- Text Generation
Qwen3 ASR Flash is Qwen’s high-accuracy, multilingual automatic speech recognition (ASR) service optimized for real-time transcription of short audio. It is built on the Qwen3-Omni foundation…
Powered by OpenAI
GPT-5.4 Mini
- Text Generation
GPT-5.4 Mini is an OpenAI language model variant optimized for lightweight, general-purpose assistant tasks. It is designed to balance capability with efficiency for everyday conversational and productivity use.
Providers Comparison
Speed
Output tokens per second · Higher is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
End-to-End Response Time
Seconds · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
Price
USD per 1M tokens (blended) · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
About the model
What is GPT-5.4 Mini?
GPT-5.4 Mini is a compact OpenAI language model intended for general-purpose text understanding and generation. It is mainly used for interactive chat assistants, quick question answering, and drafting short-form content where low latency is important. It is also suitable for simple code help, data transformation, and lightweight reasoning tasks that do not require a larger model. It belongs to the GPT-5.x Mini family, which follows earlier GPT model generations with a focus on smaller, faster deployments.
Model capabilities
5 Core Capabilities
-
Conversational Chat
Engages in multi-turn dialogues, answering questions and following instructions while maintaining context and coherent, natural conversation flows.
-
Text Translation
Translates between multiple languages, preserving original meaning and tone for documents, messages, and short or long-form content.
-
Document OCR
Extracts readable text from images or scanned documents, enabling downstream processing, search, and analysis of previously static content.
-
Image Captioning
Generates concise descriptions of images, identifying key objects, scenes, relationships, and visual details for accessibility or indexing.
-
System Monitoring
Assists with interpreting logs, metrics, and alerts, helping summarize anomalies and suggesting likely causes or next investigative steps.
Use cases
6 Most Valuable Use Cases
- Customer Support Chatbots
- Invoice Data Extraction
- Legal Document Search
- Compliance Case Monitoring
- E-commerce Product Assistance
- Code Generation Assistance
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and highest performance for GPT-5.4 Mini–class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 80ms | 120 tps | 99.99% | $0.05 | $0.10 | 256K |
| OpenAI | Global | ~120ms | ~80 tps | 99.9% | ~$0.15 | ~$0.30 | ~128K |
| Azure OpenAI | US East | ~140ms | ~70 tps | 99.9% | ~$0.16 | ~$0.32 | ~128K |
| Anthropic | US West | ~150ms | ~60 tps | 99.9% | ~$0.18 | ~$0.36 | ~200K |
| Google Cloud | Global | ~130ms | ~75 tps | 99.9% | ~$0.17 | ~$0.34 | ~128K |
Performance benchmarks
Technical Specifications
| Metric | GPT-5.4 Mini (OpenAI) | Claude 3.7 Haiku (Anthropic) | Gemini 2.0 Flash (Google) |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~230ms |
| Context Window | 128K | 200K | 1M |
| Input Price ($/1M tokens) | $0.10 | $0.15 | $0.075 |
| Output Price ($/1M tokens) | $0.30 | $0.45 | $0.30 |
| Max Output Tokens | 4K | 4K | 8K |
| Throughput | 180 tps | 150 tps | 160 tps |
| Uptime | 99.9% | 99.5% | 99.5% |
30-day usage via LLM API
- 12.5B
- Prompt tokens processed (last 30 days)
- 3.1B
- Completion tokens generated (last 30 days)
- 4.8M
- API requests served (last 30 days)
- 97.9K
- Unique developer accounts (last 30 days)
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Intelligent Model Routing
Automatically route each request to the best model across providers based on latency, cost, and quality—no client changes or redeploys required.
One endpoint, every model -
Cost-Aware Orchestration
Control spend with dynamic model selection, rate limits, and per-project policies so you can ship complex AI features without surprise bills.
Max performance, minimal spend -
Resilient Fallback Logic
Define automatic failover chains so requests seamlessly retry on backup models or providers—no more outages from a single vendor hiccup.
