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OpenAI · Efficient

GPT 4.1 Nano

Added Jan 1, 2024

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Use in the app

Cheapest model in the GPT-4.1 series. Huge context window with fast throughput and low latency.

  • Vision
  • PDF input
Input
Text, Images
Output
Text
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.10
Output
$0.40
Cache read
$0.025

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
32.8K
Average output (7 days)
49 tokens
Longer than 4% of 468 models

Side by side

GPT 4.1 Nano compared

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

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GPT 4.1 NanoOpenAIThis modelSolar Pro 3upstageRemove
ProviderOpenAIupstage
Discovery tierEfficientEfficient
AddedJan 1, 2024Mar 3, 2026
Limits
Context window1.05MBest131.07K
Max output32.77K—
Average output49 tokens—
Pricing, USD per 1M tokens
Input$0.10Best$0.15
Output$0.40Best$0.60
Cache read$0.025$0.015Best
Performance
Request success (24h)100.0%—
Benchmark indexes
Intelligence Index7.87.8
Coding Index11.116.2Best
Math Index24.0—
Capabilities
VisionYesNo
PDF inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • GPT 4.1 Nano
  • Solar Pro 3

Intelligence Index

  • GPT 4.1 Nano7.8
  • Solar Pro 37.8

GPT 4.1 Nano: Better than 12% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GPT 4.1 Nano: 11.1
    • Solar Pro 3: 16.2Top

  • Math Index

    Composite of the math evaluations

    • GPT 4.1 Nano: 24.0
    • Solar Pro 3: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT 4.1 Nano: —
    • Solar Pro 3: 0.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT 4.1 Nano: —
    • Solar Pro 3: 0.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT 4.1 Nano: —
    • Solar Pro 3: 99 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT 4.1 Nano: —
    • Solar Pro 3: 264 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT 4.1 Nano: —
    • Solar Pro 3: 1.6%

  • AA-LCRv1.1

    Reasoning across long documents

    • GPT 4.1 Nano: 20.3%
    • Solar Pro 3: 32.3%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • GPT 4.1 Nano: —
    • Solar Pro 3: 0.6%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT 4.1 Nano: 3.8%
    • Solar Pro 3: 10.3%Top

  • GPQA Diamond

    Graduate-level science questions

    • GPT 4.1 Nano: 51.2%
    • Solar Pro 3: 72.4%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GPT 4.1 Nano: 65.7%
    • Solar Pro 3: —

  • IFBench

    Following precise output instructions

    • GPT 4.1 Nano: 32.0%
    • Solar Pro 3: 71.2%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT 4.1 Nano: —
    • Solar Pro 3: 0.0%

  • SciCode

    Scientific computing in Python

    • GPT 4.1 Nano: —
    • Solar Pro 3: 25.5%

  • LiveCodeBench

    Recent competitive programming problems

    • GPT 4.1 Nano: 32.6%
    • Solar Pro 3: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GPT 4.1 Nano: 24.0%
    • Solar Pro 3: —

  • AIME

    Competition mathematics

    • GPT 4.1 Nano: 23.7%
    • Solar Pro 3: —

  • MATH-500

    Competition math problems

    • GPT 4.1 Nano: 84.8%
    • Solar Pro 3: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GPT 4.1 Nano: 3.8%
    • Solar Pro 3: 7.6%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GPT 4.1 Nano: 17.3%
    • Solar Pro 3: 86.3%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT 4.1 Nano: 20.3%
    • Solar Pro 3: 32.3%Top

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

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
0.0%
About $0.10 per 1M input tokens with caching
Request success (24h)
100.0%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 100.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

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-4.1-nano",
    "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-4.1-nano",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

Other OpenAI models, starting with the same family.