Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 2 13B Chat on DeepInfra?
DeepInfra offers Llama 2 13B Chat with pay-as-you-go pricing at $0.13/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.
Compare Llama 2 13B Chat across 11 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport DEEPINFRA_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],llama2-13b-chatRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],
base_url="https://api.deepinfra.com/v1/openai"
)
response = client.chat.completions.create(
model="llama2-13b-chat",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- DeepInfra uses "organization/model-name" format, e.g. "meta-llama/Meta-Llama-3-8B-Instruct" or "mistralai/Mistral-7B-Instruct-v0.3". See the DeepInfra model catalog for exact IDs.
- The examples expect DEEPINFRA_API_KEY; rename it only if your application config maps the new variable.
Compare Llama 2 13B Chat Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Alibaba Cloud PAI-EAS | — | — |
| AWS Bedrock | $0.75 | $1.00 |
| Microsoft Foundry | $0.81 | $0.94 |
| GCP Vertex AI | $0.16 | $0.48 |
| DeepInfra | $0.13 | $0.13 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.13 |
| Output tokens | $0.13 |
Capabilities
About Llama 2 13B Chat
The Llama 2 13B Chat model is a 13 billion parameter generative text model developed by Meta, optimized for conversational applications. Released on July 18, 2023, it's part of the Llama 2 family and excels in dialogue scenarios. The model leverages supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to generate coherent and contextually relevant responses. Trained on 2 trillion tokens from diverse public sources, it outperforms many open-source chat models and matches popular closed-source models in helpfulness and safety. This model is ideal for AI engineers working on chatbots, virtual assistants, and customer service automation.