Never go dark -
Full-Stack Observability
Get unified logs, traces, latency, and error metrics across every provider with request replay to debug production issues in minutes, not days.
See every token -
Task-Level Abstractions
Call high-level tasks—chat, tools, embeddings, rerank, vision—through one consistent API instead of juggling dozens of provider-specific endpoints.
Think tasks, not models -
High-Throughput Batch Jobs
Run massive prompt, embedding, or inference batches with automatic chunking, concurrency control, and retries to fully utilize provider quotas safely.
Scale to millions of calls
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a cost-efficient general-purpose model for everyday application features and agents.
- You need solid reasoning and coding without paying for the largest frontier model.
- Your use case involves building many concurrent chat-style assistants with moderate context lengths.
- Your use case involves rapid prototyping of product features where iteration speed matters most.
- You need to integrate with OpenAI tools, APIs, and ecosystem using a lightweight model.
- Your use case involves batch-processing user questions, summaries, or classifications at scale.
- You need reasonably strong multilingual understanding while keeping per-request costs relatively low.
Avoid if...
- You need the very best possible reasoning, planning, and tool-use from OpenAI’s flagship models.
- You need extremely long-context processing for massive documents, codebases, or multi-hour transcripts.
- You need guaranteed top-tier performance on complex, safety-critical medical, legal, or financial tasks.
- Your workload requires cutting-edge multimodal generation quality, such as highest-fidelity images or video.
- You need highly specialized domain models with rigorous benchmarks and certifications for regulated industries.
- Your workload requires maximal robustness to adversarial prompts and sophisticated jailbreak attempts.
- You need the absolute fastest inference latency available from OpenAI across all model classes.
FAQ
Frequently Asked Questions
-
What is GPT-5.4 Mini?
GPT-5.4 Mini is a lightweight OpenAI language model optimized for fast, low-cost text generation and reasoning via the LLM.API platform.
-
What modalities does GPT-5.4 Mini support?
GPT-5.4 Mini supports text-only input and output through LLM.API, without native image, audio, or video capabilities.
-
What is the context window of GPT-5.4 Mini?
GPT-5.4 Mini supports a context window of up to 16,000 tokens, including both input and generated output tokens.
-
How much does it cost to use GPT-5.4 Mini through LLM.API?
GPT-5.4 Mini is billed per 1,000 tokens through LLM.API, with exact prices defined in your LLM.API pricing and usage dashboard.
-
How fast is GPT-5.4 Mini in terms of latency and throughput?
GPT-5.4 Mini is designed for low latency and high throughput, making it suitable for interactive applications and parallel batch workloads.
-
What is GPT-5.4 Mini best suited for?
GPT-5.4 Mini is best for general-purpose chat, lightweight agents, rapid prototyping, and applications where response speed and cost are more important than peak accuracy.
-
How do I call GPT-5.4 Mini via LLM.API?
Use the LLM.API completion or chat endpoint with the model parameter set to "gpt-5.4-mini" and your standard authentication headers.
-
How does GPT-5.4 Mini compare to larger OpenAI models?
GPT-5.4 Mini is cheaper and faster than larger OpenAI models but generally less capable on complex reasoning, long-context synthesis, and highly specialized tasks.
-
Are there any important limitations of GPT-5.4 Mini?
GPT-5.4 Mini can hallucinate, lacks real-time knowledge access, and may underperform on very long, multi-step reasoning or highly domain-specific problems.
-
Can I fine-tune or customize GPT-5.4 Mini through LLM.API?
Fine-tuning availability for GPT-5.4 Mini depends on your LLM.API account features; check the dashboard or documentation for current support.
Compare
Competitive Models
- Text Generation
GLM 4.6 is Z.ai’s flagship mixture-of-experts large language model optimized for coding, reasoning, and agentic workflows. It is notable for its strong performance on code benchmarks…
- Text Generation
Claude Opus 4.5 is Anthropic’s frontier large language model optimized for advanced reasoning, coding, and long-context, agentic workflows. It is positioned as a flagship, high-intelligence model…