OpenAI · Efficient
GPT 5 Nano
Optimized for speed and ideal for applications requiring low latency. The fastest and most efficient GPT-5 variant.
- Reasoning
- Vision
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- minimal · low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.05
- Output
- $0.40
- Cache read
- $0.005
Reference prices as published by the model provider. API example
Specifications
- Context window
- 400K
- Max output
- 128K
- Average output (7 days)
- 322 tokens
- Longer than 35% of 468 models
Side by side
GPT 5 Nano compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GPT 5 NanoOpenAIThis model | Nvidia Nemotron 3.5 Lightning TEEnvidiaRemove | |
|---|---|---|
| Provider | OpenAI | nvidia |
| Discovery tier | Efficient | Open weights |
| Added | Aug 7, 2025 | Sep 11, 2026 |
| Limits | ||
| Context window | 400KBest | 262.14K |
| Max output | 128KBest | 65.54K |
| Average output | 322 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.05Best | $0.08 |
| Output | $0.40 | $0.20Best |
| Cache read | $0.005Best | $0.04 |
| Performance | ||
| Throughput | 96.6 tok/s | — |
| Time to first token | 1.8 s | — |
| Request success (24h) | 99.9% | — |
| Benchmark indexes | ||
| Intelligence Index | 13.0Best | 12.9 |
| Coding Index | — | 26.8 |
| Math Index | 83.7 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | No | Yes |
| Vision | Yes | No |
| Structured output | No | Yes |
| Reasoning effort | minimal, low, medium, high | none, low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GPT 5 Nano
- Nvidia Nemotron 3.5 Lightning TEE
Intelligence Index
- GPT 5 Nano13.0
- Nvidia Nemotron 3.5 Lightning TEE12.9
GPT 5 Nano tested at high reasoning effort
GPT 5 Nano: Better than 31% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 26.8
Math Index
Composite of the math evaluations
- GPT 5 Nano: 83.7
- Nvidia Nemotron 3.5 Lightning TEE: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 0.8%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 506 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 638 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 3.0%
AA-LCRv1.1
Reasoning across long documents
- GPT 5 Nano: 45.0%
- Nvidia Nemotron 3.5 Lightning TEE: 60.3%Top
MLCR-AA
Long-context reasoning over medical records
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 2.2%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GPT 5 Nano: 9.5%
- Nvidia Nemotron 3.5 Lightning TEE: 10.6%Top
GPQA Diamond
Graduate-level science questions
- GPT 5 Nano: 67.6%
- Nvidia Nemotron 3.5 Lightning TEE: 74.3%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- GPT 5 Nano: 78.0%
- Nvidia Nemotron 3.5 Lightning TEE: —
IFBench
Following precise output instructions
- GPT 5 Nano: 67.6%
- Nvidia Nemotron 3.5 Lightning TEE: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 0.5%
SciCode
Scientific computing in Python
- GPT 5 Nano: —
- Nvidia Nemotron 3.5 Lightning TEE: 32.1%
LiveCodeBench
Recent competitive programming problems
- GPT 5 Nano: 78.9%
- Nvidia Nemotron 3.5 Lightning TEE: —
Math
AIME 2025
Competition mathematics, 2025 problems
- GPT 5 Nano: 83.7%
- Nvidia Nemotron 3.5 Lightning TEE: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GPT 5 Nano: 12.1%
- Nvidia Nemotron 3.5 Lightning TEE: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- GPT 5 Nano: 36.5%
- Nvidia Nemotron 3.5 Lightning TEE: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GPT 5 Nano: 45.0%
- Nvidia Nemotron 3.5 Lightning TEE: 60.3%Top
Scores from Artificial Analysis, updated Oct 26, 2026. GPT 5 Nano was tested at high reasoning effort; compare scores measured at the same effort.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.
- Throughput
- 96.6 tok/s
- Faster than 62% of 254 models
- Time to first token
- 1.8 s
- Quicker than 86% of 254 models
- Prompt cache hits
- 30.4%
- About $0.0363 per 1M input tokens with caching
- Request success (24h)
- 99.9%
- 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-5-nano",
"reasoning_effort": "medium",
"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-5-nano",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)OpenAI
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