OCI Generative AI Expands to Llama 3.3 70B and Command R+ — Managed LLM API at 3× Lower Cost Than AWS Bedrock

What is OCI Generative AI Service?

Oracle Cloud Infrastructure Generative AI Service is a fully managed API endpoint for large language model inference — similar to AWS Bedrock or Azure OpenAI, but hosted within OCI's infrastructure with full VCN (Virtual Cloud Network) integration. This means AI inference requests can stay entirely within your private OCI network without traversing the public internet, and OCI IAM policies control access to the models.

What Changed?

OCI Generative AI Service expanded its model catalogue to include Llama 3.3 70B (Meta's latest instruction-tuned model), Llama 3.1 405B (the largest open-source model currently available), and Cohere Command R+ (optimised for retrieval-augmented generation and enterprise document tasks). Pricing for Llama 3.3 70B: $0.00045 per 1,000 input tokens and $0.00045 per 1,000 output tokens — flat rate, no tier differentiation. Llama 3.1 405B is priced at $0.0028/1K input and $0.0028/1K output.

Why Does This Matter?

The pricing comparison is significant: Llama 3.3 70B on OCI at $0.00045/1K tokens vs AWS Bedrock Llama 3 70B at $0.00072/1K tokens — OCI is 38% cheaper for the same model. More dramatically, OCI Llama 3.3 70B at $0.00045/1K is 6× cheaper than Claude claude-sonnet-4-20250514 on Bedrock ($0.003/1K) and performs comparably on many enterprise tasks including document analysis, structured extraction, and code generation. At 1 billion tokens per month of usage: OCI = $450, AWS Bedrock Llama = $720, Claude Sonnet = $3,000.

How to Use It

OCI Generative AI uses the same API paradigm as OpenAI — JSON request/response with chat completions format. The Python SDK is straightforward: import oci, create a GenerativeAiInferenceClient, and call chat() with your messages array. For existing applications using LangChain, the OCI Generative AI integration is a single-line provider swap. The service supports streaming responses, function calling (tool use), and system prompts. Llama 3.3 70B has a 128K token context window — sufficient for processing large documents or long conversation histories.

Who Should Act Now

For OCI-native organisations already running workloads on OCI infrastructure, this is an immediate cost reduction opportunity — switch your LLM API calls from Bedrock or Azure OpenAI to OCI Generative AI and reduce inference costs by 38-85% depending on which model you were previously using. For teams not currently on OCI: the LLM cost saving alone rarely justifies a full cloud migration, but if you are evaluating OCI for compute or database workloads, the generative AI service pricing strengthens the overall business case significantly.