openai
OpenAI: GPT-5.4 Mini
openai/gpt-5.4-mini
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog describes openai/gpt-5.4-mini as an OpenAI model that brings core GPT-5.4 capabilities into a faster, more efficient package aimed at high-throughput workloads. It lists text, image, and file inputs with text output, a large context window, tools, structured outputs, and optional reasoning with several effort levels. The catalog reports Artificial Analysis coding and agentic index results, while design-arena data and an intelligence index are absent.[1]
Strengths
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack, so target-workload validation remains necessary.[1]
- Text is the only listed output modality, so this evidence does not support image or file generation.[1]
- Benchmark coverage is incomplete: design-arena results are absent and the intelligence index is unavailable.[1]
Where to use it
- Potentially suitable for high-throughput text responses that must accept image or file inputs; validate output quality on the target workload.[1]
- May fit code- or agent-oriented prototypes, though Artificial Analysis index results are catalog-reported and not workload-specific proof.[1]
- Could support applications needing tool calls, structured outputs, or adjustable reasoning effort, subject to integration testing.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-5.4 MiniSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-5.4 mini brings the core capabilities of GPT-5.4 to a faster, more efficient model optimized for high-throughput workloads. It supports text and image inputs with strong performance across reasoning, coding,...
Specifications
- Model ID
- openai/gpt-5.4-mini
- Canonical ID
- openai/gpt-5.4-mini-20260317
- Creator
- openai
- Added to OpenRouter
- 17.03.2026
- Context length
- 400,000
- Modality
- text+image+file->text
- Input modalities
- file, image, text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.750 / out $4.5
- Knowledge cutoff
- 31.08.2025
- Expiration date
- —
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: optional · default medium · efforts: xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | BB — next 30% of the cohort | — |
| Agents | BB — next 30% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default medium · efforts: xhigh, high, medium, low, none · 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 |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 56.1 | BB — next 30% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 17.9 | BB — next 30% of the cohort | 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 | $0.375 | $2.25 | — | — | 100% |
| Azure | 400,000 | $0.750 | $4.5 | — | — | 100% |
| OpenAI | 400,000 | $0.750 | $4.5 | — | — | 100% |
| Azure | 400,000 | $0.825 | $4.95 | — | — | — |
| OpenAI | 400,000 | $1.5 | $9 | — | — | 100% |
Provider data retrieved: 13.11.2026