# GPT-4.1 nano Usage, Cost & Rank | OpenCode Data

> GPT-4.1 nano costs $0.10 per 1M input tokens and $0.40 per 1M output tokens.

Tiny GPT-4.1 option for classification, routing, and very high-volume tasks

- Page: https://opencode.ai/data/openai/gpt-4-1-nano
- JSON: https://opencode.ai/data/openai/gpt-4-1-nano.json
- Model ID: openai/gpt-4.1-nano
- Lab: OpenAI
- Updated: 2026-09-28T12:09:39.000Z

## Model facts

| Fact | Value |
| --- | --- |
| Context window | 1M |
| Max output | 33K |
| Knowledge cutoff | 2024-04 |
| Release date | 2025-04-14 |
| Input modalities | text, image |
| Output modalities | text |
| Reasoning | No |
| Tool calling | Yes |
| Open weights | No |

## Pricing: USD per 1M tokens

| Input | Output | Cached input | Cache write |
| --- | --- | --- | --- |
| $0.10 | $0.40 | $0.03 | - |

## OpenCode usage: past 2 months

| Metric | Value |
| --- | --- |
| Rank by tokens last week | Unranked |
| Tokens | 0 |
| Share of all tokens | 0% |
| Change vs previous 2 months | 0% |
| Unique users | 0 |
| Completed sessions | 1 |
| Average tokens per session | 0 |
| Average cost per session | $0.0000 |
| Total spend | $0 |
| Input tokens served from cache | 0% |
| Weekly retention | - |

## Daily usage: past 2 months

_No data yet._

## Nearby models by tokens last week

| Rank | Model | Lab | Tokens |
| --- | --- | --- | --- |
| 1 | [space-bunny](https://opencode.ai/data/unknown/space-bunny.md) | - | 57T |
| 2 | [deepseek-v4.1-flash](https://opencode.ai/data/deepseek/deepseek-v4-1-flash.md) | DeepSeek | 33T |
| 3 | [muse-spark-1.3-contributor](https://opencode.ai/data/meta/muse-spark-1-3-contributor.md) | Meta | 31T |
| 4 | [mimo-v2.6-flash](https://opencode.ai/data/xiaomi/mimo-v2-6-flash.md) | Xiaomi | 8.8T |
| 5 | [deepseek-v4-flash](https://opencode.ai/data/deepseek/deepseek-v4-flash.md) | DeepSeek | 5.7T |
| 6 | [nemotron-3-ultra](https://opencode.ai/data/nvidia/nemotron-3-ultra.md) | NVIDIA | 3.6T |
| 7 | [longcat-2.5-preview](https://opencode.ai/data/meituan/longcat-2-5-preview.md) | Meituan | 2.6T |
| 8 | [glm-5.3-flash](https://opencode.ai/data/zhipuai/glm-5-3-flash.md) | Zhipu | 2.1T |
| 9 | [mimo-v2.5](https://opencode.ai/data/xiaomi/mimo-v2-5.md) | Xiaomi | 794B |
| 10 | [muse-spark-1.2-contributor](https://opencode.ai/data/meta/muse-spark-1-2-contributor.md) | Meta | 738B |

## Benchmarks

| Benchmark | Score | Metric | Source |
| --- | --- | --- | --- |
| Aider Polyglot | 8.9 | percent correct | https://aider.chat/docs/leaderboards/ |

## Methodology

- Updates: Aggregated every hour. Days and weeks use UTC.
- Tokens: Input, output, reasoning, and cached tokens for each request.
- Users and sessions: Approximate counts of distinct users and OpenCode sessions.
- Cost: Session cost is the average cost per OpenCode session. Token prices are list prices from the OpenCode model catalog.
- Retention: The share of a model's users in one week who use it again the next week.
- Citation: Cite OpenCode Data (opencode.ai/data) with the update time shown at the top of the page.