GPT-5.4 Mini model profile

Evidence snapshot:

GPT-5.4 Mini is a OpenAI model profile with a 400,000-token context window. The dated catalog snapshot records file, image, text modalities and interfaces for file input, prompt caching, reasoning controls, structured output, text generation.

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, and tool use, while reducing latency and cost for large-scale deployments. The model is designed for production environments that require a balance of capability and efficiency, making it well suited for chat applications, coding assistants, and agent workflows that operate at scale. GPT-5.4 mini delivers reliable instruction following, solid multi-step reasoning, and consistent performance across diverse tasks with improved cost efficiency.

GPT-5.4 Mini is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

GPT-5.4 Mini is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

GPT-5.4 Mini accepts file, image, and text and returns text. The snapshot records file input, prompt caching, reasoning controls, structured output, text generation, tool calling, vision, and web search pricing as capabilities or interfaces.

The dated reference snapshot lists $0.375 input and $2.25 output per million tokens. Cached input is $0.0375 per million tokens.

The 2026-09-06 snapshot includes 2 Artificial Analysis indexes and AutoExacto results for 4 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

GPT-5.4 Mini ranked #69 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type
Model research profile
Provider or publisher
OpenAI
Context window
400,000 tokens
Snapshot date
2026-09-06
Knowledge cutoff
2025-08-31
Reference catalog ID
openai/gpt-5.4-mini

When to pick GPT-5.4 Mini

GPT-5.4 Mini is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.

  • Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
  • Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
  • Reach for it when you want to trade depth against cost per call. Reasoning effort is selectable across xhigh, high, medium, low, none, so one route can serve both cheap and deep work.
  • Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.

Context, modalities, and identity

GPT-5.4 Mini accepts file, image, and text and returns text. The snapshot records file input, prompt caching, reasoning controls, structured output, text generation, tool calling, vision, and web search pricing as capabilities or interfaces.

Provider or publisher
OpenAI
Context window
400,000 tokens
Maximum output
128,000 tokens
Input modalities
file, image, and text
Output modalities
text
Knowledge cutoff
2025-08-31

Model overview

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, and tool use, while reducing latency and cost for large-scale deployments. The model is designed for production environments that require a balance of capability and efficiency, making it well suited for chat applications, coding assistants, and agent workflows that operate at scale. GPT-5.4 mini delivers reliable instruction following, solid multi-step reasoning, and consistent performance across diverse tasks with improved cost efficiency.

Reference model ID
openai/gpt-5.4-mini
Canonical version
openai/gpt-5.4-mini-20260317
Hugging Face ID
Not separately documented

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters
include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, seed, structured_outputs, tool_choice, tools
  • file input
  • prompt caching
  • reasoning controls
  • structured output
  • text generation
  • tool calling
  • vision
  • web search pricing

Dated pricing snapshot

The dated reference snapshot lists $0.375 input and $2.25 output per million tokens. Cached input is $0.0375 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date
2026-09-06
Input
$0.375 per 1M tokens
Cached input
$0.0375 per 1M tokens
Output
$2.25 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 5 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints
5
Best p50 latency
1.02 s
Best p50 throughput
197 tok/s
Availability with routing
99.99% over the sampled window
Availability without routing
98.87% over the sampled window
Performance date
2026-09-06
ProviderQuantizationInput / 1MOutput / 1MCache read / 1MContextp50 latencyp50 throughputUptime (1d)
OpenAI Flexunknown$0.375 / 1M$2.25 / 1M$0.0375 / 1M400,000 tokens2.31 s197 tok/s100.00%
Azureunknown$0.75 / 1M$4.5 / 1M$0.075 / 1M400,000 tokens1.02 s51 tok/s99.98%
OpenAIunknown$0.75 / 1M$4.5 / 1M$0.075 / 1M400,000 tokens1.03 s56 tok/s99.74%
Azure (US)unknown$0.825 / 1M$4.95 / 1M$0.0825 / 1M400,000 tokens1.40 s33 tok/s100.00%
OpenAI Fastunknown$1.5 / 1M$9 / 1M$0.15 / 1M400,000 tokens1.17 s43 tok/s100.00%

Benchmark evidence and limitations

The 2026-09-06 snapshot includes 2 Artificial Analysis indexes and AutoExacto results for 4 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Coding Index
56.1
Agentic Index
19.8
AutoExacto coverage
4 provider observations over 32 days

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

ProviderGPQA DiamondTAU-Bench AirlineRuns
auto-routing84.34%68%1
Azure83%66.67%1
Azure (US)82.5%64.63%2
OpenAI84.85%64.67%1

Popularity and market context

GPT-5.4 Mini ranked #69 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Third-party catalog rank
#69
Global market share
Not inferred
Observation date
2026-09-06

Frequently asked questions

When should I use GPT-5.4 Mini?

GPT-5.4 Mini is a reference profile: OpenAI publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Reach for it when you want to trade depth against cost per call: Reasoning effort is selectable across xhigh, high, medium, low, none, so one route can serve both cheap and deep work. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.

What is GPT-5.4 Mini?

GPT-5.4 Mini is a OpenAI model profile with a 400,000-token context window. The dated catalog snapshot records file, image, text modalities and interfaces for file input, prompt caching, reasoning controls, structured output, text generation.

What context window does GPT-5.4 Mini have?

The dated profile lists 400,000 tokens of context and up to 128,000 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for GPT-5.4 Mini?

The 2026-09-06 snapshot includes 2 Artificial Analysis indexes and AutoExacto results for 4 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Is GPT-5.4 Mini available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

Does the popularity rank represent GPT-5.4 Mini's global market share?

GPT-5.4 Mini ranked #69 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share. No global market-share percentage is inferred when the source does not publish one.

Sources and evidence dates

  1. GPT-5.4 Mini third-party catalog record (catalog, checked 2026-09-06)
  2. Third-party model catalog methodology (methodology, checked 2026-09-06)
  3. OpenAI official model documentation (primary, checked 2026-09-06)
  4. Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)
  5. GPT-5.4 Mini third-party catalog record (benchmark, checked 2026-09-06)