Model APIs

Model APIs provide instant access to high-performance LLMs through OpenAI-compatible endpoints. Point your existing OpenAI SDK at Baseten’s inference endpoint and start making calls, no model deployment required. Unlike self-deployed models, where you configure hardware, engines, and scaling yourself, Model APIs run on shared infrastructure that Baseten manages. You get a fixed set of popular models with optimized serving out of the box. When you need a model that isn’t in the supported list, or want dedicated GPUs with custom scaling, deploy your own with Truss.

Supported models

Enable a model from the Model APIs page in the Baseten dashboard.

Model	Slug	Context	Max output
DeepSeek V3 0324	`deepseek-ai/DeepSeek-V3-0324`	164k	131k
DeepSeek V3.1	`deepseek-ai/DeepSeek-V3.1`	164k	131k
GLM 4.6	`zai-org/GLM-4.6`	200k	200k
GLM 4.7	`zai-org/GLM-4.7`	200k	200k
GLM 5	`zai-org/GLM-5`	203k	203k
Kimi K2.5	`moonshotai/Kimi-K2.5`	262k	262k
Minimax M2.5	`MiniMaxAI/MiniMax-M2.5`	204k	204k
OpenAI GPT OSS 120B	`openai/gpt-oss-120b`	128k	128k

Pricing

Pricing is per million tokens.

Model	Input	Output
OpenAI GPT OSS 120B	$0.10	$0.50
Minimax M2.5	$0.30	$1.20
DeepSeek V3.1	$0.50	$1.50
GLM 4.6	$0.60	$2.20
GLM 4.7	$0.60	$2.20
Kimi K2.5	$0.60	$3.00
DeepSeek V3 0324	$0.77	$0.77
GLM 5	$0.95	$3.15

Query the /v1/models endpoint for current pricing.

Feature support

All models support tool calling. Support for other features varies by model. See Reasoning for configuration details.

Model	JSON mode	Structured outputs	Reasoning	Vision
DeepSeek V3 0324	Yes	Yes	Enabled by default	No
DeepSeek V3.1	No	No	Enabled by default	No
GLM 4.6	Yes	Yes	Opt-in	No
GLM 4.7	Yes	Yes	Opt-in	No
GLM 5	Yes	Yes	No	No
Kimi K2.5	Yes	Yes	Opt-in	Yes
Minimax M2.5	Yes	Yes	Enabled by default	No
OpenAI GPT OSS 120B	Yes	Yes	Enabled by default	No

GLM models also support top_p and top_k sampling parameters.

Create a chat completion

If you’ve already completed the quickstart, you have a working client. The examples below show a multi-turn conversation with a system message, which you can adapt for your application.

Python
JavaScript
cURL

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://inference.baseten.co/v1",
    api_key=os.environ["BASETEN_API_KEY"],
)

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3.1",
    messages=[
        {"role": "system", "content": "You are a concise technical writer."},
        {"role": "user", "content": "What is gradient descent?"},
        {"role": "assistant", "content": "An optimization algorithm that iteratively adjusts model parameters by moving in the direction of steepest decrease in the loss function."},
        {"role": "user", "content": "How does the learning rate affect it?"}
    ],
)

print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
    baseURL: "https://inference.baseten.co/v1",
    apiKey: process.env.BASETEN_API_KEY,
});

const response = await client.chat.completions.create({
    model: "deepseek-ai/DeepSeek-V3.1",
    messages: [
        { role: "system", content: "You are a concise technical writer." },
        { role: "user", content: "What is gradient descent?" },
        { role: "assistant", content: "An optimization algorithm that iteratively adjusts model parameters by moving in the direction of steepest decrease in the loss function." },
        { role: "user", content: "How does the learning rate affect it?" }
    ],
});

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

curl https://inference.baseten.co/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Api-Key $BASETEN_API_KEY" \
  -d '{
    "model": "deepseek-ai/DeepSeek-V3.1",
    "messages": [
      {"role": "system", "content": "You are a concise technical writer."},
      {"role": "user", "content": "What is gradient descent?"},
      {"role": "assistant", "content": "An optimization algorithm that iteratively adjusts model parameters by moving in the direction of steepest decrease in the loss function."},
      {"role": "user", "content": "How does the learning rate affect it?"}
    ]
  }'

Replace the model slug with any model from the supported models table.

Features

Model APIs are compatible with the OpenAI Chat Completions API. Available features include structured outputs, tool calling, reasoning, vision, and streaming (stream: true). Not all models support every feature. See feature support for per-model availability. For the complete parameter reference, see the Chat Completions API documentation.

List available models

Query the /v1/models endpoint for the current list of models with metadata including pricing, context lengths, and supported features.

curl https://inference.baseten.co/v1/models \
  -H "Authorization: Api-Key $BASETEN_API_KEY"

Migrate from OpenAI

To migrate existing OpenAI code to Baseten, change three values:

Replace your API key with a Baseten API key.
Change the base URL to https://inference.baseten.co/v1.
Update the model name to a Baseten model slug.

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://inference.baseten.co/v1",  
    api_key=os.environ["BASETEN_API_KEY"]  
)

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3.1",  
    messages=[{"role": "user", "content": "Hello"}]
)

Handle errors

Model APIs return standard HTTP error codes:

Code	Meaning
400	Invalid request (check your parameters)
401	Invalid or missing API key
402	Payment required
404	Model not found
429	Rate limit exceeded
500	Internal server error

The response body contains details about the error and suggested resolutions.

Next steps

Reasoning

Control extended thinking for complex tasks

Vision

Send images and videos alongside text

Rate limits

Understand and configure rate limits

API reference

Complete parameter documentation

Get started

Concepts

Development

Deployment

Inference

Engines

Training

Organization

Observability

Troubleshooting

Supported models

Pricing

Feature support

Create a chat completion

Features

List available models

Migrate from OpenAI

Handle errors

Next steps

Reasoning

Vision

Rate limits

API reference

Get started

Concepts

Development

Deployment

Inference

Engines

Training

Organization

Observability

Troubleshooting

​Supported models

​Pricing

​Feature support

​Create a chat completion

​Features

​List available models

​Migrate from OpenAI

​Handle errors

​Next steps

Reasoning

Vision

Rate limits

API reference

Supported models

Pricing

Feature support

Create a chat completion

Features

List available models

Migrate from OpenAI

Handle errors

Next steps