openai
OpenAI: GPT-5.4 Mini (batch)
openai/gpt-5.4-mini:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to the OpenRouter catalog, openai/gpt-5.4-mini:batch is a batch-labeled variant of OpenAI's GPT-5.4 Mini, described as a faster, more efficient model aimed at high-throughput workloads. It accepts text, image, and file inputs and produces text, with a large context window and a late-August 2025 knowledge cutoff. Reasoning is optional, disabled by default, and tunable across five effort levels. Tool calling and structured outputs are supported. An independent model card was not available in this source pack.[1]
Strengths
- The catalog lists text, image, and file inputs with text output and a very large context window, suiting long or multimodal prompts.[1]
- Reasoning is optional and adjustable across five effort levels, and the entry supports tools, structured outputs, seeds, and verbosity controls.[1]
- The catalog description positions the model as fast and efficient for high-throughput workloads, and lists an Artificial Analysis coding index well above its agentic index.[1]
Limitations
- Only OpenRouter catalog data was supplied; no independent model card was in this source pack, so capabilities should be validated on real workloads.[1]
- The catalog's Artificial Analysis agentic index is much lower than its coding index, and no intelligence index value is provided.[1]
- Batch-specific behavior beyond the ':batch' label, plus licensing and safety details, are not described in the source.[1]
Where to use it
- High-volume text generation, summarization, or classification where throughput and efficiency matter; an editorial suggestion, not a measured result.[1]
- Document and image-to-text pipelines that use file and image inputs, such as extraction or captioning.[1]
- Tool-calling or structured-output integrations; for agentic multi-step workflows, test carefully given the low catalog agentic index.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-5.4 Mini (batch)Sources 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:batch
- 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 $0.375 / out $2.25
- 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 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.