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GPT-5.4 mini

Input:$0.6/M
Output:$3.6/M
Cache Read:$0.06/M
Bแป‘i cแบฃnh:400,000
ฤแบงu ra tแป‘i ฤ‘a:128,000
Ngร y phรกt hร nh:Mar 17, 2026

GPT-5.4 mini brings the strengths of GPT-5.4 to a faster, more efficient model designed for high-volume workloads.

Mแป›i
Phแป• biแบฟn
Sแปญ dแปฅng thฦฐฦกng mแบกi

Playground cho GPT-5.4 mini

Khรกm phรก Playground cแปงa GPT-5.4 mini โ€” mรดi trฦฐแปng tฦฐฦกng tรกc ฤ‘แปƒ kiแปƒm tra mรด hรฌnh vร  chแบกy truy vแบฅn theo thแปi gian thแปฑc. Thแปญ prompts, ฤ‘iแปu chแป‰nh tham sแป‘ vร  lแบทp lแบกi ngay lแบญp tแปฉc ฤ‘แปƒ tฤƒng tแป‘c phรกt triแปƒn vร  xรกc thแปฑc cรกc trฦฐแปng hแปฃp sแปญ dแปฅng.

Technical Specifications of GPT-5.4 Mini

ItemGPT-5.4 Mini (estimated from official + cross-validation)
Model familyGPT-5.4 series (cost-efficient โ€œminiโ€ variant)
ProviderOpenAI
Input typesText, Image
Output typesText
Context window400,000 tokens
Max output tokens128,000 tokens
Knowledge cutoff~May 31, 2024 (inherits mini lineage)
Reasoning supportYes (lightweight vs full GPT-5.4)
Tool supportFunction calling, web search, file search, agents (inferred from GPT-5 family)
PositioningHigh-speed, cost-efficient near-frontier model

What is GPT-5.4 Mini?

GPT-5.4 Mini is a cost-efficient, high-speed variant of GPT-5.4 designed for latency-sensitive, high-volume workloads. It brings a significant portion of GPT-5.4โ€™s reasoning, coding, and multimodal capabilities into a smaller, faster model optimized for production-scale systems.

Compared to earlier โ€œminiโ€ models, GPT-5.4 Mini is positioned as a near-frontier small model, meaning it approaches flagship-level performance while dramatically reducing cost and response time.

Key Features of GPT-5.4 Mini

  • High-speed inference: Optimized for low-latency applications such as chatbots, copilots, and real-time systems
  • Large context window (400K): Supports long documents, multi-step workflows, and agent memory
  • Strong coding & agent support: Designed for tool use, multi-step reasoning, and delegated sub-agent tasks
  • Multimodal input: Accepts both text and image inputs for richer workflows
  • Cost-efficient scaling: Significantly cheaper than GPT-5.4 while retaining strong reasoning ability
  • Agent pipeline optimization: Ideal for multi-model architectures where large models plan and mini models execute

Benchmark Performance of GPT-5.4 Mini

  • Approaches GPT-5.4 performance on SWE-Bench-style coding tasks (~94โ€“95% of flagship performance) (cross-validated estimate from release discussions)
  • Significant improvements over GPT-5 Mini in:
    • reasoning accuracy
    • tool usage reliability
    • multimodal understanding
  • Designed to outperform previous โ€œminiโ€ generations in agent workflows and coding benchmarks
  • speed measurements: early API testers report ~180โ€“190 tokens/sec on GPT-5.4 Mini (vs ~55โ€“120 t/s for older GPT-5 mini variants depending on priority modes).

๐Ÿ‘‰ Key takeaway: GPT-5.4 Mini delivers near-frontier performance at a fraction of the cost and latency, making it ideal for scalable systems.

GPT-5.4 mini

Representative use cases

  1. Coding assistants & editors (IDE plugins, Copilot): fast context parsing, codebase exploration, and quick completions make GPT-5.4 Mini ideal for in-editor suggestions where time-to-first-token matters. GitHub Copilot is an early integration.
  2. Subagents / delegated workers: where a master agent delegates short, fast tasks (formatting, small reasoning steps, grep-style searches) to a cheap, fast worker. OpenAI positions mini/nano for these roles.
  3. High-volume API automation: bulk code generation, automated ticket triage, log summarization at scale where per-call cost and latency are primary constraints. Community throughput numbers indicate material operational advantages for mini.
  4. Tool-wrapping and toolchains: fast tool calls where the model orchestrates calls to external tools (search, grep, run tests) and returns compact, actionable outputs. GPT-5.4 family includes improved โ€œcomputer useโ€ capabilities.

How to access GPT-5.4 Mini API

Step 1: Sign Up for API Key

Log in toย cometapi.com. If you are not our user yet, please register first. Sign into yourย CometAPI console. Get the access credential API key of the interface. Click โ€œAdd Tokenโ€ at the API token in the personal center, get the token key: sk-xxxxx and submit.

cometapi-key

Step 2: Send Requests to GPT-5.4 Mini API

Select the โ€œgpt-5.4-miniโ€ endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account. base url isย Chat Completionsย andย Responses.

