All Models/GPT-5.1-Codex-Max
Benchmark:86.0
Speed:Slow
Training Cutoff:2024-09

Specs & Pricing

API pricing per 1M tokens and core technical specifications
📥
Input / 1M
$1.2500
📤
Output / 1M
$10.0000
⚡
Cache Price / 1M
$0.1250
📏
Context Window
400K
400,000 tokens
📝
Max Output
128K
128,000 tokens
🎯
Benchmark & Speed
86.0
Speed:Slow

Cost Calculator

Simulate estimated API usage cost based on your specific traffic and context size

Calculation Settings

Pricing Tier
▶ Detailed Settings
▶ Presets

Simulation Results

Input Cost$0.0122
Output Cost$0.0300
Cache Cost$0.0013
Total$0.0435
Saved: $0.0115

Calculation Details

INPUT
(1,024 / 1M) × $1.25 + 10req × (976 / 1M) × $1.25 = $0.0122
OUTPUT
10req × (300 / 1M) × $10 = $0.0300
CACHE
Read: 9req × (1,024 / 1M) × $0.125 = $0.0013

Alternative Models

Models with comparable benchmark score and pricing tier
ModelProviderContext WindowMax OutputTraining CutoffInput / 1MCache Price / 1MOutput / 1MBenchmarkSpeedTotal
OpenAI
128K16K2024-09$1.25$0.125$10.0086Standard$0.0435
OpenAI
128K16K2024-09$1.25$0.125$10.0086Standard$0.0435
Google
1M65K2025-01$1.25$0.125$10.0085.75Standard$0.0550
OpenAI
400K128K2024-09$1.25$0.125$10.0084.5Standard$0.0435
OpenAI
400K128K2024-09$1.25$0.125$10.0084.25Standard$0.0435

Provider

OpenAI

Benchmark

86

Speed

Standard

Training Cutoff

2024-09

Context Window

128K

Max Output

16K

Input / 1M

$1.25

Cache Price / 1M

$0.125

Output / 1M

$10.00

Total(試算)
In: $0.0122 / Out: $0.0300
$0.0435

Provider

OpenAI

Benchmark

86

Speed

Standard

Training Cutoff

2024-09

Context Window

128K

Max Output

16K

Input / 1M

$1.25

Cache Price / 1M

$0.125

Output / 1M

$10.00

Total(試算)
In: $0.0122 / Out: $0.0300
$0.0435

Provider

Google

Benchmark

85.75

Speed

Standard

Training Cutoff

2025-01

Context Window

1M

Max Output

65K

Input / 1M

$1.25

Cache Price / 1M

$0.125

Output / 1M

$10.00

Total(試算)
In: $0.025 / Out: $0.0300
$0.0550

Provider

OpenAI

Benchmark

84.5

Speed

Standard

Training Cutoff

2024-09

Context Window

400K

Max Output

128K

Input / 1M

$1.25

Cache Price / 1M

$0.125

Output / 1M

$10.00

Total(試算)
In: $0.0122 / Out: $0.0300
$0.0435

Provider

OpenAI

Benchmark

84.25

Speed

Standard

Training Cutoff

2024-09

Context Window

400K

Max Output

128K

Input / 1M

$1.25

Cache Price / 1M

$0.125

Output / 1M

$10.00

Total(試算)
In: $0.0122 / Out: $0.0300
$0.0435
⚡ Main Feature

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GPT-5.1-Codex-Max Frequently Asked Questions (FAQ)

Key insights into GPT-5.1-Codex-Max API pricing, context capacity, caching savings, and performance benchmarks

Q. What is the API pricing for GPT-5.1-Codex-Max? How much does it cost per 1M tokens?+

GPT-5.1-Codex-Max (OpenAI) is priced at $1.2500 per 1 million input tokens and $10.0000 per 1 million output tokens. The output rate is approximately 8.0x higher than the input rate. You can simulate your exact monthly API expenses tailored to your request volume and token length using the calculator above.

Q. What are the context window and maximum output limits of GPT-5.1-Codex-Max?+

GPT-5.1-Codex-Max features a 400K context window and a maximum output limit of 128K tokens per request. It provides ample capacity for multi-turn dialogs and complex document parsing.

Q. Does GPT-5.1-Codex-Max support Prompt Caching, and how much cost can be saved?+

Yes, GPT-5.1-Codex-Max supports prompt caching. Cached reads cost $0.1250 per 1M tokens, delivering an estimated 90% discount compared to standard input rates. (Minimum cache threshold: 1K) Caching reusable system instructions and documentation substantially lowers recurring API expenses.

Q. What is the benchmark score (86) and performance profile of GPT-5.1-Codex-Max?+

GPT-5.1-Codex-Max achieves an overall benchmark score of 86/100 with a "Slow" speed rating. It strikes an optimal tradeoff between high analytical capability, speed, and affordability.

Q. Which alternative models are comparable to GPT-5.1-Codex-Max?+

Key alternatives in similar price-to-performance tiers include GPT-5 Chat, GPT-5.1 Chat, Gemini 2.5 Pro. We recommend comparing them based on your latency targets, context window needs, and prompt caching benefits using the full comparison tool on this site.