GPT-4.1 Nano model profile

Evidence snapshot: 2026-09-06

GPT-4.1 Nano is a OpenAI model profile with a 1,047,576-token context window. The dated catalog snapshot records image, text, file modalities and interfaces for file input, prompt caching, structured output, text generation, tool calling.

For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million token context window, and scores 80.1% on MMLU, 50.3% on GPQA, and 9.8% on Aider polyglot coding – even higher than GPT‑4o mini. It’s ideal for tasks like classification or autocompletion.

GPT-4.1 Nano is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

GPT-4.1 Nano is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

GPT-4.1 Nano accepts image, text, and file and returns text. The snapshot records file input, prompt caching, structured output, text generation, tool calling, vision, and web search pricing as capabilities or interfaces.

The dated reference snapshot lists $0.1 input and $0.4 output per million tokens. Cached input is $0.025 per million tokens.

The 2026-09-06 snapshot includes 1 Artificial Analysis index, 6 Design Arena categories, and AutoExacto results for 4 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

GPT-4.1 Nano ranked #81 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type: Model research profile
Provider or publisher: OpenAI
Context window: 1,047,576 tokens
Snapshot date: 2026-09-06
Knowledge cutoff: 2024-06-30
Reference catalog ID: openai/gpt-4.1-nano

When to pick GPT-4.1 Nano

GPT-4.1 Nano is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.

Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.

Context, modalities, and identity

Provider or publisher: OpenAI
Context window: 1,047,576 tokens
Maximum output: 32,768 tokens
Input modalities: image, text, and file
Output modalities: text
Knowledge cutoff: 2024-06-30

Model overview

Reference model ID: openai/gpt-4.1-nano
Canonical version: openai/gpt-4.1-nano-2025-04-14
Hugging Face ID: Not separately documented

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters: max_completion_tokens, max_tokens, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_p

file input
prompt caching
structured output
text generation
tool calling
vision
web search pricing

Dated pricing snapshot

The dated reference snapshot lists $0.1 input and $0.4 output per million tokens. Cached input is $0.025 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date: 2026-09-06
Input: $0.1 per 1M tokens
Cached input: $0.025 per 1M tokens
Output: $0.4 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 3 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints: 3
Best p50 latency: 0.94 s
Best p50 throughput: 75 tok/s
Availability with routing: 100.00% over the sampled window
Availability without routing: 99.82% over the sampled window
Performance date: 2026-09-06

Provider	Quantization	Input / 1M	Output / 1M	Cache read / 1M	Context	p50 latency	p50 throughput	Uptime (1d)
Azure	unknown	$0.1 / 1M	$0.4 / 1M	$0.03 / 1M	1,047,576 tokens	0.96 s	22 tok/s	99.86%
OpenAI	unknown	$0.1 / 1M	$0.4 / 1M	$0.025 / 1M	1,047,576 tokens	0.94 s	75 tok/s	99.97%
Azure (EU)	unknown	$0.11 / 1M	$0.44 / 1M	$0.033 / 1M	1,047,576 tokens	No recent p50	No recent p50	No recent uptime

Benchmark evidence and limitations

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Coding Index: 11.1
AutoExacto coverage: 4 provider observations over 32 days

Design Arena category	Elo	Win rate	Rank
3d	962	46%	#106
codecategories	979	47.3%	#115
dataviz	909	41.1%	#115
gamedev	1000	49.6%	#109
uicomponent	938	43.9%	#110
website	986	48.1%	#115

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

Provider	GPQA Diamond	TAU-Bench Airline	Runs
auto-routing	50%	10%	1
Azure	50.84%	14%	1
Azure (EU)	51.18%	12%	1
OpenAI	50.51%	13.33%	1

Popularity and market context

Third-party catalog rank: #81
Global market share: Not inferred
Observation date: 2026-09-06

Frequently asked questions

When should I use GPT-4.1 Nano?

GPT-4.1 Nano is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.

What is GPT-4.1 Nano?

What context window does GPT-4.1 Nano have?

The dated profile lists 1,047,576 tokens of context and up to 32,768 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for GPT-4.1 Nano?

Is GPT-4.1 Nano available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

Does the popularity rank represent GPT-4.1 Nano's global market share?

Sources and evidence dates

GPT-4.1 Nano third-party catalog record (catalog, checked 2026-09-06)
Third-party model catalog methodology (methodology, checked 2026-09-06)
OpenAI official model documentation (primary, checked 2026-09-06)
Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)
Design Arena leaderboard and methodology (benchmark, checked 2026-09-06)
GPT-4.1 Nano third-party catalog record (benchmark, checked 2026-09-06)