Insert your question or request into the content fieldโ€”this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

Cรขu Hแปi Thฦฐแปng Gแบทp

Giรก cแบฃ cho GPT-5.4 mini

Khรกm phรก mแปฉc giรก cแบกnh tranh cho GPT-5.4 mini, ฤ‘ฦฐแปฃc thiแบฟt kแบฟ ฤ‘แปƒ phรน hแปฃp vแป›i nhiแปu ngรขn sรกch vร  nhu cแบงu sแปญ dแปฅng khรกc nhau. Cรกc gรณi linh hoแบกt cแปงa chรบng tรดi ฤ‘แบฃm bแบฃo bแบกn chแป‰ trแบฃ tiแปn cho nhแปฏng gรฌ bแบกn sแปญ dแปฅng, giรบp dแป… dร ng mแปŸ rแป™ng quy mรด khi yรชu cแบงu cแปงa bแบกn tฤƒng lรชn. Khรกm phรก cรกch GPT-5.4 mini cรณ thแปƒ nรขng cao cรกc dแปฑ รกn cแปงa bแบกn trong khi vแบซn kiแปƒm soรกt ฤ‘ฦฐแปฃc chi phรญ.

ModelTierConditionComet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
gpt-5.4-ministandard-
Input:$0.6000/M
Output:$3.6000/M
Cache Read:$0.0600/M
Input:$0.7500/M
Output:$4.5000/M
Cache Read:$0.0750/M
-20%
gpt-5.4-mini-2026-03-17standard-
Input:$0.6000/M
Output:$3.6000/M
Cache Read:$0.0600/M
Input:$0.7500/M
Output:$4.5000/M
Cache Read:$0.0750/M
-20%

Mรฃ mแบซu vร  API cho GPT-5.4 mini

Truy cแบญp mรฃ mแบซu toร n diแป‡n vร  tร i nguyรชn API cho GPT-5.4 mini ฤ‘แปƒ tแป‘i ฦฐu hรณa quy trรฌnh tรญch hแปฃp cแปงa bแบกn. Tร i liแป‡u chi tiแบฟt cแปงa chรบng tรดi cung cแบฅp hฦฐแป›ng dแบซn tแปซng bฦฐแป›c, giรบp bแบกn khai thรกc toร n bแป™ tiแปm nฤƒng cแปงa GPT-5.4 mini trong cรกc dแปฑ รกn cแปงa mรฌnh.

#!/usr/bin/env bash
# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

response=$(curl --silent --location --request POST "https://api.cometapi.com/v1/responses" \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "Content-Type: application/json" \
  --header "Accept: application/json" \
  --data-raw '{
    "model": "gpt-5.4-mini",
    "input": "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    "reasoning": {
      "effort": "none"
    }
  }')

if command -v jq >/dev/null 2>&1; then
  printf '%s
' "$response" | jq -r '(
    [
      .output[]?
      | select(.type == "message")
      | .content[]?
      | select(.type == "output_text")
      | .text
    ][0]
  ) // .output_text // .'
else
  printf '%s
' "$response"
fi

cURL Code Example

#!/usr/bin/env bash
# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

response=$(curl --silent --location --request POST "https://api.cometapi.com/v1/responses" \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "Content-Type: application/json" \
  --header "Accept: application/json" \
  --data-raw '{
    "model": "gpt-5.4-mini",
    "input": "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    "reasoning": {
      "effort": "none"
    }
  }')

if command -v jq >/dev/null 2>&1; then
  printf '%s\n' "$response" | jq -r '(
    [
      .output[]?
      | select(.type == "message")
      | .content[]?
      | select(.type == "output_text")
      | .text
    ][0]
  ) // .output_text // .'
else
  printf '%s\n' "$response"
fi

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

response = client.responses.create(
    model="gpt-5.4-mini",
    input="How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
    reasoning={"effort": "none"},
)

print(response.output_text)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/v1";

const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: BASE_URL,
});

const response = await client.responses.create({
  model: "gpt-5.4-mini",
  input: "How much gold would it take to coat the Statue of Liberty in a 1mm layer?",
  reasoning: {
    effort: "none",
  },
});

console.log(response.output_text);

Uptime

Tแปท lแป‡ thร nh cรดng cแปงa yรชu cแบงu trong 30 ngร y qua, phแบฃn รกnh ฤ‘แป™ tin cแบญy cแปงa tแปซng nhร  cung cแบฅp mรด hรฌnh. CometAPI giรกm sรกt tแบฅt cแบฃ cรกc nhร  cung cแบฅp ฤ‘ฦฐแปฃc kแบฟt nแป‘i theo thแปi gian thแปฑc, 24/7.

RespondLIVE
1468msAvg. Response
UptimeLIVE
100.0%Avg. Uptime

Cรกc phiรชn bแบฃn cแปงa GPT-5.4 mini

Lรฝ do GPT-5.4 mini cรณ nhiแปu snapshot cรณ thแปƒ bao gแป“m cรกc yแบฟu tแป‘ tiแปm nฤƒng nhฦฐ: sแปฑ thay ฤ‘แป•i ฤ‘แบงu ra sau cรกc bแบฃn cแบญp nhแบญt cแบงn cรกc snapshot cลฉ ฤ‘แปƒ ฤ‘แบฃm bแบฃo tรญnh nhแบฅt quรกn, cung cแบฅp cho nhร  phรกt triแปƒn thแปi gian chuyแปƒn tiแบฟp ฤ‘แปƒ thรญch แปฉng vร  di chuyแปƒn, cลฉng nhฦฐ cรกc snapshot khรกc nhau tฦฐฦกng แปฉng vแป›i cรกc endpoint toร n cแบงu hoแบทc khu vแปฑc nhแบฑm tแป‘i ฦฐu hรณa trแบฃi nghiแป‡m ngฦฐแปi dรนng. ฤแปƒ biแบฟt chi tiแบฟt vแป sแปฑ khรกc biแป‡t giแปฏa cรกc phiรชn bแบฃn, vui lรฒng tham khแบฃo tร i liแป‡u chรญnh thแปฉc.

Version
gpt-5.4-mini
gpt-5.4-mini-2026-03-17