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OpenAI · Balanced

GPT-3.5 Turbo

Added Jan 1, 2024

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Use in the app

Older model. Brought ChatGPT to the mainstream, seen as dated nowadays. 90% cheaper than GPT-4-Turbo, recommended for very simple tasks.

Input
Text
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.50
Output
$1.50

Reference prices as published by the model provider. API example

Specifications

Context window
16.4K
Max output
4.1K

Side by side

GPT-3.5 Turbo compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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GPT-3.5 TurboOpenAIThis modelGPT 6 LunaOpenAIRemove
ProviderOpenAIOpenAI
Discovery tierBalancedEfficient
AddedJan 1, 2024Sep 22, 2026
Limits
Context window16.39K1.05MBest
Max output4.1K128KBest
Average output—120 tokens
Pricing, USD per 1M tokens
Input$0.50$0.10Best
Output$1.50$0.50Best
Cache read—$0.01
Cache write—$0.13
Performance
Throughput—77.0 tok/s
Time to first token—6.8 s
Request success (24h)—99.7%
Benchmark indexes
Intelligence Index5.529.9Best
Coding Index10.7—
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputNoYes
Reasoning effort—none, low, medium, high, xhigh, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • GPT-3.5 Turbo
  • GPT 6 Luna

Intelligence Index

  • GPT-3.5 Turbo5.5
  • GPT 6 Luna29.9

GPT-3.5 Turbo: Better than 1% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GPT-3.5 Turbo: 10.7
    • GPT 6 Luna: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 40.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 10.2%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 1,097 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 1,263 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 13.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 78.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 18.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 28.3%

  • GPQA Diamond

    Graduate-level science questions

    • GPT-3.5 Turbo: 29.7%
    • GPT 6 Luna: —

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GPT-3.5 Turbo: 46.2%
    • GPT 6 Luna: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 2.5%

  • SciCode

    Scientific computing in Python

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 50.9%

Math

  • MATH-500

    Competition math problems

    • GPT-3.5 Turbo: 44.1%
    • GPT 6 Luna: —

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT-3.5 Turbo: —
    • GPT 6 Luna: 78.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-3.5-turbo",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="openai/gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

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