Llama 4 Maverick 17B Instruct FP8 on DeepInfra

Llama 4 · AI at Meta

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Last refreshed 2026-07-09. Next refresh: weekly.

Why use Llama 4 Maverick 17B Instruct FP8 on DeepInfra?

DeepInfra offers Llama 4 Maverick 17B Instruct FP8 with pay-as-you-go pricing at $0.15/1M input tokens. DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models.

Compare Llama 4 Maverick 17B Instruct FP8 across 11 providers to find the best fit for your use case
Input / 1M
$0.15
Output / 1M
$0.60
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export DEEPINFRA_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
Model ID
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8

Request 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="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Gotchas

  • Use provider model ID "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8", not the LLMReference slug "llama-4-maverick-17b-128e-instruct-fp8".
  • 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 4 Maverick 17B Instruct FP8 Across Providers

ProviderInput (per 1M)Output (per 1M)
Microsoft Foundry$0.35$1.41
Together AI$0.27$0.85
OpenRouter$0.15$0.60
Fireworks AI——
DeepInfra$0.15$0.60
View all 11 providers →

Pricing

TypePrice (per 1M)
Input tokens$0.15
Output tokens$0.60

Capabilities

VisionMultimodalStructured Outputs

About Llama 4 Maverick 17B Instruct FP8

Meta's Llama 4 Maverick 17B with 128 experts, FP8-optimized for cost-efficient inference. Supports native Model Router integration on Microsoft Foundry.

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