Last refreshed 2026-07-09. Next refresh: weekly.
Why use CodeLlama 70B on Together AI?
Together AI offers CodeLlama 70B with pay-as-you-go pricing at $0.90/1M 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 CodeLlama 70B across 6 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="codellama-70b",codellama-70bRequest example
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="codellama-70b",
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 CodeLlama 70B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Together AI | $0.90 | $0.90 |
| NVIDIA NIM | — | — |
| DeepInfra | $0.45 | $0.65 |
| Fireworks AI | $0.90 | $0.90 |
| Microsoft Foundry | $3.78 | $11.34 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
About CodeLlama 70B
CodeLlama 70B is a state-of-the-art generative text model by Meta, specifically designed for code synthesis and understanding. It utilizes an auto-regressive transformer architecture and has been fine-tuned with up to 16,000 tokens, supporting inference with up to 100,000 tokens. The model excels in code completion, infilling, and instruction following, making it versatile for various programming languages and applications. With 70 billion parameters, it offers advanced capabilities for general code generation tasks, while also providing specialized variants for Python and instruction-following.