flagship · Apr 2025
Llama 4 Maverick
Meta’s multimodal Llama model with native image understanding.
By Meta · Text + Vision · Llama 4 Community License
Model details
Specs & substance
Spec sheet
Developed byMeta
Model familyLlama
Categoryflagship
ModalityText + Vision
Context window1M tokens
ArchitectureMoE FP8
VersionMaverick
LicenseLlama 4 Community License
Pricing$0.35 in$1.00 out · $0.17 cache
ReleasedApr 2025
Endpointparasail-llama-4-maverick-instruct-fp8
Meta’s multimodal Llama model with native image understanding.
Llama 4 Maverick is part of the Llama family by Meta, categorized as a flagship model. It supports a 1M tokens context window and is built on a MoE FP8 architecture.
Key strengths: reasoning, multimodal. Parasail serves Llama 4 Maverick on a global fleet of current-gen GPUs behind a single OpenAI-compatible endpoint — with per-token pricing, no minimums, and dedicated capacity options when you need guaranteed throughput.
Integrate
Drop-in via the OpenAI SDK
Point any OpenAI-compatible chat client at Parasail and change the model name. That's it.
pythonparasail · Llama 4 Maverick
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.parasail.io/v1"
)
response = client.chat.completions.create(
model="parasail-llama-4-maverick-instruct-fp8",
messages=[
{"role": "user", "content": "Hello, what can you do?"}
],
stream=True,
stream_options={"include_usage": True},
top_p=1,
max_tokens=1000,
temperature=1
)
for chunk in response:
if chunk.choices and chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="", flush=True)bashparasail · Llama 4 Maverick
curl https://api.parasail.io/v1/chat/completions \
-H "Authorization: Bearer $PARASAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "parasail-llama-4-maverick-instruct-fp8",
"messages": [{"role": "user", "content": "Hello, what can you do?"}],
"stream": true,
"max_tokens": 1000
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