Last refreshed 2026-06-29. Next refresh: weekly.
Why use GPT-3.5 Turbo on Vercel AI Gateway?
Vercel AI Gateway offers GPT-3.5 Turbo with pay-as-you-go pricing at $0.50/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.
Compare GPT-3.5 Turbo across 6 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport AI_GATEWAY_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],openai/gpt-3.5-turboRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="openai/gpt-3.5-turbo",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "openai/gpt-3.5-turbo", not the LLMReference slug "gpt-3.5-turbo".
- creator/model-name e.g. kwaipilot/kat-coder-pro-v2
- The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.
Compare GPT-3.5 Turbo Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Azure OpenAI | $0.50 | $1.50 |
| OpenAI API | $0.50 | $1.50 |
| Salesforce Einstein Generative AI | — | — |
| OpenRouter | $0.50 | $1.50 |
| Replicate API | $0.50 | $1.50 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $1.50 |
Capabilities
About GPT-3.5 Turbo
GPT-3.5 Turbo is an advanced language model developed by OpenAI, showcasing significant advancements over GPT-3 and GPT-3.5. As the engine behind the popular ChatGPT application, it excels in tasks like text generation, translation, question answering, summarization, and code generation. This model employs Reinforcement Learning from Human Feedback (RLHF) to enhance accuracy and produce policy-optimized responses. Despite its prowess, it has a knowledge cutoff of September 2021 and can demonstrate biases from its training data. Occasionally, it may generate incorrect or nonsensical content, known as "hallucination," and is sensitive to input phrasing variations.