- Text Generation
Devstral 2 2512 is a 123B-parameter open-source large language model from Mistral AI, optimized for agentic coding and long-context software engineering workflows. It supports a 256K/262K-token…
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GPT Chat Latest
- Text Generation
GPT Chat Latest is OpenAI’s most up-to-date GPT-based chat model, offering strong general-purpose reasoning, coding, and writing capabilities. It is designed for interactive conversations and assistance across a wide range of tasks.
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 Chat Latest?
GPT Chat Latest is an OpenAI conversational AI model that provides current, general-purpose language understanding and generation. It is mainly used for interactive chat-based assistance, such as answering questions, drafting content, and explaining complex topics. It is also used for practical workflows like code assistance, brainstorming, and helping integrate natural-language capabilities into applications. It belongs to OpenAI’s GPT family of large language models, following earlier GPT-based chat systems.
Model capabilities
5 Core Capabilities
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Conversational Chat
Engages in multi-turn dialogue, follows instructions, and provides helpful, context-aware responses across a wide range of topics.
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Image Understanding
Interprets images to describe scenes, recognize objects, read embedded text, and answer questions about visual content.
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Text Translation
Translates text between many languages while preserving meaning and tone, useful for cross-lingual communication and content localization.
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Document OCR
Extracts and interprets text from images or scanned documents, enabling search, analysis, and transformation of visual text content.
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Web Integration
Uses online tools and browsing to retrieve current information, check facts, and augment responses with up-to-date external knowledge.
Use cases
6 Most Valuable Use Cases
- Customer Support Chat
- Invoice Data Extraction
- Legal Case Research
- Regulation Change Monitoring
- Marketing Content Drafting
- Code Generation Assistance
Transparent pricing
Cost Comparison
Up to ~70% cheaper and faster than comparable GPT-class chat models
| Provider | Region | Latency | Throughput | Uptime | Input ($/1M) | Output ($/1M) | Context |
|---|---|---|---|---|---|---|---|
| LLM API BEST | Global | 120ms | 80 tps | 99.99% | $0.20 | $0.60 | 256K |
| OpenAI | Global | ~250ms | ~40 tps | 99.9% | ~$0.60 | ~$1.80 | 128K |
| Azure OpenAI | US East / EU West | ~280ms | ~35 tps | 99.9% | ~$0.65 | ~$1.90 | 128K |
| Together AI | US West | ~230ms | ~30 tps | ~99.5% | ~$0.55 | ~$1.70 | 128K |
| Anyscale Endpoints | US Central | ~260ms | ~32 tps | ~99.5% | ~$0.58 | ~$1.75 | 128K |
Performance benchmarks
Technical Specifications
| Metric | GPT Chat Latest (OpenAI) | Claude 3.5 Sonnet (Anthropic) | Gemini 1.5 Pro (Google) |
|---|---|---|---|
| Avg Latency | ~180ms | ~220ms | ~250ms |
| Context Window | 128K | 200K | 1M |
| Input Price ($/1M tokens) | $0.50 | $3.00 | $3.50 |
| Output Price ($/1M tokens) | $1.50 | $15.00 | $10.50 |
| Max Output Tokens | 4K | 4K | 8K |
| Throughput | ~120 tps | ~80 tps | ~70 tps |
| Uptime | 99.9% | 99.5% | 99.5% |
30-day usage via LLM API
- 182B
- Prompt tokens processed (last 30 days)
- 54B
- Completion tokens generated (last 30 days)
- 96M
- API requests served (last 30 days)
- 12.4M
- Unique developer & app users (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 using policies, performance data, and constraints—no client changes or manual wiring required.
One endpoint, every model. -
Cost-Aware Orchestration
Define cost caps and smart downgrade rules so non-critical workloads hit cheaper models automatically while critical paths retain premium performance.
Optimize spend by default. -
Resilient Fallbacks
Configure automatic failover to alternate models or providers on errors, timeouts, or rate limits to keep production workloads online without custom retry logic.
No single point of failure. -
End-to-End Observability
Inspect requests, latencies, token usage, and provider performance from one place, with structured logs and traces ready for your existing monitoring stack.
See every token, everywhere. -
Task-Level Abstractions
Describe tasks—chat, embeddings, tools, RAG—once and let LLM.API map them to compatible models and providers as they evolve over time.
Code to tasks, not models. -
High-Throughput Batch
Ship thousands of requests in a single batch job with automatic sharding, retries, and aggregation, dramatically reducing latency and API overhead.
Scale workloads, not code.
Decision guide
When to Use — When NOT to Use
Use it if...
- You need a strong general-purpose chat model for diverse everyday assistant tasks.
- You need up-to-date web-aware answers on news, products, tools, or APIs.
- Your use case involves drafting, rewriting, or polishing emails, documents, or marketing copy.
- Your use case involves coding help, quick prototypes, or explaining programming concepts clearly.
- You need natural language understanding for classification, extraction, or question answering over text.
- Your use case involves interactive brainstorming, ideation, or refining product and UX concepts.
Avoid if...
- You need guaranteed offline inference without any connection to external cloud services.
- You need strict, auditable on-prem deployment to satisfy highly sensitive regulatory requirements.
- Your workload requires deterministic, bit-for-bit reproducible outputs across runs and environments.
- You need hard real-time responses under tight latency bounds on constrained edge hardware.
- Your workload requires training or fine-tuning a fully custom base model from scratch.
- You need processing of extremely sensitive data where external cloud processing is categorically forbidden.
FAQ
Frequently Asked Questions
-
What is GPT Chat Latest?
GPT Chat Latest is LLM.API’s alias for OpenAI’s most recent general-purpose GPT chat model, automatically tracking OpenAI’s default production chat release.
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What is GPT Chat Latest best suited for?
GPT Chat Latest is best for everyday chat, code assistance, and general reasoning tasks where you always want OpenAI’s newest stable chat model without manual upgrades.
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What is the context window of GPT Chat Latest?
Because GPT Chat Latest tracks OpenAI’s current default, its exact context window size can change; check the LLM.API model docs for the current token limit.
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What modalities does GPT Chat Latest support?
GPT Chat Latest inherits modalities from OpenAI’s current default chat model, typically supporting text input and output and possibly additional modalities if that default does.
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How is GPT Chat Latest priced on LLM.API?
GPT Chat Latest uses LLM.API’s unified pricing layer, which may differ from OpenAI’s direct prices; refer to the LLM.API pricing table for current per-token rates.
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How fast is GPT Chat Latest in terms of latency?
Latency for GPT Chat Latest generally matches other top-tier OpenAI chat models, but actual speed depends on LLM.API routing, load, and your request size.
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How do I call GPT Chat Latest through the LLM.API?
Specify the model name "gpt-chat-latest" in your LLM.API request payload; authentication, endpoints, and rate limits follow the standard LLM.API conventions.
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How does GPT Chat Latest compare to pinning a specific OpenAI GPT model?
GPT Chat Latest auto-upgrades to newer OpenAI defaults, while pinning a specific model gives stable behavior and performance until you explicitly change versions.
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Can GPT Chat Latest access tools or structured outputs via LLM.API?
Tool use and structured outputs depend on LLM.API’s capabilities; if supported, GPT Chat Latest can be used with tools and schema-guided responses like other models.
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What are the main limitations of GPT Chat Latest?
GPT Chat Latest can still hallucinate, lacks real-time internet access by default, and its exact capabilities may shift whenever OpenAI updates the default chat model.
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