OpenAI · Efficient
GPT 4.1 Nano
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.
| GPT 4.1 NanoOpenAIThis model | GPT 6 Luna ProOpenAIRemove | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Discovery tier | Efficient | Efficient |
| Added | Jan 1, 2024 | Sep 22, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05MBest |
| Max output | 32.77K | 128KBest |
| Average output | 49 tokens | 2.8K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.40Best | $0.50 |
| Cache read | $0.025 | $0.01Best |
| Cache write | — | $0.13 |
| Performance | ||
| Throughput | — | 245.6 tok/s |
| Time to first token | — | 22.2 s |
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | 7.8 | — |
| Coding Index | 11.1 | — |
| Math Index | 24.0 | — |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | Yes | Yes |
| Structured output | No | Yes |
| PDF input | Yes | Yes |
| 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 Luna Pro
Intelligence Index
- GPT 4.1 Nano7.8
- GPT 6 Luna Pro—
GPT 4.1 Nano: Better than 12% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GPT 4.1 Nano: 11.1
- GPT 6 Luna Pro: —
Math Index
Composite of the math evaluations
- GPT 4.1 Nano: 24.0
- GPT 6 Luna Pro: —
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- GPT 4.1 Nano: 20.3%
- GPT 6 Luna Pro: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GPT 4.1 Nano: 3.8%
- GPT 6 Luna Pro: —
GPQA Diamond
Graduate-level science questions
- GPT 4.1 Nano: 51.2%
- GPT 6 Luna Pro: —
MMLU-Pro
Multi-subject knowledge and reasoning
- GPT 4.1 Nano: 65.7%
- GPT 6 Luna Pro: —
IFBench
Following precise output instructions
- GPT 4.1 Nano: 32.0%
- GPT 6 Luna Pro: —
Coding
LiveCodeBench
Recent competitive programming problems
- GPT 4.1 Nano: 32.6%
- GPT 6 Luna Pro: —
Math
AIME 2025
Competition mathematics, 2025 problems
- GPT 4.1 Nano: 24.0%
- GPT 6 Luna Pro: —
AIME
Competition mathematics
- GPT 4.1 Nano: 23.7%
- GPT 6 Luna Pro: —
MATH-500
Competition math problems
- GPT 4.1 Nano: 84.8%
- GPT 6 Luna Pro: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GPT 4.1 Nano: 3.8%
- GPT 6 Luna Pro: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- GPT 4.1 Nano: 17.3%
- GPT 6 Luna Pro: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GPT 4.1 Nano: 20.3%
- GPT 6 Luna Pro: —
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.
- 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.
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
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