GPT-6 Sol

Release facts and lifecycle

Release announced

September 22, 2026

Model ID

gpt-6-sol

Input / output

Text and image inputs; text output

API formats

Responses and Chat Completions

Original provider sources checked 2026-10-10. These are source facts, not a benchmark of Flonno's deployment.

Where to start

Compare Sol and Luna with the same task rubric and complete output budget. Record retries and accepted answers before deciding whether a larger token budget improves the actual workflow.

• Reasoning workflows
• Image understanding
• Coding evaluation

What to check before deployment

Distinguish GPT-6 Sol from the later GPT-6.1 Sol release. Pricing depends on input length, caching and processing tier; keep those choices in the evaluation record.

Confirm the exact model ID, checkpoint revision and endpoint in your test record. A base model name does not establish a provider's quantization, accepted inputs, context limit or current availability.

Measure useful results

Build a small evaluation from the workflow you already run. Define the expected answer before testing. Track correct results, formatting errors, retries, complete request time and reported input and output usage.

Count rejected answers and manual corrections. A low token rate can still produce a high cost per accepted result when the workflow needs retries or repair.

Sources and scope

This page is an editorial evaluation guide, not a benchmark result or a claim that this model is served by Flonno.

License / access: Provider service terms. Read the linked license or service terms for the full conditions. Original release and lifecycle sources checked 2026-10-10.