Model index · Text · text generation · standard · OpenAI · released 2025-04-14
GPT-4.1 Nano pricing
Served by 4 providers from $0.1750 to $0.1925 per 1M tokens on the standard tier — a 1.1× gap for identical weights.
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...
OpenAI · first published 2025-04-14 · Text model · text generation · 1.05M context · description as published by the source, not written by us
$0.1750
Cheapest standard /1M — OpenAI
1.05M
Native context window
5
Providers serving it
—
Quality not measured yet
Quality not measured yet
We measure models on request rather than pre-scoring the whole catalog, so this one has no score yet. Absence of a score is not a low score.
At 1M requests/month (1500 in / 500 out tokens), moving from Azure to OpenAI saves about $35/month.
Illustrative traffic shape, stated so you can check it against your own. Same weights both sides — but confirm quantisation and context below before switching.
Every provider and service tier
Standard on-demand rows first, cheapest of each group first. Tiers are not interchangeable — see the note below the table.
| Provider | In /1M | Out /1M | Blended /1M | Tier | Region | Source |
|---|---|---|---|---|---|---|
| OpenAI cheapest standard | $0.1000 | $0.4000 | $0.1750 | standard | — | third_party |
| Azure | $0.1000 | $0.4000 | $0.1750 | standard | — | third_party |
| OpenRouter (default route) * resells other hosts | $0.1000 | $0.4000 | $0.1750 | standard | — | provider_api |
| Azure | $0.1100 | $0.4400 | $0.1925 | standard | — | third_party |
| OpenRouter (default route) * resells other hosts | $0.0500 | $0.2000 | $0.0875 | batch | — | provider_api |
Not every row is the same product
This table mixes service tiers, and they are not interchangeable. Rows marked standard are ordinary on-demand requests. The others trade delivery for price:
- batch — submitted as a batch and collected later, typically within 24 hours — not for interactive use
Every comparison elsewhere on this site uses the standard tier, so a model is never shown at a queued rate beside another model's on-demand rate.
Cheaper if your workload can wait: batch at $0.0875 per 1M on OpenRouter — 50% below standard , submitted as a batch and collected later, typically within 24 hours — not for interactive use.
* OpenRouter chooses a host for each request, and the figure above is what its default choice costs — not a fixed rate for this model. Selecting a specific host through the same account costs whatever that host charges, which is why this row can sit above or below the hosts listed beside it. Token rates are passed through from the underlying provider with no markup, so the per-1M price above is what that host charges directly — OpenRouter's own charge sits on funding instead: 5.5% (min $0.80) by Stripe or 5% by Coinbase to buy credits, 5% of the equivalent spend if you bring your own provider key. So budget about 5% above the rate shown unless you already hold credit. Fee schedule.
Compare GPT-4.1 Nano with alternatives
One model per vendor, ordered by how prominent the vendor is and how many independent providers serve the model — hosts only carry what customers ask for, so that is a real demand signal. This is not traffic or popularity data, which we do not have. Every alternative below does the same job — text generation — because a price comparison between a generator and, say, an upscaler is arithmetic rather than advice. Prices on both sides are standard on-demand rates, so the comparison is like for like — a discounted batch or flex rate is never shown against another model’s standard rate.
| Alternative | Vendor | $/1M | vs GPT-4.1 Nano | Quality | Kind | Context | Hosts |
|---|---|---|---|---|---|---|---|
| Llama 4 Scout | Meta | $0.1500 DeepInfra | 14% cheaper | 40/100 | standard | 1.31M | 4 |
| Nova Lite 1.0 | Amazon | $0.1050 OpenRouter (default route) | 40% cheaper | 40/100 | standard | 300k | 2 |
| WizardLM-2 8x22B | Microsoft | $0.4800 DeepInfra | 174% dearer | 100/100 | standard | 66k | 3 |
| Qwen3 VL 32B Instruct | Alibaba | $0.1820 Alibaba | 4% dearer | not measured | standard open weights | 131k | 1 |
| Kimi K2 0905 | MoonshotAI | $1.00 OpenRouter (default route) | 473% dearer | not measured | standard | 262k | 3 |
| Command R (08-2024) | Cohere | $0.2625 Cohere | 50% dearer | not measured | standard | 128k | 1 |
| Gemma 3 27B | $0.1000 DeepInfra | 43% cheaper | not measured | standard open weights | 262k | 9 | |
| DeepSeek V3 0324 | DeepSeek | $0.4050 DeepInfra | 131% dearer | not measured | standard | 164k | 4 |
Prices are the cheapest host for each model, blended at a 3:1 input:output ratio. "Quality" is our own probe suite where we have run it — see what it measures. A cheaper alternative is only a real saving if it also passes on the capability your workload needs.
3 of these alternatives cost less than GPT-4.1 Nano — the cheapest being Gemma 3 27B at $0.1000 per 1M tokens blended (43% cheaper).
Cheaper is not automatically better: check the quality column, and confirm the context window and capabilities your workload depends on before switching.
Before you switch
Identical weights do not guarantee identical output. Check that the cheaper host serves the model at full precision rather than a quantised copy, that its context window matches what you need, and that its rate limits carry your peak traffic. A cheaper host that cannot take your throughput is not cheaper — it is an outage.
Move to OpenAI without a rewrite
VernaOne fronts every provider on this page with one API, so switching host is a config change — with automatic fallback if quality or latency regresses.
Try VernaOne free →Frequently asked
How much does GPT-4.1 Nano cost?
The cheapest standard-tier provider is OpenAI at $0.1750 per 1M tokens blended (3:1 input:output). A batch tier is available at $0.0875, 50% less, if the work can be collected later. Prices change often; verify with the provider before budgeting.
Which provider is best for GPT-4.1 Nano?
Cheapest is not automatically best. Compare quantisation (a lossy copy of the weights changes output), the context window each host actually serves, and rate limits. Where a provider serves less context than the model's native window we flag it in the table above.
Can I switch providers for GPT-4.1 Nano without changing code?
Yes, if you route through an abstraction. VernaOne exposes one API across every provider listed here, so switching host is a config change and you keep automatic fallback if the new one degrades.
← All models · Generated catalog of AI models and every provider that serves them, with normalised prices in USD per 1,000,000 tokens. Blended prices assume a 3:1 input:output ratio.