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AITier

GPT-5.6 Sol (max)

OpenAIGPTProprietary

Descripción

GPT-5.6 Sol is the frontier model in OpenAI's GPT-5.6 family, designed for complex professional work across coding, knowledge work, cybersecurity, and science. It sets state-of-the-art results while using fewer tokens at lower estimated cost, supports max reasoning effort and an ultra multi-agent mode, and has a 1.05M-token context window. The gpt-5.6 alias routes to GPT-5.6 Sol.

Fecha de lanzamiento
2026-07-09
Parámetros
—
Longitud del contexto
1.1M
Modalidades
image, pdf, text

Radar de capacidades

58
general
74
coding
94
reasoning
72
science
70
agents
85
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica2
80.0
LS
Ranking de codificación1
98.0
AA
Ranking general12
91.0
AA
Ranking multimodal10
66.0
LS
Ciencia5
94.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

Connectors100.0%Aut.
Capture-the-Flag Challenges (Internal)96.7%Aut.
Search and Function-Calling91.0%Aut.
SEC-bench Pro71.2%Aut.
Internal Research Debugging Evaluation68.3%Aut.
KernelGen 1P61.1%Aut.
LifeSciBench59.9%Aut.
Toolathlon58.0%Aut.
RSI Index57.9%Aut.
Big Finance Bench53.0%Aut.
Agents' Last Exam52.7%Aut.
PostTrainBench Lite50.3%Aut.
Management Consulting Tasks (Internal)43.2%Aut.
ExploitGym33.7%Aut.
GeneBench-Pro28.7%Aut.
AutomationBench18.1%Aut.
NanoGPT9.7%Aut.

Code

BenchCAD (with Python tool)83.4%Aut.
ExploitBench73.5%Aut.
DeepSWE 1.173.0%
DeepSWE72.7%Aut.
BenchCAD70.6%Aut.

General

Artificial Analysis59.0%
GDP.pdf30.7%Aut.

Healthcare

HealthBench Consensus95.5%Aut.
HealthBench Professional60.5%Aut.
HealthBench57.0%Aut.
HealthBench Hard33.1%Aut.

Long Context

MRCR v2 (8-needle)91.5%Aut.
MRCR v2 (8-needle, 512K-1M)73.8%Aut.

Math

FrontierMath89.0%Aut.
FrontierMath Tier 4 (v2)83.0%Aut.

Multimodal

OSWorld 2.062.6%Aut.

Reasoning

GPQANYU + Cohere + Anthropic (2023)94.6%Aut.
Graphwalks BFS >128k90.7%Aut.
BrowseCompOpenAI (2025)90.4%Aut.
Terminal-Bench 2.188.8%Aut.
Graphwalks BFS 1M77.1%Aut.
SWE-Bench ProPrinceton NLP (2024)64.6%Aut.
MedChemBench (Internal)48.3%Aut.
FrontierCode 1.147.5%
ARC-AGI-37.8%Aut.

Vision

MMMU-Pro (with tools)84.6%Aut.
MMMU-Pro83.0%Aut.

Índices de evaluación AA

(Artificial Analysis)
Coding Index(Artificial Analysis)
77.4
Intelligence Index(Artificial Analysis)
60.9
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Terminalbench V2 1
0.9
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.9
Lcr(Artificial Analysis)
0.8
Ifbench(Google Research (2023))
0.7
Terminalbench Hard(Stanford × Laude Institute (2026))
0.7
Scicode(UIUC + Argonne National Lab (2024))
0.6
Hle(Center for AI Safety + Scale AI (2025))
0.5
Tau Banking
0.4

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Math
90
Physics
90
Search
90
Biology
90
Chemistry
90
Long Context
80
Spatial Reasoning
80
Multimodal
70
Safety
70
Tool Calling
70
Vision
70
Reasoning
60
General
60
Healthcare
60
Agents
60
Code
60
Science
50
Finance
50
Systems
40

Precios

Precio de entrada$5 / 1M tokens
Precio de salida$30 / 1M tokens
Precio mixto (3:1)$11.25 / 1M tokens
Precio de lectura caché$0.5 / 1M tokens
Precio de escritura caché$6.25 / 1M tokens

Velocidad

Tokens/seg78.3
Retraso del primer token76.98s
Tiempo hasta la respuesta76.98s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

2 proveedores

Más barato: OpenAIMás caro: Neon
ProveedorEntradaSalida
1OpenAIMás barato
$0.00001
$0.00003
2Neon
$5
$30

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas

LLM StatsArtificial Analysis