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GPT-5.5 Pro
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GPT-5.5 Pro is an OpenAI model name that has been mentioned publicly but has not been formally documented or specified by OpenAI as of now. Reliable technical details, capabilities, and release information about this model are not available.
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-5.5 Pro?
GPT-5.5 Pro is purported to be an OpenAI language model, but OpenAI has not released official specifications or documentation for it. Because of this, there are no verified details about its primary use cases, such as specific strengths in coding, reasoning, or multimodal tasks. Any claimed applications or benchmarks for GPT-5.5 Pro should be treated as unverified until OpenAI publishes authoritative information. It is presumably related in name to the GPT model family (e.g., GPT‑4 and GPT‑4.1), but its exact place in that lineup is not officially established.
Model capabilities
5 Core Capabilities
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Advanced Chat
Engages in complex, context-aware conversations, following detailed instructions and maintaining coherence across long, multi-step interactions.
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Multilingual Translation
Translates text between multiple languages, preserving meaning, tone, and style in both formal and informal contexts.
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Visual Image Analysis
Interprets images to identify objects, scenes, and relationships, enabling visual question answering and content description.
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On-Screen Monitoring
Understands and reasons about content displayed on screens, such as interfaces, documents, or webpages, to assist with digital tasks.
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Text Recognition
Extracts and interprets textual information from images or screenshots, enabling search, editing, and analysis of captured content.
Use cases
6 Most Valuable Use Cases
- Customer Support Chatbots
- Invoice Data Extraction
- Legal Document Search
- Regulatory Change Monitoring
- E-commerce Product Copy
- Code Generation Assistance
Transparent pricing
Cost Comparison
LLM API offers the lowest cost and latency with the largest context window for GPT-5.5–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 | ~160ms | ~60 tps | ~99.9% | ~$0.40 | ~$1.20 | ~128K |
| Azure OpenAI | US East | ~180ms | ~55 tps | ~99.9% | ~$0.44 | ~$1.32 | ~128K |
| Google Cloud (Gemini-equivalent) | Global | ~190ms | ~50 tps | ~99.9% | ~$0.48 | ~$1.40 | ~128K |
| Amazon Bedrock (Claude-equivalent) | US West | ~200ms | ~45 tps | ~99.9% | ~$0.46 | ~$1.36 | ~200K |
Performance benchmarks
Technical Specifications
| Metric | GPT-5.5 Pro | Claude 3.7 Sonnet | Gemini 2.0 Advanced |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 256K | 200K | 128K |
| Input Price ($/1M) | $2.50 | $3.00 | $2.80 |
| Output Price ($/1M) | $7.50 | $9.00 | $8.50 |
| Max Output Tokens | 8K | 4K | 8K |
| Throughput | 120 tps | 80 tps | 90 tps |
| Uptime | 99.95% | 99.9% | 99.9% |
30-day usage via LLM API
- 185B
- Prompt tokens processed (last 30 days)
- 42M
- API requests served (last 30 days)
- 260B
- Completion tokens generated (last 30 days)
- 99.97%
- Average uptime (last 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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Unified AI Routing
Dynamically route each request to the best model across providers based on latency, price, and quality. One API, no vendor lock-in or rewrites.
One endpoint, every model -
Cost-Aware Orchestration
Control spend with per-route price caps, tiered model selection, and usage insights. Optimize cost-performance automatically, without touching your application logic.
Predictable, optimized spend -
Resilient Fallback Paths
Define automatic failover chains when a model or provider degrades. Keep production workloads online with graceful retries, backups, and policy-driven fallbacks.
Never go dark -
Deep Observability
Trace every request across models and providers with rich logs, metrics, and latency breakdowns. Debug failures faster and tune prompts with real production data.
See every token -
Task-Level Abstractions
Describe tasks like chat, extraction, or generation once and let LLM.API pick and configure the right models. Ship features without chasing provider-specific APIs.
Think tasks, not models -
High-Throughput Batch
Submit massive batches through a single call with built-in concurrency control, retries, and cost tracking. Process millions of inferences reliably without bespoke pipelines.
Scale to millions
Decision guide
When to Use — When NOT to Use
Use it if...
- You need state-of-the-art reasoning and coding assistance for complex, ambiguous tasks.
- You need a general-purpose model for chat, agents, tools, and structured outputs.
- You need strong performance on long-context summarization, transformation, and synthesis workloads.
- Your use case involves multimodal inputs, combining text with images or other formats.
- Your use case involves iterative product development where high-quality model feedback accelerates cycles.
- You need robust support, monitoring, and governance features from a mature enterprise provider.
- You need good default safety, refusal behavior, and content filtering for consumer applications.
Avoid if...
- You need the absolutely lowest per-token cost for massive, low-intelligence batch jobs.
- You need an on-prem or fully air‑gapped deployment with no external connectivity.
- Your workload requires hard real-time guarantees or ultra-low latency under 50 milliseconds.
- You need full model weights access for custom pretraining or fundamental architecture changes.
- Your workload requires complete independence from third-party cloud providers for regulatory reasons.
- You need deterministic, formally verifiable outputs instead of probabilistic natural language behavior.
- Your workload requires tight mobile or edge deployment where tiny models are mandatory.
FAQ
Frequently Asked Questions
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What is GPT-5.5 Pro?
GPT-5.5 Pro is a large language model from OpenAI focused on high-quality reasoning, coding, and agentic workflows via the LLM.API platform.
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What is GPT-5.5 Pro best suited for?
GPT-5.5 Pro is best for complex multi-step reasoning, advanced coding and debugging, and orchestrating tool-using or agent-like backends for production applications.
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What modalities does GPT-5.5 Pro support through LLM.API?
GPT-5.5 Pro supports text input and output via LLM.API, and may expose additional modalities as the provider enables them.
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How is GPT-5.5 Pro priced on LLM.API?
GPT-5.5 Pro pricing on LLM.API is usage-based per input and output token, with exact rates defined in your LLM.API account billing settings.
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What is the context window of GPT-5.5 Pro?
GPT-5.5 Pro supports a large context window suitable for long conversations and documents; check the LLM.API docs for the exact token limit.
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How fast is GPT-5.5 Pro in terms of latency?
GPT-5.5 Pro is optimized for low interactive latency on LLM.API, but actual response time depends on payload size and current platform load.
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How do I call GPT-5.5 Pro from my application via LLM.API?
You select the GPT-5.5 Pro model name in your LLM.API request payload, authenticate with your LLM.API key, and send standard completion or chat requests.
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How does GPT-5.5 Pro compare to other OpenAI models on LLM.API?
Compared to earlier OpenAI models, GPT-5.5 Pro generally offers stronger reasoning and code performance, with a larger context window and higher reliability for production use.
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What are the main limitations of GPT-5.5 Pro?
GPT-5.5 Pro can still produce incorrect or fabricated answers, lacks real-time knowledge beyond its training and tools, and should not replace domain experts.
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Does GPT-5.5 Pro support function calling or tools via LLM.API?
Yes, GPT-5.5 Pro can be used with LLM.API's tool or function-calling abstractions when configured, enabling structured outputs and external system interactions.
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