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 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.

Which endpoint do I call for GPT-3.5 Turbo?

POST https://api.llmapi.ai/v1/chat/completions with model "gpt-3.5-turbo" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to GPT-3.5 Turbo on LLM.API?

Change two lines: set base_url to https://api.llmapi.ai/v1 and api_key to your LLM.API key. The rest of your OpenAI SDK code stays the same.

Does GPT-3.5 Turbo support function calling and structured outputs?

Function calling: supported via tools. Structured outputs: not supported.

GPT-3.5 Turbo API: Endpoint & Pricing

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.

Start Using API

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.

Can you self-host GPT-3.5 Turbo?

No. We found no public weights for GPT-3.5 Turbo on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.

Skip the deploy — use LLM.API as your endpoint

No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, up to 30% below list price.

Get API key See API code ↓

Providers

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

List price by provider

InputOutput

openai$0.5 in

$1.5 out

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

Provider	Pricing	Context	Capabilities
openai	in $0.5; out $1.5 per 1M tokens	16K tokens	vision, tools, streaming, JSON

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 8 Oct 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.

Switching from OpenAI? Change 2 lines.

- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"

Everything else stays the same — SDK, message format, tools, streaming. Set model to gpt-3.5-turbo and the call runs unchanged.

bash

curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-3.5-turbo",
    "messages": [
      {"role": "user", "content": "Give me three crisp launch checklist items."}
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAPI_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)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.LLMAPI_KEY,
  baseURL: "https://api.llmapi.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "gpt-3.5-turbo",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

console.log(resp.choices[0].message.content);

stream = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Write a haiku about latency."}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

{
  "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."}
  ]
}

ENDPOINTS

Supported endpoints & features

Base URL https://api.llmapi.ai/v1 · model ID gpt-3.5-turbo · OpenAI-compatible.

POST /v1/chat/completionsChat Completions — supported

Feature	Status	How to set it
Function calling (tools)	Supported	`tools, tool_choice`
Parallel tool calls	Not supported	`parallel_tool_calls`
JSON mode	Supported	`response_format: {"type": "json_object"}`
Structured outputs	Not supported	`response_format: {"type": "json_schema", …}`
Streaming	Supported	`stream: true`
Vision (image input)	Supported	`image_url content parts`
Web search	Not supported	`web_search`

ERRORS

Errors & fallback routing

Code	What it means	What to do
`401`	Missing or invalid API key.	Send `Authorization: Bearer YOUR_LLMAPI_KEY` and check the key is active.
`429`	Rate limited, or the upstream provider is throttling the request.	Back off and retry with jitter; the gateway also retries the request on another provider where one is available.
`5xx`	Upstream provider error or timeout.	Retry; fallback routing sends the retry to the next healthy provider for this model.

When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.

GPT-3.5 Turbo in production

Best workloadsLLM.API features

What the model is good at.

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.

What you get when you call GPT-3.5 Turbo through LLM.API.

Unified AI Routing
Reach GPT-3.5 Turbo and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.
Cost Control
Practical: Compare provider price points and keep spend visible as you scale GPT-3.5 Turbo.
More performance, less spend.
Reliability Layer
Production: Retry and route across configured providers when a single upstream blips.
Never go dark on users.
Observability
Practical: Trace prompts, tokens, and errors for GPT-3.5 Turbo alongside the rest of your stack.
See every token, everywhere.
Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.
Model Breadth
Practical: Swap GPT-3.5 Turbo for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.

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

LLM API rating for GPT-3.5 Turbo

★ 2.0/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & value✓ Verified benchmark · LMArena + Artificial Analysis

2.2Production adoptionLegacy model, declining traffic

1.0Benchmark qualityArtificial Analysis Intelligence Index 5.5 · LMArena text rank #347, Elo 1125

2.8Developer ecosystemContext window, tool and JSON support, price against the category median

Reasoning & chat 2.0Coding 2.0Vision & multimodal 2.4Tool & function calling 2.9

How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

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.

Intelligence index-37% vs median

GPT-3.5 Turbo: Self-Hosting & Deployment Guide5

Median tracked model8

Higher is better. The median covers every model tracked by Artificial Analysis.

Reference price / 1M tokens

Input$0.50

Output$1.50

Provider list prices, before the LLM.API discount.

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)

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

LMArena#347 · Elo 1125Arena coding#338 · Elo 1137Speed—Sources: LMArena, Artificial Analysis

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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GPT-3.5 Turbo API: Endpoint & Pricing

What is GPT-3.5 Turbo?

Can you self-host GPT-3.5 Turbo?

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

GPT-3.5 Turbo in production

Multi-step reasoning

Long-context synthesis

Instruction following

Safety-aware replies

Conversational UX

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth