OpenAI identifies GPT-5.1 as a mid-cycle upgrade within the GPT-5 generation, utilizing a sparse Mixture-of-Experts (MoE) architecture. While documentation confirms it leverages the same foundational weights as the reasoning-capable variants, specific architectural modifications for the 'No Thinking' (reasoning_effort: none) mode are not fully detailed. The transition from dense to sparse is mentioned in technical descriptions, but the specific pretraining and fine-tuning methodologies that differentiate 5.1 from 5.0 remain largely proprietary and vague.

OpenAI provides no specific breakdown of the training data for GPT-5.1. Documentation states it was trained on the 'same data and stack as GPT-5,' which itself lacks public disclosure of sources, proportions, or filtering methodologies. Claims of 'high-quality' or 'diverse' data are unverifiable marketing assertions without a public dataset card or technical paper detailing the composition.

While the model uses a tokenizer consistent with the GPT-4o lineage (vocabulary size of approximately 200,000 tokens), there is no dedicated public documentation or open-source repository for the specific tokenizer used in the GPT-5.1 variant. Vocabulary size is inferred from previous models rather than explicitly stated in official 5.1 technical specs, and alignment with the claimed multilingual support is not independently verifiable through official tools.

OpenAI has not officially disclosed the total or active parameter counts for GPT-5.1. While third-party analysis of related open-weight models (GPT-OSS) suggests a 21B total/3.6B active structure for smaller variants, the flagship GPT-5.1 parameter density remains 'Unknown.' The lack of clarity regarding active parameters in the MoE architecture for the 'No Thinking' variant is a significant transparency gap.

No official data regarding GPU/TPU hours, hardware specifications, or training duration has been released. Environmental impact and carbon footprint calculations are left to third-party estimates (e.g., Epoch AI) rather than being disclosed by the provider. OpenAI explicitly avoids compute disclosure for competitive reasons.

OpenAI reports high scores on benchmarks like MMLU (92.3%) and SWE-bench Verified (76.3%), but does not provide the evaluation code, exact prompts, or reproduction instructions. Third-party audits have highlighted significant issues with benchmark reliability, and the lack of a public evaluation harness for the 'No Thinking' mode specifically makes these claims difficult to verify independently.

The model generally identifies itself correctly as part of the GPT-5.1 family and is transparent about its 'No Thinking' configuration via the API (reasoning_effort: none). However, it occasionally exhibits identity confusion or relies on predefined statements about its capabilities that do not always align with observed performance in edge cases, leading to minor consistency gaps.

The model is released under a restrictive proprietary license. While the Terms of Service (2026) clarify that users own the output, the model weights and code are not accessible. The license terms are primarily focused on usage policies and commercial restrictions rather than providing transparency into the model's legal provenance or derivative rights.

OpenAI provides no official VRAM or hardware guidance for local deployment, as the model is only accessible via API. While third-party documentation for 'GPT-OSS' exists, there is no official documentation regarding the memory scaling or quantization tradeoffs for the proprietary GPT-5.1 'No Thinking' variant.

OpenAI uses a versioning system (e.g., gpt-5.1-chat-latest) and maintains a basic changelog. However, the 'No Thinking' mode was introduced as a silent default change in some contexts, and users have reported behavioral drift and performance fluctuations without detailed technical explanations or a clear migration path for previous snapshots.