GPT-6 Sol OpenAI 1050000 🏔️ Context Cliff
💰 Total Cost Calculation (from Plugin)
Output: $0.015000 (rounded ~ $0.02)
Output: $0.015000 (rounded ~ $0.02)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 1,000,000 input tokens and 2,000 output tokens:
- Input Cost: $2.000000
- Output Cost: $0.015000 (rounded ~ $0.02)
- Total Cost: $1.115000 (rounded ~ $1.12)
- Cost per 1K tokens: $0.001113
- Tokens per dollar: 898,655 tokens
- Context Window: 1050000 tokens
Speed & Performance Analysis
With a processing speed of 131 tokens per second and 340ms time to first token:
- Processing Time: 2 hours, 10 minutes, 2.01 seconds
- Latency: 340 milliseconds to first token
- Base Throughput: 131 tokens/second
- Effective Throughput: 128 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to GPT-6 Sol| Rank | AI Model & Provider | Total Cost | vs GPT-6 Sol |
|---|---|---|---|
| 🏆 |
Gemini 3.5 Flash-Lite
Google
|
$0.042500 (rounded ~ $0.04) Best Value | ↓ 96.2% cheaper |
| 🥈 |
GPT-6 Luna
OpenAI
|
$0.055750 (rounded ~ $0.06) | ↓ 95% cheaper |
| 🥉 |
Gemini 3.8 Flash
Google
|
$0.105000 (rounded ~ $0.11) | ↓ 90.6% cheaper |
| #4 |
Gemini 3.6 Flash
Google
|
$0.105000 (rounded ~ $0.11) | ↓ 90.6% cheaper |
| #5 |
Gemini 4 Argon
Google
|
$0.280000 | ↓ 74.9% cheaper |
| #6 |
Gemini 2.5 Pro
Google
|
$0.702500 (rounded ~ $0.70) | ↓ 37% cheaper |
| #7 |
GPT-6.1 Sol
OpenAI
|
$1.115000 (rounded ~ $1.12) | Same price |
| #8 |
GPT-5.4
OpenAI
|
$1.397500 (rounded ~ $1.40) | ↑ 25.3% more |
| #9 |
GPT-5.4 Thinking
OpenAI
|
$1.397500 (rounded ~ $1.40) | ↑ 25.3% more |
| #10 |
GPT-6 Astra
OpenAI
|
$5.600000 | ↑ 402.2% more |
| #11 |
GPT-6 Astra
OpenAI
|
$5.600000 | ↑ 402.2% more |
Gemini 3.5 Flash-Lite Google
GPT-6 Luna OpenAI
Gemini 3.8 Flash Google
Gemini 3.6 Flash Google
Gemini 4 Argon Google
Gemini 2.5 Pro Google
GPT-6.1 Sol OpenAI
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-6 Astra OpenAI
GPT-6 Astra OpenAI
For a game studio managing hundreds of licensing agreements, the ability to extract specific clauses like indemnity, intellectual property assignment, and termination rights from 50-page contracts is critical. GPT-6 Sol offers a balanced approach for legal teams needing high reasoning capabilities without the overhead of more expensive, reasoning-heavy alternatives. Its architecture is particularly well-suited for document-heavy workflows where parsing nuances in legalese is mandatory to avoid compliance blind spots.
Legal document review pipelines often struggle with context retention when documents vary wildly in structure. This model handles long-context inputs effectively, allowing for consistent extraction across large batches of contracts. For mid-market studios, the primary advantage is reliability; you can maintain high throughput while ensuring that critical data points are captured accurately. Unlike models designed primarily for creative writing, this model demonstrates a strong aptitude for structured data extraction, making it a dependable choice for automating the initial stages of contract due diligence. When integrated into a larger document management system, it minimizes the need for human intervention in the preliminary review phase, allowing legal counsel to focus on high-value negotiation rather than manual data entry.