Llama 3.3 70B Instruct API Pricing
As of October 10, 2026, Llama 3.3 70B Instruct costs $0.12 per 1M input tokens and $0.30 per 1M output tokens from Hyperbolic, the lowest of 18 providers. It has a 131,072-token context window and returns up to 131,072 tokens per response.
- Input
- $0.12 / 1M tokens
- Output
- $0.30 / 1M tokens
- Context window
- 131,072 tokens
- Max output
- 131,072 tokens
- Providers
- 18
- Added to LiteLLM
- December 2024
Llama 3.3 70B Instruct pricing by provider
19 listings across 18 providers. Token prices are in US dollars per 1M tokens. The highlighted row is the price quoted above.
| Provider | Model name in LiteLLM | Input | Output | Batch in | Batch out | Context |
|---|---|---|---|---|---|---|
| Hyperbolic | hyperbolic/meta-llama/Llama-3.3-70B-Instruct | $0.12 | $0.30 | – | – | 128K |
| Meta Llama API | meta_llama/Llama-3.3-70B-Instruct | – | – | – | – | 128K |
| Amazon Bedrock | meta.llama3-3-70b-instruct-v1:0 | $0.72 | $0.72 | – | – | 128K |
| Azure AI Foundry | azure_ai/Llama-3.3-70B-Instruct | $0.71 | $0.71 | – | – | 128K |
| Crusoe | crusoe/meta-llama/Llama-3.3-70B-Instruct | $0.20 | $0.20 | – | – | 128K |
| DeepInfra | deepinfra/meta-llama/Llama-3.3-70B-Instruct | $0.23 | $0.40 | – | – | 128K |
| Google Vertex AI | vertex_ai/meta/llama-3.3-70b-instruct-maas | $0.72 | $0.72 | $0.36 | $0.36 | 128K |
| GradientAI | gradient_ai/llama3.3-70b-instruct | $0.65 | $0.65 | – | – | 128K |
| IBM watsonx.ai | watsonx/meta-llama/llama-3-3-70b-instruct | $0.7526 | $0.7526 | – | – | 128K |
| Nebius AI Studio | nebius/meta-llama/Llama-3.3-70B-Instruct | $0.13 | $0.40 | – | – | 128K |
| Novita AI | novita/meta-llama/llama-3.3-70b-instruct | $0.135 | $0.40 | – | – | 12K |
| Nscale | nscale/meta-llama/Llama-3.3-70B-Instruct | $0.20 | $0.20 | – | – | – |
| Oracle Cloud (OCI) | oci/meta.llama-3.3-70b-instruct | $0.72 | $0.72 | – | – | 128K |
| OVHcloud | ovhcloud/Meta-Llama-3_3-70B-Instruct | $0.67 | $0.67 | – | – | 131K |
| SambaNova | sambanova/Meta-Llama-3.3-70B-Instruct | $0.60 | $1.20 | – | – | 128K |
| Scaleway | scaleway/meta/llama-3.3-70b-instruct | $0.90 | $0.90 | – | – | 128K |
| Weights & Biases | wandb/meta-llama/Llama-3.3-70B-Instruct | $0.71 | $0.71 | – | – | 128K |
| Amazon BedrockUS cross-region | us.meta.llama3-3-70b-instruct-v1:0 | $0.72 | $0.72 | – | – | 128K |
| Lambdafp8 | lambda_ai/llama3.3-70b-instruct-fp8 | $0.12 | $0.30 | – | – | 128K |
What Llama 3.3 70B Instruct costs in practice
1,000 requests with 2,000 input and 500 output tokens each
| Hyperbolic | $0.39 |
| Nebius AI Studio | $0.46 |
| Novita AI | $0.47 |
| Crusoe | $0.50 |
100 long-document requests with 100,000 input and 2,000 output tokens each
| Hyperbolic | $1.26 |
| Nebius AI Studio | $1.38 |
| Novita AI | $1.43 |
| Crusoe | $2.04 |
Llama 3.3 70B Instruct features
- Function calling
- Parallel tool calls
- Structured output
Use Llama 3.3 70B Instruct with LiteLLM
Call Llama 3.3 70B Instruct through the LiteLLM Python SDK, or put it behind the LiteLLM proxy and send OpenAI-format requests to /v1/chat/completions. LiteLLM tracks the cost of every request at these prices.
from litellm import completion
response = completion(
model="hyperbolic/meta-llama/Llama-3.3-70B-Instruct",
messages=[{"role": "user", "content": "Hello!"}],
)model_list:
- model_name: llama-3.3-70b-instruct
litellm_params:
model: hyperbolic/meta-llama/Llama-3.3-70B-Instruct
# credentials: see the provider's LiteLLM docs pagecurl http://0.0.0.0:4000/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-1234" \
-d '{
"model": "llama-3.3-70b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'Llama 3.3 70B Instruct FAQ
How much does Llama 3.3 70B Instruct cost?
Llama 3.3 70B Instruct costs $0.12 per 1M input tokens and $0.30 per 1M output tokens from Hyperbolic, the lowest of 18 providers.
What is the context window of Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct has a 131,072-token context window and returns up to 131,072 tokens per response.
Which providers offer Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is available from 18 providers through LiteLLM: Hyperbolic, Meta Llama API, Amazon Bedrock, Azure AI Foundry, Crusoe, DeepInfra, Google Vertex AI, GradientAI, IBM watsonx.ai, Nebius AI Studio, Novita AI and Nscale and 6 more. The lowest price is on Hyperbolic.
How do I call Llama 3.3 70B Instruct with an OpenAI-compatible API?
Use the LiteLLM Python SDK with model="hyperbolic/meta-llama/Llama-3.3-70B-Instruct", or add the model to the LiteLLM proxy's config.yaml and send requests to /v1/chat/completions from any OpenAI client. LiteLLM tracks the cost of every request at the prices on this page.
What features does Llama 3.3 70B Instruct support?
Llama 3.3 70B Instruct supports function calling, parallel tool calls and structured output.
When did LiteLLM add Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct was added to LiteLLM's model price file in December 2024.
Sources
Prices come from LiteLLM's open-source model_prices_and_context_window.json, which LiteLLM uses to calculate the cost of every request. Provider pricing pages:
- ai.developer.meta.com/docs/models
- learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure
- cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing
- dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-models.html?context=wx
LiteLLM docs: Hyperbolic, Meta Llama API, Amazon Bedrock, Azure AI Foundry, Crusoe, DeepInfra.
Provider pages: Hyperbolic, Meta Llama API, Amazon Bedrock, Azure AI Foundry, Crusoe, DeepInfra, Google Vertex AI, GradientAI, IBM watsonx.ai, Nebius AI Studio, Novita AI, Nscale.
