GPT-5.6 Cyber
$8,187.50 / month- Input cost
- $2,562.50
- Output cost
- $5,625.00
- Per 1,000 calls
- $163.75
- Pricing profile
- standard
Source-tracked model comparison
GPT-5.6 Cyber vs GPT-5.6 Sol: when does the specialized route apply?
Compare verified pricing and model limits for specialized cybersecurity access versus a general OpenAI route. The cost example uses a developer assistant backend workload and does not assume equal model quality.
Direct cost answer: GPT-5.6 Cyber is estimated at $8,187.50 per month and GPT-5.6 Sol at $2,320.00 for 5,000 input tokens, 1,500 output tokens, and 50,000 monthly requests. GPT-5.6 Sol is $5,867.50 lower under these assumptions. This does not identify a quality winner.
Tracked facts
Pricing and model limits
Prices are USD per 1M tokens under each model's verified default profile.
| Field | GPT-5.6 Cyber | GPT-5.6 Sol |
|---|---|---|
| API access provider | OpenAI | OpenAI |
| API model ID | gpt-5.6-cyber | gpt-5.6-sol |
| Input / 1M | $12.50 | $4.00 |
| Cached input / 1M | $1.25 | $0.40 |
| Output / 1M | $75.00 | $20.00 |
| Context window | 400,000 tokens | 1,050,000 tokens |
| Maximum output | 128,000 tokens | 128,000 tokens |
| Accepted input | text, image | text, image |
Example workload
Developer assistant backend cost scenario
5,000 input and 1,500 output tokens per request, 50,000 monthly requests, and 20% cached input.
GPT-5.6 Sol
$2,320.00 / month- Input cost
- $820.00
- Output cost
- $1,500.00
- Per 1,000 calls
- $46.40
- Pricing profile
- standard / short context
Cost result: GPT-5.6 Sol is $5,867.50 lower per month for these assumptions. This is a price comparison, not a model-quality ranking.
Questions to answer before choosing
- Does the use case qualify for GPT-5.6 Cyber access?
- Is a cybersecurity-specific route necessary for this workload?
- How do the verified token rates affect the expected monthly cost?
What this estimate leaves out
The calculation does not compare coding quality and excludes indexing, execution sandboxes, and repository storage.
Latency, reliability, output quality, retries, regional processing, and provider-specific tool charges can change the practical decision.