Price Per TokenPrice Per Token
OpenAI

GPT 3.5 Turbo (older v0613) API Pricing 2026

Compare pricing, benchmarks, and providers for GPT 3.5 Turbo (older v0613). Find the best value for your use case.

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Last updated: February 7, 2026 at 08:06 AM

Overview

GPT 3.5 Turbo (older v0613) was released on January 25, 2024. Pricing starts at $1.00 per million input tokens and $2.00 per million output tokens. The model supports a context window of up to 4K tokens. API access is available through OpenAI.

Context Window
4K
tokens
Pricing
Input$1.00
Output$2.00
per 1M tokens
Speed
Output-
TTFT-
median latency
Capabilities
Text only

Pricing Comparison

Compare GPT 3.5 Turbo (older v0613) with 10 similar models by price.

Current Pricing (per 1M tokens)

11 models

Provider
Model
Input $/M
Output $/M
Coding
MMLU
GPQA
Context
Actions
$1.000
$2.000
4,095
$0.850
$3.400
131,072
$0.900
$1.900
262,144
$0.900
$3.300
131,072
$1.000
$1.750
4,096
$1.000
$3.000
256,000
$1.000
$5.000
51.1
80.0
64.6
200,000
$1.000
$3.000
54.6
72.9
53.6
131,072
$1.000
$1.000
29.5
68.9
47.1
127,072
$1.000
$5.000
128,000
$1.000
$1.000
131,072

* Some models use tiered pricing based on prompt length. Displayed prices are for prompts ≤ 200k tokens.

Compare Providers

GPT 3.5 Turbo (older v0613) is available from multiple providers with different pricing and availability.

2
Providers
$1.000
Cheapest Input/M
$2.000
Cheapest Output/M
Azure
Best Price

Provider Pricing

2 models

Provider
Input $/M
Output $/M
Uptime
A
Azure
Best Price
$1.000
$2.000
-
OpenAI
OpenAI
$1.500
$2.000
-
Provider pricing data sourced from OpenRouter and Helicone

Cost vs. Quality

Compare GPT 3.5 Turbo (older v0613)'s benchmark performance against all models.

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Frequently Asked Questions

GPT 3.5 Turbo (older v0613) costs $0.001000 per 1,000 input tokens and $0.002000 per 1,000 output tokens.
GPT 3.5 Turbo (older v0613) is available from 2 provider(s). Azure offers the best price.
We compare GPT 3.5 Turbo (older v0613) with 10 similarly-priced models. See the benchmark scatter plot above to compare quality vs cost.

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