openai
OpenAI: GPT-5 Nano
openai/gpt-5-nano
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenAI's GPT-5 Nano (openai/gpt-5-nano) is listed in the OpenRouter catalog as the smallest and fastest variant in the GPT-5 family, positioned for developer tools, rapid interactions and ultra-low-latency environments. According to the catalog, it accepts text, image and file inputs and produces text, offers a roughly 400,000-token context window, and supports tool calling, structured outputs and an adjustable, always-on reasoning mode. The catalog reports middling Design Arena results and a May 2024 knowledge cutoff. Because only catalog data was available, these claims should be validated on real workloads.[1]
Strengths
- Accepts text, image and file inputs and returns text, according to the OpenRouter catalog.[1]
- The catalog lists a roughly 400,000-token context window plus tool calling, structured outputs, seed and response-format controls.[1]
- Reasoning effort is adjustable across four levels, from minimal to high, per the catalog.[1]
Limitations
- Evidence is catalog-only; no independent model card was available in this source pack, so capabilities and performance need validation on your own workloads.[1]
- The catalog's own description notes limited reasoning depth versus larger GPT-5 variants, and its reported Design Arena results are middling.[1]
- Reasoning is mandatory rather than optional, output is text-only, and OpenRouter lists a December 2026 expiration date for this listing.[1]
Where to use it
- Worth evaluating for latency-sensitive assistants and interactive developer tools, matching the catalog's stated positioning.[1]
- Plausible fit for agents or pipelines that need tool calls or structured output over long inputs.[1]
- Could suit multimodal preprocessing, such as extracting text from images and files, pending quality and cost testing.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-5 NanoSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Specifications
- Model ID
- openai/gpt-5-nano
- Canonical ID
- openai/gpt-5-nano-2025-08-07
- Creator
- openai
- Added to OpenRouter
- 07.08.2025
- Context length
- 400,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.050 / out $0.400
- Knowledge cutoff
- 31.05.2024
- Expiration date
- 11.12.2026
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · default medium · efforts: high, medium, low, minimal · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default medium · efforts: high, medium, low, minimal · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Design Arena | models · 3dwin rate 36.3% · rank 126 | 948Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 48% · rank 114 | 1,075Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 46.2% · rank 112 | 1,054Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 46.5% · rank 119 | 1,035Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 51.9% · rank 112 | 1,057Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 48.9% · rank 115 | 1,094Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| OpenAI | 400,000 | $0.025 | $0.200 | — | — | 100% |
| Azure | 400,000 | $0.050 | $0.400 | — | — | 100% |
| OpenAI | 400,000 | $0.050 | $0.400 | — | — | 100% |
| Azure | 400,000 | $0.055 | $0.440 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.