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GPT-3.5 Turbo

Up to 30%Deprecated 23 Oct 2026

Call GPT-3.5 Turbo through LLM.API when you want OpenAI-family text generation with unified auth, provider choice, and production-friendly defaults.

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What is GPT-3.5 Turbo?

GPT-3.5 Turbo is an OpenAI chat model exposed on LLM.API under id `gpt-3.5-turbo`. Fast and cost-effective model for simple tasks and conversational applications. Teams use it when they need reliable text generation with text, image inputs and text outputs over an OpenAI-compatible API.

Providers

LLM.API routes GPT-3.5 Turbo to the providers below, with discounted effective rates versus list price.

List price by provider ($ / 1M tokens)

InputOutput
openai$0.5 in
$1.5 out

Provider list prices; the LLM.API discount applies on top.

ProviderPricingContextCapabilities
openai30% offin $500; out $1500 per 1M tokens16K tokensvision, tools, streaming, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test GPT-3.5 Turbo right here — free to start.

GPT-3.5 Turbo
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call GPT-3.5 Turbo through the OpenAI-compatible API — POST /v1/chat/completions.

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "gpt-3.5-turbo",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Multi-step reasoning

    Breaks down complex problems into intermediate steps before answering.

  • Long-context synthesis

    Summarizes and cross-references information across large prompts when context allows. Tuned to how teams typically call GPT-3.5 Turbo.

  • Instruction following

    Follows detailed system and user instructions with strong adherence to format and tone. Grounded in the model's chat role rather than generic chat claims.

  • Safety-aware replies

    Supports product policies with refusals and cautious handling of sensitive topics. Tuned to how teams typically call GPT-3.5 Turbo.

  • Conversational UX

    Maintains coherent multi-turn assistant behavior for product chat surfaces. Grounded in the model's chat role rather than generic chat claims.

6 Most Valuable Use Cases

  • Policy Q&A bots with careful refusal behavior with GPT-3.5 Turbo
  • Internal knowledge assistants grounded with your retrieval layer
  • Sales and success email drafting with CRM context with GPT-3.5 Turbo
  • Data extraction into JSON for downstream systems
  • Customer support copilots that draft accurate, on-brand replies with GPT-3.5 Turbo
  • Multilingual localization drafts for UX copy

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run GPT-3.5 Turbo on LLM.API?

  • Unified AI Routing

    Reach GPT-3.5 Turbo and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Practical: Compare provider price points and keep spend visible as you scale GPT-3.5 Turbo.

  • Reliability Layer

    Production: Retry and route across configured providers when a single upstream blips.

  • Observability

    Practical: Trace prompts, tokens, and errors for GPT-3.5 Turbo alongside the rest of your stack.

  • Drop-in SDKs

    Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Practical: Swap GPT-3.5 Turbo for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (GPT-3.5 Turbo)
  • You need a general-purpose text model for assistants, agents, or content workflows (GPT-3.5 Turbo)
  • You need provider failover options exposed for this model id (GPT-3.5 Turbo)
  • You want OpenAI-compatible chat completions through a single LLM.API key (GPT-3.5 Turbo)

Avoid if...

  • You require on-prem only deployment with no cloud inference
  • You need guaranteed real-time hard latency SLAs without benchmarking the provider
  • You need pure embedding, OCR, or media generation instead of chat
  • Your use case depends on unpublished proprietary benchmarks not listed here

BENCHMARKS

GPT-3.5 Turbo benchmark scores

Intelligence index

This model5.
Tracked median8.

Scale: 0-100 index points

Reference price per 1M tokens

Input$0.50
Output$1.50

Bars compare input and output list prices for this model.

Artificial Analysis Intelligence Index5
Median index across all tracked models8
Reference input price$0.50 / 1M tokens
Reference output price$1.50 / 1M tokens

Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.

RELIABILITY

GPT-3.5 Turbo uptime, last 30 days

30-Day Uptime
96.70%
Past Incidents (30d)
3
Error rate (24h)
9.27%

Last 30 days

26/30 days operational | 96.70% uptime

Availability tracked for this model. Full history on the LLM Uptime Status page or the status hub. LLM.API routes around provider outages automatically.

COMMUNITY

What developers say about OpenAI models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to GPT-3.5 Turbo.

  • Long-horizon coding reports on GPT-6 Astra describe a clear step up over the GPT-5.x line, with the higher reasoning tiers seen as the sweet spot for planning and implementation in large (100K+ LOC) codebases.
  • The same field reports note that fast/ultra modes burn quota quickly and that very large refactors still stall, so teams tend to mix a cheap tier for routine calls with a reasoning tier for hard steps.
  • Community threads temper the hype: capability gains are acknowledged, but developers still report the usual failure modes on obscure reverse-engineering and modding work.

SOURCES

Frequently Asked Questions

  • Can I use tools or structured outputs with GPT-3.5 Turbo?

    Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

  • Where is the canonical page for GPT-3.5 Turbo?

    https://llmapi.ai/models/openai-gpt-3-5-turbo/

  • How is GPT-3.5 Turbo priced on LLM.API?

    Listed pricing metadata shows: In $0.5 / 1M tokens · Out $1.5 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • How do I call GPT-3.5 Turbo via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "gpt-3.5-turbo" and your LLM.API key. See the code snippet on this page.

  • Is GPT-3.5 Turbo a chat model?

    Yes—GPT-3.5 Turbo is exposed as a chat/completions-style endpoint on LLM.API.

  • Does GPT-3.5 Turbo support streaming?

    Yes—at least one listed provider advertises streaming.

  • When should I choose GPT-3.5 Turbo?

    Your prompts benefit from the model's family strengths (reasoning, speed, or cost) — especially when you specifically need GPT-3.5 Turbo.

  • What is GPT-3.5 Turbo?

    Fast and cost-effective model for simple tasks and conversational applications. On LLM.API it is addressed as `gpt-3.5-turbo`.

  • What is the context length for GPT-3.5 Turbo?

    Reported context for GPT-3.5 Turbo is 16K tokens. Always verify the active provider row if multiple providers are listed.

  • Which providers serve GPT-3.5 Turbo?

    LLM.API currently lists: openai. Availability can vary by region and account.

  • What modalities does GPT-3.5 Turbo support?

    GPT-3.5 Turbo accepts text, image and produces text according to its architecture metadata on LLM.API.

  • What are limitations of GPT-3.5 Turbo?

    Like other API models, GPT-3.5 Turbo can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

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