All Models/o4-mini-deep-research
OpenAI

o4-mini-deep-research

Benchmark:74.5
Speed:Very Slow
Training Cutoff:2024-06

Specs & Pricing

API pricing per 1M tokens and core technical specifications
📥
Input / 1M
$2.0000
📤
Output / 1M
$8.0000
⚡
Cache Price / 1M
$0.5000
📏
Context Window
200K
200,000 tokens
📝
Max Output
100K
100,000 tokens
🎯
Benchmark & Speed
74.5
Speed:Very 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$0.0195
Output Cost$0.0240
Cache Cost$0.0051
Total$0.0486
Saved: $0.0154

Calculation Details

INPUT
(1,024 / 1M) × $2 + 10req × (976 / 1M) × $2 = $0.0195
OUTPUT
10req × (300 / 1M) × $8 = $0.0240
CACHE
Read: 9req × (1,024 / 1M) × $0.5 = $0.0051

Alternative Models

Models with comparable benchmark score and pricing tier
ModelProviderContext WindowMax OutputTraining CutoffInput / 1MCache Price / 1MOutput / 1MBenchmarkSpeedTotal
OpenAI
400K128K2024-09$1.25$0.125$10.0084.5Standard$0.0435
OpenAI
400K128K2024-09$1.25$0.125$10.0084.25Standard$0.0435
OpenAI
1M32K2024-06$2.00$0.50$8.0079.75Fast$0.0486
xAI
2M--$2.00$0.20$6.0077.75Standard$0.0396
OpenAI
200K100K2024-06$2.00$0.50$8.0076.5Slow$0.0486

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

Provider

OpenAI

Benchmark

79.75

Speed

Fast

Training Cutoff

2024-06

Context Window

1M

Max Output

32K

Input / 1M

$2.00

Cache Price / 1M

$0.50

Output / 1M

$8.00

Total(試算)
In: $0.0195 / Out: $0.0240
$0.0486

Provider

xAI

Benchmark

77.75

Speed

Standard

Training Cutoff

-

Context Window

2M

Max Output

-

Input / 1M

$2.00

Cache Price / 1M

$0.20

Output / 1M

$6.00

Total(試算)
In: $0.0195 / Out: $0.018
$0.0396

Provider

OpenAI

Benchmark

76.5

Speed

Slow

Training Cutoff

2024-06

Context Window

200K

Max Output

100K

Input / 1M

$2.00

Cache Price / 1M

$0.50

Output / 1M

$8.00

Total(試算)
In: $0.0195 / Out: $0.0240
$0.0486
⚡ Main Feature

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o4-mini-deep-research Frequently Asked Questions (FAQ)

Key insights into o4-mini-deep-research API pricing, context capacity, caching savings, and performance benchmarks

Q. What is the API pricing for o4-mini-deep-research? How much does it cost per 1M tokens?+

o4-mini-deep-research (OpenAI) is priced at $2.0000 per 1 million input tokens and $8.0000 per 1 million output tokens. The output rate is approximately 4.0x 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 o4-mini-deep-research?+

o4-mini-deep-research features a 200K context window and a maximum output limit of 100K tokens per request. It provides ample capacity for multi-turn dialogs and complex document parsing.

Q. Does o4-mini-deep-research support Prompt Caching, and how much cost can be saved?+

Yes, o4-mini-deep-research supports prompt caching. Cached reads cost $0.5000 per 1M tokens, delivering an estimated 75% 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 (74.5) and performance profile of o4-mini-deep-research?+

o4-mini-deep-research achieves an overall benchmark score of 74.5/100 with a "Very Slow" speed rating. It is optimized for high-throughput, low-latency applications requiring budget-conscious performance.

Q. Which alternative models are comparable to o4-mini-deep-research?+

Key alternatives in similar price-to-performance tiers include GPT-5.1 Codex, GPT-5-Codex, GPT-4.1. We recommend comparing them based on your latency targets, context window needs, and prompt caching benefits using the full comparison tool on this site.