GPT-5.6 Sol cost & VRAM calculator
What does GPT-5.6 Sol cost to run for your workload, and can you run it on your own hardware? Set your workload below - we compute per-provider API cost live and tell you honestly whether local hardware can run it.
This is where owning stops making sense
GPT-5.6 Sol is a large-billion-parameter model. No rig an individual can buy runs it - so unlike a workstation GPU model, there's no break-even to compute. The honest answer for nearly everyone is the per-provider API cost below.
Proprietary dense model from OpenAI. Parameter count is undisclosed. Native 1,050,000-token context, 128K max output, knowledge cutoff February 16, 2026. Text + image in, text out. Reasoning effort spans none through max; medium is default. Supports programmatic tool calling, explicit prompt caching (cache writes billed at 1.25x input), persisted reasoning, and a pro reasoning mode for harder tasks. Pricing: $5/1M input, $30/1M output. Agents on Rails benchmark (Aug 2026, Le Mans round). 84.1% accuracy on 63 runs - solidly frontier but behind the Opus 5 / Fable 5 / Kimi K3 cluster. Cost was about $0.52 mean per run. A good default for complex Rails work if you do not need the last few points of accuracy.
Your workload
API cost for your workload
| Provider | Rate ($/1M) | Monthly cost |
|---|---|---|
| DigitalOcean may be stale | $5.00 in · $30.00 out · $0.50 cache | $0.12 cheapest |
| OpenAI may be stale | $5.00 in · $30.00 out | $0.12 cheapest |
Monthly cost is an estimate from list prices and your workload - verify against the provider before committing. Cached fraction applies the cache rate to that share of input.
Can you run it locally?
GPT-5.6 Sol has no published quantization that fits a rig one person can buy, so there's no local-hardware recommendation and no break-even to compute. The honest answer is the per-provider API cost above.
Proprietary dense model from OpenAI. Parameter count is undisclosed. Native 1,050,000-token context, 128K max output, knowledge cutoff February 16, 2026. Text + image in, text out. Reasoning effort spans none through max; medium is default. Supports programmatic tool calling, explicit prompt caching (cache writes billed at 1.25x input), persisted reasoning, and a pro reasoning mode for harder tasks. Pricing: $5/1M input, $30/1M output. Agents on Rails benchmark (Aug 2026, Le Mans round). 84.1% accuracy on 63 runs - solidly frontier but behind the Opus 5 / Fable 5 / Kimi K3 cluster. Cost was about $0.52 mean per run. A good default for complex Rails work if you do not need the last few points of accuracy.
See the model card for the full architecture notes and any cloud subscription plans.