All Models/GPT-3.5 Turbo
Benchmark:47.5
Speed:Fast
Training Cutoff:2021-09

Specs & Pricing

API pricing per 1M tokens and core technical specifications
📥
Input / 1M
$0.5000
📤
Output / 1M
$1.5000
⚡
Cache Price / 1M
-
📏
Context Window
16K
16,385 tokens
📝
Max Output
4K
4,096 tokens
🎯
Benchmark & Speed
47.5
Speed:Fast

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$0.01
Output Cost$0.0045
Total$0.0145

Calculation Details

INPUT
10req × (2,000 / 1M) × $0.5 = $0.01
OUTPUT
10req × (300 / 1M) × $1.5 = $0.0045

Alternative Models

Models with comparable benchmark score and pricing tier
ModelProviderContext WindowMax OutputTraining CutoffInput / 1MCache Price / 1MOutput / 1MBenchmarkSpeedTotal
OpenAI
400K128K2024-05$0.25$0.025$2.0077.75Fast$0.0087
xAI
256K--$0.20$0.02$1.5077.75Fast$0.0067
Google👑
1M65K2025-01$0.25$0.025$1.5074.25Blazing Fast$0.0085
OpenAI
400K128K2024-09$0.25$0.025$2.0073.5Fast$0.0087
OpenAI
1M32K2024-06$0.40$0.10$1.6068.75Fast$0.0097

Provider

OpenAI

Benchmark

77.75

Speed

Fast

Training Cutoff

2024-05

Context Window

400K

Max Output

128K

Input / 1M

$0.25

Cache Price / 1M

$0.025

Output / 1M

$2.00

Total(試算)
In: $0.0024 / Out: $0.0060
$0.0087

Provider

xAI

Benchmark

77.75

Speed

Fast

Training Cutoff

-

Context Window

256K

Max Output

-

Input / 1M

$0.20

Cache Price / 1M

$0.02

Output / 1M

$1.50

Total(試算)
In: $0.0020 / Out: $0.0045
$0.0067

Provider

Google👑

Benchmark

74.25

Speed

Blazing Fast

Training Cutoff

2025-01

Context Window

1M

Max Output

65K

Input / 1M

$0.25

Cache Price / 1M

$0.025

Output / 1M

$1.50

Total(試算)
In: $0.0024 / Out: $0.0045
$0.0085

Provider

OpenAI

Benchmark

73.5

Speed

Fast

Training Cutoff

2024-09

Context Window

400K

Max Output

128K

Input / 1M

$0.25

Cache Price / 1M

$0.025

Output / 1M

$2.00

Total(試算)
In: $0.0024 / Out: $0.0060
$0.0087

Provider

OpenAI

Benchmark

68.75

Speed

Fast

Training Cutoff

2024-06

Context Window

1M

Max Output

32K

Input / 1M

$0.40

Cache Price / 1M

$0.10

Output / 1M

$1.60

Total(試算)
In: $0.0039 / Out: $0.0048
$0.0097
⚡ Main Feature

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Compare cutting-edge models from OpenAI, Anthropic, Google, and DeepSeek. Accurately simulate real-world API costs with prompt caching and custom context length.

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GPT-3.5 Turbo Frequently Asked Questions (FAQ)

Key insights into GPT-3.5 Turbo API pricing, context capacity, caching savings, and performance benchmarks

Q. What is the API pricing for GPT-3.5 Turbo? How much does it cost per 1M tokens?+

GPT-3.5 Turbo (OpenAI) is priced at $0.5000 per 1 million input tokens and $1.5000 per 1 million output tokens. The output rate is approximately 3.0x 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-3.5 Turbo?+

GPT-3.5 Turbo features a 16K context window and a maximum output limit of 4K tokens per request. It provides sufficient capacity for standard chat interactions and structured data processing.

Q. What are the best practices for optimizing API costs with GPT-3.5 Turbo?+

Because output tokens ($1.5000/1M) cost significantly more than inputs, always configure a strict max_tokens ceiling and employ structured output schemas. Additionally, pairing GPT-3.5 Turbo with lightweight models for routine tasks via multi-LLM routing can substantially lower total infrastructure spend.

Q. What is the benchmark score (47.5) and performance profile of GPT-3.5 Turbo?+

GPT-3.5 Turbo achieves an overall benchmark score of 47.5/100 with a "Fast" speed rating. It is optimized for high-throughput, low-latency applications requiring budget-conscious performance.

Q. Which alternative models are comparable to GPT-3.5 Turbo?+

Key alternatives in similar price-to-performance tiers include GPT-5 mini, grok-code-fast-1, Gemini 3.1 Flash-Lite Preview. We recommend comparing them based on your latency targets, context window needs, and prompt caching benefits using the full comparison tool on this site.