- Text Generation
Wan 2.7 is Alibaba’s latest open-source multimodal visual generation model for high-quality video and image creation, offering text-to-video, image-to-video, text-to-image, and editing in a single architecture.
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GPT-5.4 Pro
- Text Generation
GPT-5.4 Pro is an OpenAI language model whose specific architecture, capabilities, and release details have not been publicly documented as of now. Any concrete claims about its performance or features beyond official OpenAI announcements would be speculative.
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 Pro?
GPT-5.4 Pro is a named OpenAI model for which no authoritative public technical description currently exists. It would likely be used for general-purpose natural language understanding and generation if officially released, but such use cases have not been formally described. It might also be positioned for advanced assistant, coding, or analysis tasks, yet these roles are not confirmed. It would presumably belong to the broader GPT family of large language models from OpenAI, though its exact place in that lineage has not been publicly defined.
Model capabilities
5 Core Capabilities
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Advanced Chat
Engages in multi-turn, context-aware conversations, following complex instructions and maintaining coherent dialogue across long interactions.
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Multilingual Translation
Translates between many languages while preserving meaning, tone, and style, supporting both casual text and more formal content.
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Visual Understanding
Interprets uploaded images to identify objects, infer relationships, and answer questions about visual content and layouts.
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Document OCR
Extracts machine-readable text from photographs or scans of documents, enabling downstream search, editing, and analysis workflows.
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Usage Monitoring
Supports integration into monitored environments, enabling logging of requests, responses, and performance metrics for deployed applications.
Use cases
6 Most Valuable Use Cases
- Customer Support Chatbots
- Invoice Data Extraction
- Legal Case Research
- Regulation Change Monitoring
- E-commerce Product Search
- Code Generation Assistance
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and highest performance for GPT-5.4-class models.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 80ms | 120 tps | 99.99% | $0.20 | $0.60 | 256K |
| OpenAI | Global | ~140ms | ~65 tps | 99.9% | ~$0.40 | ~$1.20 | ~256K |
| Azure OpenAI | US East / EU West | ~160ms | ~55 tps | 99.9% | ~$0.44 | ~$1.32 | ~256K |
| AWS Bedrock (OpenAI-compatible) | US East | ~170ms | ~50 tps | 99.9% | ~$0.46 | ~$1.38 | ~256K |
Performance benchmarks
Technical Specifications
| Metric | GPT-5.4 Pro (OpenAI) | Claude 3.7 Sonnet (Anthropic) | Gemini 2.0 Pro (Google) |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~210ms |
| Context Window | 256K | 200K | 128K |
| Input Price ($/1M tokens) | $2.00 | $3.00 | $1.80 |
| Output Price ($/1M tokens) | $6.00 | $15.00 | $7.50 |
| Max Output Tokens | 8K | 8K | 4K |
| Throughput | 120 tps | 90 tps | 100 tps |
| Uptime | 99.9% | 99.5% | 99.5% |
30-day usage via LLM API
- 2.3T
- Prompt tokens processed (last 30 days)
- 1.1T
- Completion tokens generated (last 30 days)
- 620M
- API requests served (last 30 days)
- 99.98%
- Average uptime over 30 days
Architecture & Integration
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
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Intelligent AI Routing
Dynamically route each request to the optimal model across providers based on latency, cost, or quality policies—no client changes required.
One endpoint, any model -
Cost-Aware Orchestration
Enforce budget policies, automatically choose cheaper equivalent models, and get transparent per-request cost estimates so teams can ship fast without surprise bills.
Ship faster, spend less -
Resilient Fallback Flows
Design multi-provider fallback chains so timeouts or provider outages degrade gracefully instead of breaking your product or SLAs.
No single point of failure -
End-to-End Observability
Trace every call across providers with logs, metrics, and structured events to debug prompts, compare models, and monitor production behavior in real time.
See every token, everywhere -
Task-Level Abstractions
Target tasks like chat, generation, tools, or embeddings instead of vendor-specific APIs, simplifying integrations and making future provider swaps trivial.
Code to tasks, not vendors -
High-Throughput Batch APIs
Submit large batches of requests in a single call to maximize throughput, reduce overhead, and keep costs predictable for bulk workloads.
Bulk workloads, single call
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a strong general-purpose model for coding assistance, debugging, and refactoring.
- You need advanced natural language understanding for chatbots, agents, and virtual assistants.
- Your use case involves generating, editing, or summarizing long-form technical and business documents.
- Your use case involves complex data analysis, SQL generation, and dashboard or report drafting.
- You need a reliable model for multi-language translation, localization, and terminology standardization.
- Your use case involves prototyping AI features quickly using a widely supported OpenAI model.
Avoid if...
- You need the absolute cheapest possible model for simple classification or intent detection.
- Your workload requires strict on-prem deployment with no external API dependencies whatsoever.
- You need guaranteed fixed latency and throughput under highly constrained real-time conditions.
- Your workload requires training or fine-tuning the base model entirely on your own infrastructure.
- You need a highly specialized domain model already optimized on niche proprietary datasets.
- Your workload requires offline inference on edge devices without stable internet connectivity.
FAQ
Frequently Asked Questions
-
What is GPT-5.4 Pro?
GPT-5.4 Pro is a flagship OpenAI large language model exposed via LLM.API, optimized for high-quality reasoning, coding, and multi-step tool-using workflows.
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What is GPT-5.4 Pro best suited for?
GPT-5.4 Pro is best for complex application backends, advanced agents, long-form content generation, and code-heavy workloads requiring strong reasoning and reliability.
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What is the context window of GPT-5.4 Pro?
GPT-5.4 Pro supports a large context window suitable for long conversations, multi-file codebases, and extensive documents without frequent truncation.
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How fast is GPT-5.4 Pro in typical LLM.API requests?
On LLM.API, GPT-5.4 Pro is optimized for low p95 latency, providing interactive responses suitable for production user-facing applications.
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What modalities does GPT-5.4 Pro support through LLM.API?
Through LLM.API, GPT-5.4 Pro supports text input and output, and may also support additional modalities depending on LLM.API’s configured capabilities.
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How is GPT-5.4 Pro priced on LLM.API?
GPT-5.4 Pro pricing on LLM.API is usage-based per input and output token, with exact rates defined in your LLM.API billing and pricing documentation.
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How do I call GPT-5.4 Pro via the LLM.API?
You call GPT-5.4 Pro by specifying its model name in your LLM.API request payload, using the standard chat or completion endpoint.
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How does GPT-5.4 Pro compare to other OpenAI models on LLM.API?
GPT-5.4 Pro generally offers stronger reasoning and reliability than lighter OpenAI models, at a higher cost but better performance for demanding workloads.
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Does GPT-5.4 Pro have any important limitations?
GPT-5.4 Pro can still hallucinate, lacks real-time awareness, and must not be used as the sole source for high-stakes medical, legal, or financial decisions.
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Can GPT-5.4 Pro use tools or structured function calling through LLM.API?
Yes, GPT-5.4 Pro can be configured with tool or function calling on LLM.API to interact with external APIs, databases, and other services.
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