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OpenAI · Frontier

GPT 6 Sol Pro

Added Sep 22, 2026

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Use in the app

GPT-6 Sol Pro uses the same underlying model as GPT-6 Sol with Pro reasoning mode enabled for higher-quality responses on complex tasks.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • PDF input
Input
Text, Images
Output
Text
Reasoning effort
low · medium · high · xhigh · max
Discovery tier
Frontier

Pricing

USD per 1M tokens
Input
$2.00
Output
$10.00
Cache read
$0.20
Cache write
$2.50

Reference prices as published by the model provider. API example

Specifications

Context window
1.1M
Max output
128K
Average output (7 days)
135 tokens
Longer than 13% of 473 models

Side by side

GPT 6 Sol Pro compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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GPT 6 Sol ProOpenAIThis modelGemini 4 ArgonGoogleRemove
ProviderOpenAIGoogle
Discovery tierFrontierFrontier
AddedSep 22, 2026Oct 13, 2026
Limits
Context window1.05MBest1.05M
Max output128KBest65.54K
Average output135 tokens1.6K tokens
Pricing, USD per 1M tokens
Input$2.00$2.00
Output$10.00$10.00
Cache read$0.20$0.10Best
Cache write$2.50$0.19Best
Performance
Throughput—113.7 tok/s
Time to first token—10.0 s
Request success (24h)—98.5%
Benchmark indexes
Intelligence Index—52.6
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
PDF inputYesYes
Audio inputNoYes
Video inputNoYes
Reasoning effortlow, medium, high, xhigh, maxlow, medium, high

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • GPT 6 Sol Pro
  • Gemini 4 Argon

Intelligence Index

  • GPT 6 Sol Pro—
  • Gemini 4 Argon52.6
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 77.5%
  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 53.1%
  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 3.9%
  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 1,486 Elo
  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 1,624 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 21.8%
  • AA-LCRv1.1

    Reasoning across long documents

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 79.7%
  • MLCR-AA

    Long-context reasoning over medical records

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 13.9%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 57.1%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 57.1%
  • SciCode

    Scientific computing in Python

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 61.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT 6 Sol Pro: —
    • Gemini 4 Argon: 79.7%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-6-sol-pro",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="openai/gpt-6-sol-pro",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

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