OpenAI
OpenAI
CodeProprietary Commercial API Verified Architecture & Specs$1.25/1M in · $10/1M out

GPT-5.1

GPT-5.1 is a code model from OpenAI with Proprietary parameters, supporting a 400,000-token context window, with text, image modalities. Hosted/proprietary model; upstream API availability and pricing should be checked against the linked provider documentation.

Technical Architecture & Execution Specifications
Architecture Overview

GPT-5.1

GPT-5.1 is a code model from OpenAI with Proprietary parameters, supporting a 400,000-token context window, with text, image modalities. Hosted/proprietary model; upstream API availability and pricing should be checked against the linked provider documentation.

Supported Modalities
textimage

Hardware & Execution ParametersCode

Total Parameter CountProprietary
Active Parameters (MoE)Dense Architecture
Context Window Capacity400,000 tokens
Model Weights FootprintCloud Hosted API
Distribution LicenseProprietary Commercial API
Standard API Pricing (1M Tokens)$1.25 in / $10 out
Model Heritage & Evolutionary Lineage
GPT v5.1

Genealogical Graph & Evolutionary Provenance

Tracing foundational base architecture ancestry, architectural successors, scale siblings, and reasoning distillation derivatives.

AI Model Architecture & Intelligence

Architecture Engineering & Capability Deep-Dive

An objective architectural evaluation of GPT-5.1 by OpenAI, analyzing underlying compute dynamics, memory constraints, and deployment economics.

Topology & Attention Mechanics

Features an Omni multimodal unified encoder capable of test-time compute scaling via explicit Chain-of-Thought (CoT) reasoning tokens.

Architecture Type:Advanced Transformer

Evaluation Profile & Reasoning

Exhibits frontier-tier behavior in reasoning and coding. World-class step-by-step mathematical extraction.

Domain Specialty:Code

LLM Hardware Sizing & Serving

Served via scalable API endpoints guaranteeing high tokens-per-second concurrency and enterprise SLAs.

KV Cache Mgmt: PagedAttention / FlashAttention-3
Hosting Type:Proprietary Commercial API

Inference Economics & Workflows

Reasoning tokens dynamically scale compute on hard problems. Expect higher output costs and varied TTFB, offset by massive reductions in hallucination rates.

Enterprise Fit:Production Ready
Production Trade-Offs & Capability Balance

Architectural Strengths vs. Considerations

An objective balance sheet analyzing the operational advantages and production constraints of deploying GPT-5.1.

Key Architectural Strengths

  • Omni multimodal unified encoder with test-time compute scaling (CoT reasoning tokens) maxes out complex problem solving.
  • Exceptional adherence to structured JSON schemas accelerates integration into deterministic enterprise pipelines.
  • Massive 400,000-token context allows full-repository and book-length ingestion.
  • Demonstrated SWE-bench Verified evaluation score of 76.3% in verified benchmarks.

Operational Considerations

  • Autoregressive CoT reasoning tokens can increase Time-to-First-Byte (TTFB) and inflate output token budgets unpredictably.
  • 128k+ token prefill stages become heavily compute-bound and balloon KV cache without PagedAttention chunking.
LLM Hardware Sizing & Runtime Compatibility

Inference Runtimes & Hardware Sizing

Deployment targets, inference engines, and memory requirements for GPT-5.1.

Recommended Hardware Profile:
Cloud Hosted API (Zero Local VRAM)
Supported Inference Engines
Vendor REST API

Primary managed cloud endpoint

Official
OpenRouter

Unified multi-provider gateway

Supported
Amazon Bedrock / GCP

Private cloud enterprise integration

Enterprise
OpenAI SDK

Standard chat completions client

Compatible
Precision & Quantization Formats
Cloud PrecisionManaged Serving

Vendor-optimized floating point precision (FP8/BF16)

Prompt CachingPrefix Cache

Up to 50–90% cost reduction on repeated system prompts

LLM Benchmark Database & Performance Metrics

9 Tested

Standardized evaluation results across reasoning, agentic coding, computer use, and alignment.

Flagship Headline MetricsIndustry SOTA Standard
Coding & Software

SWE-bench Verified

76.3%percent correct
0%100%
Reasoning & Science

GPQA Diamond

88.1%percent correct
0%100%
Reasoning & Science

FrontierMath

26.7%percent correct
0%100%
SWE-bench Verified
percent correct
76.3%
GPQA Diamond
percent correct
88.1%
AIME 2025
percent correct
94%
FrontierMath
percent correct
26.7%
MMMU
percent correct
85.4%
Tau²-bench Airline
percent correct
67%
Tau²-bench Telecom
percent correct
95.6%
Tau²-bench Retail
percent correct
77.9%
Commercial Rates & Inference Costs

API & Deployment Pricing

Standard API consumption rates per million tokens as indexed from official laboratory pricing documentation.

Usage TierRate / Unit
Prompt / Input Tokens$1.25 / 1M tokens
Completion / Output Tokens$10 / 1M tokens
Inference Cost & ROI Engine
Official API Rate
Prompt / Input Volume:50M Tokens / mo
1M500M1,000M
Generated / Output Volume:10M Tokens / mo
1M250M500M
Estimated Monthly Spend
$162.50/ mo
Input (50M @ $1.25/1M):$62.50
Output (10M @ $10.00/1M):$100.00
Cloud GPU Breakeven Ratio
RunPod RTX 4090 ($316/mo)0.51x spend
Lambda 1x H100 ($1,800/mo)0.09x spend
Similar Frontier Models & Alternatives
Explore All Comparisons

Comparable Foundation Architectures

Alternative models in the Code class with similar capabilities, context windows, or deployment profiles.

GoogleCode

Gemini 3.8 Flash

Context:1049k ctx
Parameters:Undisclosed
Input Rate:$0.75/1M
Alibaba CloudCode

Qwen3.8-Max-0902

Context:1000k ctx
Parameters:2.4T
Input Rate:$2/1M
MetaCode

Muse Glimmer 30B

Context:131k ctx
Parameters:30B
Input Rate:Free / Self-Host
Integration & Deployment
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("OPENAI_KEY", "EMPTY"),
    base_url="https://api.openai.com/v1"
)

response = client.chat.completions.create(
    model="openai-gpt-5.1",
    messages=[{"role": "user", "content": "Explain quantum superposition in 2 sentences."}]
)
print(response.choices[0].message.content)
Frequently Asked Questions

Frequently Asked Questions about GPT-5.1

Essential facts, architectural specs, hardware constraints, and pricing answers for GPT-5.1.

GPT-5.1 is a proprietary API model and cannot be run locally. It requires no local VRAM.

Primary Sources & Access Repositories

All technical specifications, parameter distributions, context architectures, and benchmark evaluations for GPT-5.1 are audited against primary source release documentation, research whitepapers, and verified vendor API endpoints.

api id:openai/gpt-5.1
knowledge cutoff:2024-09-30