Last refreshed 2026-06-15. Next refresh: weekly.
Why use SOLAR 10.7B on Together AI?
Together AI offers SOLAR 10.7B with pay-as-you-go pricing at $0.30/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Compare SOLAR 10.7B across 5 providers to find the best fit for your use caseSetup recipe
Python + curlpip install togetherexport TOGETHER_API_KEY=...from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="solar-10.7b",solar-10.7bRequest example
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="solar-10.7b",
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.
Compare SOLAR 10.7B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| NVIDIA NIM | — | — |
| Together AI | $0.30 | $0.30 |
| Upstage Console | $0.15 | $0.60 |
| Microsoft Foundry | $0.52 | $0.67 |
| Fireworks AI | $0.20 | $0.20 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $0.30 |
Capabilities
About SOLAR 10.7B
SOLAR 10.7B is a robust large language model created by Upstage AI in South Korea, featuring 10.7 billion parameters. It is tailored for high efficiency and performance through its innovative "Depth Up-Scaling" (DUS) approach, which deepens the model's layers rather than widening them, allowing for enhanced capabilities without significantly increasing computational costs. This method distinguishes it from other models that utilize more complex techniques like Mixture of Experts. By integrating pre-trained weights from the Mistral 7B model with the Llama 2 framework, SOLAR 10.7B achieves notable performance, outpacing even some models with up to 30 billion parameters.