Comparison beginner · 3 min read

Together AI vs OpenAI comparison

Quick answer

Together AI and OpenAI both offer powerful large language model APIs with OpenAI providing a broader model selection including gpt-4o, while Together AI specializes in high-performance meta-llama models. Both support OpenAI-compatible SDKs, but Together AI is preferred for large-scale Llama-based deployments and OpenAI for general-purpose chat and multimodal tasks.

VERDICT

Use OpenAI for versatile, widely supported AI applications with extensive model options; choose Together AI for optimized Llama-3.3-70B models and cost-effective large-scale deployments.

Tool	Key strength	Pricing	API access	Best for
OpenAI	Broadest model variety including gpt-4o and multimodal	Pay-as-you-go, competitive	Official openai SDK with native support	General-purpose chat, coding, multimodal tasks
Together AI	Optimized large Llama-3.3-70B instruct models	Competitive, often lower for large models	OpenAI-compatible SDK with base_url override	High-scale Llama deployments, instruction tuning
OpenAI	Strong ecosystem and plugin integrations	Transparent pricing tiers	SDK v1+ with extensive tooling	Rapid prototyping and production apps
Together AI	Focus on Llama model family with instruction tuning	Flexible pricing for enterprise	OpenAI-compatible API endpoint	Llama-based research and custom solutions

Key differences

OpenAI offers a wide range of models including gpt-4o and multimodal capabilities, making it versatile for many AI tasks. Together AI focuses on large-scale Llama-3.3-70B models optimized for instruction tuning and cost efficiency. OpenAI has a mature ecosystem with plugins and multimodal support, while Together AI provides a specialized API endpoint compatible with OpenAI SDKs but tailored for Llama workloads.

Side-by-side example

Here is how to call the chat completion API for a simple prompt using the official openai SDK for both providers.

python

import os
from openai import OpenAI

# OpenAI client
openai_client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
response_openai = openai_client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Explain RAG in AI."}]
)
print("OpenAI response:", response_openai.choices[0].message.content)

# Together AI client (OpenAI-compatible with base_url)
together_client = OpenAI(
    api_key=os.environ["TOGETHER_API_KEY"],
    base_url="https://api.together.xyz/v1"
)
response_together = together_client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
    messages=[{"role": "user", "content": "Explain RAG in AI."}]
)
print("Together AI response:", response_together.choices[0].message.content)

output

OpenAI response: Retrieval-Augmented Generation (RAG) is a technique that combines retrieval of relevant documents with generative models to produce accurate and context-aware answers.
Together AI response: RAG stands for Retrieval-Augmented Generation, a method that enhances language models by integrating external knowledge retrieval to improve response accuracy.

Together AI equivalent

Using Together AI with the OpenAI SDK pattern requires specifying the base_url and using their Llama-3.3-70B instruct model. This approach is ideal for users familiar with OpenAI's SDK but wanting to leverage Llama models.

python

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ["TOGETHER_API_KEY"],
    base_url="https://api.together.xyz/v1"
)
response = client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
    messages=[{"role": "user", "content": "Summarize the benefits of RAG."}]
)
print(response.choices[0].message.content)

output

RAG improves language model responses by combining document retrieval with generation, enabling more accurate and contextually relevant answers.

When to use each

Use OpenAI when you need a broad model selection, multimodal capabilities, and a mature ecosystem with plugins and integrations. Choose Together AI when your focus is on deploying large Llama-3.3-70B models with instruction tuning at scale and potentially lower costs.

Scenario	Use OpenAI	Use Together AI
General-purpose chatbots	Yes, with gpt-4o and plugins	Possible but less ecosystem support
Large Llama model deployments	Limited to OpenAI's models	Optimized for Llama-3.3-70B instruction tuning
Multimodal tasks (images, audio)	Supported natively	Not currently supported
Cost-sensitive large-scale usage	Competitive pricing	Often more cost-effective for Llama workloads

Pricing and access

Option	Free	Paid	API access
OpenAI	Yes, limited free credits	Pay-as-you-go with detailed tiers	Official openai SDK, wide model support
Together AI	No public free tier	Competitive enterprise pricing	OpenAI-compatible SDK with base_url override

✅

Key Takeaways

OpenAI offers the most versatile AI models and ecosystem for general use.
Together AI excels in large-scale Llama-3.3-70B instruction-tuned deployments.
Both use OpenAI-compatible SDKs, enabling easy switching with minimal code changes.

Verified 2026-04 · gpt-4o, meta-llama/Llama-3.3-70B-Instruct-Turbo

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