
Output: $0.030000
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: $0.250000
- Output Cost: $0.030000
- Total Cost: $0.167500 (rounded ~ $0.17)
- Cost per 1K tokens: $0.001642
- Tokens per dollar: 608,955 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 420 tokens per second and 210ms time to first token:
- Processing Time: 4 minutes, 7.89 seconds
- Latency: 210 milliseconds to first token
- Base Throughput: 420 tokens/second
- Effective Throughput: 412 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to GPT-5.5| Rank | AI Model & Provider | Total Cost | vs GPT-5.5 |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001525 Best Value | ↓ 99.1% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.004188 | ↓ 97.5% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 96.8% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 96.8% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.007625 (rounded ~ $0.01) | ↓ 95.4% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↓ 92.7% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.012563 (rounded ~ $0.01) | ↓ 92.5% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.015750 (rounded ~ $0.02) | ↓ 90.6% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.016250 (rounded ~ $0.02) | ↓ 90.3% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.016750 (rounded ~ $0.02) | ↓ 90% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.016750 (rounded ~ $0.02) | ↓ 90% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.017325 (rounded ~ $0.02) | ↓ 89.7% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.024375 (rounded ~ $0.02) | ↓ 85.4% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.025125 (rounded ~ $0.03) | ↓ 85% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 81.5% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.031063 (rounded ~ $0.03) | ↓ 81.5% cheaper |
| #17 |
Claude Sonnet 5
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↓ 80.6% cheaper |
| #18 |
GPT-5.6 Terra
OpenAI
|
$0.041875 (rounded ~ $0.04) | ↓ 75% cheaper |
| #19 |
Gemini 2.5 Pro
Google
|
$0.044375 (rounded ~ $0.04) | ↓ 73.5% cheaper |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.048750 (rounded ~ $0.05) | ↓ 70.9% cheaper |
| #21 |
Grok 4.3
xAI
|
$0.059000 (rounded ~ $0.06) | ↓ 64.8% cheaper |
| #22 |
Grok 4.20 Beta
xAI
|
$0.059000 (rounded ~ $0.06) | ↓ 64.8% cheaper |
| #23 |
Gemini 3.1 Pro
Google
|
$0.067000 (rounded ~ $0.07) | ↓ 60% cheaper |
| #24 |
Claude Opus 4.7
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↓ 51.5% cheaper |
| #25 |
Claude Opus 5
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↓ 51.5% cheaper |
| #26 |
Claude Opus 4.8
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↓ 51.5% cheaper |
| #27 |
Claude Opus 4.6
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↓ 51.5% cheaper |
| #28 |
GPT-5.4
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↓ 50% cheaper |
| #29 |
GPT-5.4 Thinking
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↓ 50% cheaper |
| #30 |
GPT-5.5 Instant
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↓ 50% cheaper |
| #31 |
GPT-5.6 Sol
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↓ 50% cheaper |
| #32 |
Claude Fable 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↓ 8.6% cheaper |
| #33 |
Claude Mythos 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↓ 8.6% cheaper |
| #34 |
o3 Deep Research
OpenAI
|
$0.157500 (rounded ~ $0.16) | ↓ 6% cheaper |
| #35 |
Claude Fable 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↓ 3% cheaper |
| #36 |
Claude Mythos 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↓ 3% cheaper |
| #37 |
o3 Pro
OpenAI
|
$0.315000 (rounded ~ $0.32) | ↑ 88.1% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.325000 (rounded ~ $0.33) | ↑ 94% more |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 122.5% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 122.5% more |
Mistral Small 3 Mistral AI
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
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
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
GPT-5.6 Sol OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Enterprise-Scale Contract Analysis with GPT-5.5
For EdTech platforms and enterprise legal teams managing high-volume contract review, the core challenge is consistency. You need a model that can reliably parse fifty-page documents, extract nested clauses, and maintain context across complex legal language. GPT-5.5 excels here by providing a robust reasoning engine that minimizes hallucinations in structured extraction tasks.
When you are building a pipeline at 100M+ tokens monthly, the cost-to-performance ratio becomes the primary decision factor. GPT-5.5 is designed for high-throughput environments where accuracy in clause identification is non-negotiable. Its native ability to handle reasoning and function calling in a single pass simplifies your agentic workflows, potentially reducing the need for multi-step orchestration that adds latency and cost.
Legal teams often require specific handling for redlining and comparison. GPT-5.5 provides the instruction fidelity needed to follow strict playbooks without drifting into conversational fluff. Whether you are automating first-pass reviews or surfacing high-risk deviations, the model’s architectural focus on reasoning makes it a strong contender for production-grade legal automation. It is best used for complex, multi-clause analysis where reliable structured outputs feed directly into downstream compliance databases.