StripedHyena Nous 7B on Together AI

Striped Hyena · Together.ai

ServerlessOpen Source

Last refreshed 2026-06-15. Next refresh: weekly.

Why use StripedHyena Nous 7B on Together AI?

Together AI offers StripedHyena Nous 7B with pay-as-you-go pricing at $0.20/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.

Input / 1M
$0.20
Output / 1M
$0.20
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install together
Auth
export TOGETHER_API_KEY=...
Call
from together import Together
client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="stripedhyena-nous-7b",
Model ID
stripedhyena-nous-7b

Request example

from together import Together

client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="stripedhyena-nous-7b",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Gotchas

  • Together 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.
  • The examples expect TOGETHER_API_KEY; rename it only if your application config maps the new variable.

Pricing

TypePrice (per 1M)
Input tokens$0.20
Output tokens$0.20

Capabilities

Structured Outputs

About StripedHyena Nous 7B

StripedHyena-Nous-7B (SH-N 7B) is a state-of-the-art large language AI model from Together Computer, developed alongside Nous Research. Diverging from the traditional Transformer-based architecture, SH-N 7B employs a unique design integrating multi-head, grouped-query attention with gated convolutions in structured Hyena blocks. This hybrid architecture enhances its capacity for long-context processing and offers superior training efficiency and decoding speeds. The model is adept in chat applications, capable of engaging in coherent long-form dialogues, answering questions, and performing various language tasks. Despite requiring specific hardware configurations, SH-N 7B presents competitive performance comparable to leading open-source Transformer models.

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Model Specs

Released2023-12-08
Parameters7B
Context32k
ArchitectureDecoder Only

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