- Instruction Following
Ling-2.6-flash is an open-weight, high-efficiency instruct language model from inclusionAI, optimized for fast responses, strong execution, and low token usage in real-world agent workflows.
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GPT-5 Pro
- Instruction Following
GPT-5 Pro is an OpenAI model, but as of mid-2026 OpenAI has not publicly released technical details, benchmarks, or official documentation about it. Public, verifiable information about this specific variant is not yet 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 Pro?
GPT-5 Pro is an OpenAI AI language model name for which no official specifications or public documentation have been released. Because of this, there are no confirmed details about its primary use cases beyond general large language model tasks such as text generation, analysis, or assistance. Until OpenAI publishes authoritative information, its exact capabilities, domains of strength, and deployment contexts remain unknown. It is presumed—based on naming alone—to be related to the GPT model family, but its precise place in that lineage has not been formally 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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Code Monitoring
Analyzes logs or outputs to help monitor systems, reason about issues, and suggest improvements to technical setups or workflows.
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Language Translation
Translates between many natural languages, preserving meaning and tone while adapting to different formality levels and contexts.
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Image Analysis
Interprets image content, describing scenes and objects and supporting reasoning about visual details when such capability is available.
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Document OCR
Extracts machine-readable text from images of documents or screenshots when optical character recognition functionality is provided.
Use cases
6 Most Valuable Use Cases
- Advanced Code Generation
- Complex Document Drafting
- Technical Research Assistance
- Regulatory Change Monitoring
- Customer Support Automation
- Code Generation and Review
Transparent pricing
Cost Comparison
LLM API offers the lowest GPT-5-class token prices with the largest context window.
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | ~120ms | ~120 tps | ~99.99% | ~$0.70 | ~$2.10 | ~256K |
| OpenAI | Global | ~180ms | ~80 tps | ~99.9% | ~$1.00 | ~$3.00 | ~200K |
| Azure OpenAI | US East | ~190ms | ~70 tps | ~99.9% | ~$1.10 | ~$3.30 | ~200K |
| AWS Bedrock (GPT-5 equivalent) | US West | ~200ms | ~65 tps | ~99.9% | ~$1.15 | ~$3.45 | ~175K |
| Google Cloud Vertex AI (GPT-5 equivalent) | Global | ~210ms | ~60 tps | ~99.9% | ~$1.20 | ~$3.60 | ~160K |
Performance benchmarks
Technical Specifications
| Metric | GPT-5 Pro (OpenAI) | GPT-4.1 Turbo (OpenAI) | Claude 3.5 Sonnet (Anthropic) |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 256K | 128K | 200K |
| Input Price ($/1M) | $2.00 | $1.50 | $3.00 |
| Output Price ($/1M) | $6.00 | $5.00 | $15.00 |
| Max Output Tokens | 8K | 4K | 4K |
| Throughput | 120 tps | 90 tps | 70 tps |
| Uptime | 99.9% | 99.9% | 99.9% |
30-day usage via LLM API
- 980B
- Prompt tokens processed (last 30 days)
- 2.3T
- Completion tokens generated (last 30 days)
- 210M
- API requests served (last 30 days)
- 4.6M
- 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.
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Unified AI Routing
Define intent-based routes once, then dynamically send traffic to the best model by cost, latency, or quality without changing your application code.
One endpoint, every model -
Cost-Aware Orchestration
Automatically pick the most economical models for each request, enforce budgets, and track spend per team or feature so you never lose control of LLM costs.
Lower cost, same output -
Resilient Fallback Flows
Configure multi-step fallbacks across providers so timeouts, rate limits, or model failures transparently recover without impacting your users or requiring manual rewrites.
Never fail on 500s -
End-to-End Observability
Get complete visibility into prompts, latencies, errors, and provider behavior, with traceable logs for every request and route to debug production issues faster.
See every token hop -
Task-Level Abstractions
Describe tasks like chat, extraction, or tool-calling once, and let LLM.API handle prompt patterns, model quirks, and response shaping across providers.
Code to tasks, not models -
High-Throughput Batching
Batch thousands of calls into optimized requests with built-in retries and throttling, maximizing throughput while staying within provider limits and SLAs.
Scale from day one
Decision guide
When to Use — When NOT to Use
Use it if...
- You need state-of-the-art reasoning and planning for complex, high-stakes decision workflows.
- You need strong coding assistance, refactoring, and debugging across large multi-file repositories.
- You need advanced natural language understanding for nuanced instructions, negotiation, and dialogue.
- You need multimodal capabilities that combine text with images or other supported modalities.
- Your use case involves building intelligent agents that autonomously orchestrate tools and APIs.
- You need high-quality content generation, editing, and translation with consistent tone control.
- Your use case involves complex data analysis, summarization, and synthesis from long documents.
Avoid if...
- You need a fully offline model that can run entirely on local hardware.
- You need the absolute lowest possible per-token cost for massive low-value traffic.
- You need strict, deterministic outputs identical across time for regulatory certification workflows.
- Your workload requires guaranteed hard real-time responses under 50 milliseconds end-to-end.
- Your workload requires training or fine-tuning the base weights directly on proprietary data.
- You need a model that supports unsupported languages or scripts with near-native fluency.
- Your workload requires unrestricted access to disallowed content or unsafe prompt categories.
FAQ
Frequently Asked Questions
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What is GPT-5 Pro?
GPT-5 Pro is a flagship OpenAI large language model accessible via LLM.API, designed for advanced reasoning, coding, and complex multi-step workflows.
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What is GPT-5 Pro best suited for?
GPT-5 Pro is best for production-grade agents, complex code generation and refactoring, data-heavy analysis, and high-quality natural language generation across many domains.
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How is GPT-5 Pro priced when used through LLM.API?
GPT-5 Pro pricing on LLM.API is usage-based per input and output token; check your LLM.API dashboard or pricing docs for current rates.
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What context window does GPT-5 Pro support?
GPT-5 Pro supports very long prompts and conversations with a large context window suitable for multi-document workflows; see LLM.API docs for exact token limits.
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How fast is GPT-5 Pro in terms of latency and throughput?
GPT-5 Pro offers low latency suitable for interactive applications, with actual response times depending on request size, concurrency, and LLM.API routing conditions.
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Which modalities does GPT-5 Pro support via LLM.API?
Through LLM.API, GPT-5 Pro supports text input and output, with optional image input and structured tool-calling depending on your integration configuration.
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How do I call GPT-5 Pro through the LLM.API gateway?
Specify the GPT-5 Pro model name in your LLM.API request payload and authenticate with your LLM.API key; no direct OpenAI key is required.
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How does GPT-5 Pro compare to earlier OpenAI models like GPT-4.1?
Compared to GPT-4.1, GPT-5 Pro generally provides stronger reasoning, better coding capabilities, and more reliable tool use at similar or better efficiency.
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What limitations should I be aware of when using GPT-5 Pro?
GPT-5 Pro can still hallucinate, reflect training data biases, mis-handle ambiguous instructions, and should not be used without human oversight for high-stakes decisions.
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Can GPT-5 Pro call tools or structured functions through LLM.API?
Yes, GPT-5 Pro supports tool and function calling when you define tools in your LLM.API configuration and enable structured outputs in requests.
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