Using OLMo 7B on Together AI
Implementation guide · OLMo · Allen Institute for Artificial Intelligence (AI2)
Together AI exposes OLMo 7B through model ID olmo-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
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Code Examples
pip install togetherTOGETHER_API_KEYolmo-7bTogether uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="olmo-7b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Together AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About OLMo 7B
OLMo 7B is a large language model created by the Allen Institute for Artificial Intelligence (AI2), characterized by its open-source nature where model weights, training data, code, and evaluation tools have been publicly released. It utilizes a decoder-only transformer architecture, featuring 32 layers, a hidden size of 4096, and 32 attention heads, among other features. Trained on 2.5 trillion tokens from the Dolma dataset, this model excels in text generation, question answering, and language understanding, with performance metrics often comparable to or exceeding those of similar-sized models.