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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 modelGPT 6.1 SolOpenAIRemove
ProviderOpenAIOpenAI
Discovery tierEfficientFrontier
AddedJan 1, 2024Sep 29, 2026
Limits
Context window1.05M1.05MBest
Max output32.77K128KBest
Average output49 tokens388 tokens
Pricing, USD per 1M tokens
Input$0.10Best$2.00
Output$0.40Best$10.00
Cache read$0.025Best$0.10
Cache write—$2.50
Performance
Throughput—124.2 tok/s
Time to first token—5.6 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index7.847.8Best
Coding Index11.1—
Math Index24.0—
Capabilities
ReasoningNoYes
ToolsNoYes
VisionYesYes
Structured outputNoYes
PDF inputYesYes
Reasoning effort—low, medium, high, xhigh, max

Public evaluations

Benchmarks

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

  • GPT 4.1 Nano
  • GPT 6.1 Sol

Intelligence Index

  • GPT 4.1 Nano7.8
  • GPT 6.1 Sol47.8

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
    • GPT 6.1 Sol: —
  • Math Index

    Composite of the math evaluations

    • GPT 4.1 Nano: 24.0
    • GPT 6.1 Sol: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 62.6%
  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 30.1%
  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 1,359 Elo
  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 1,450 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 30.0%
  • AA-LCRv1.1

    Reasoning across long documents

    • GPT 4.1 Nano: 20.3%
    • GPT 6.1 Sol: 83.3%Top
  • MLCR-AA

    Long-context reasoning over medical records

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 32.2%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT 4.1 Nano: 3.8%
    • GPT 6.1 Sol: 49.9%Top
  • GPQA Diamond

    Graduate-level science questions

    • GPT 4.1 Nano: 51.2%
    • GPT 6.1 Sol: —
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GPT 4.1 Nano: 65.7%
    • GPT 6.1 Sol: —
  • IFBench

    Following precise output instructions

    • GPT 4.1 Nano: 32.0%
    • GPT 6.1 Sol: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 48.0%
  • SciCode

    Scientific computing in Python

    • GPT 4.1 Nano: —
    • GPT 6.1 Sol: 53.2%
  • LiveCodeBench

    Recent competitive programming problems

    • GPT 4.1 Nano: 32.6%
    • GPT 6.1 Sol: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GPT 4.1 Nano: 24.0%
    • GPT 6.1 Sol: —
  • AIME

    Competition mathematics

    • GPT 4.1 Nano: 23.7%
    • GPT 6.1 Sol: —
  • MATH-500

    Competition math problems

    • GPT 4.1 Nano: 84.8%
    • GPT 6.1 Sol: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GPT 4.1 Nano: 3.8%
    • GPT 6.1 Sol: —
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GPT 4.1 Nano: 17.3%
    • GPT 6.1 Sol: —
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT 4.1 Nano: 20.3%
    • GPT 6.1 Sol: 83.3%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.