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llama-4-maverick-17b-128e-instructMeta

from /1M in$0.20novita ai
context1.0M1.0M out
providers11 region
endpoints11 region
endpoints
1
regions
1
api
chat
released
April 2025

capabilities 0/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

endpoints

1 / 1 region
Providers serving llama-4-maverick-17b-128e-instruct, with pricing and measured performance. Best value in each column is coloured.
#flags
1Novita AIGlobal1.0M$0.20$0.85$0.20zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Sep 12

no measured traffic for this model yet. the endpoints table above carries provider pricing

benchmarks

artificial analysis

no published benchmark scores for this model

call it

model=
novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8

this model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible
main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

A lightweight and ultra-fast variant of Llama 3.3 70B, for use when quick response times are needed most.

questions 5

Which providers serve llama-4-maverick-17b-128e-instruct?
llama-4-maverick-17b-128e-instruct is available from 1 provider through Requesty: Novita AI. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does llama-4-maverick-17b-128e-instruct cost?
Pricing starts at $0.20 per million input tokens and $0.85 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is llama-4-maverick-17b-128e-instruct open weights?
Yes. llama-4-maverick-17b-128e-instruct is an open-weights model from Meta, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of llama-4-maverick-17b-128e-instruct?
llama-4-maverick-17b-128e-instruct supports up to 1.0M tokens of context, with up to 1.0M output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use llama-4-maverick-17b-128e-instruct with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.

more from meta 6

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route llama-4-maverick-17b-128e-instruct through one endpoint

One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

llama-4-maverick-17b-128e-instruct1 provider1 endpointsfrom $0.20 /1M inctx 1.0Mupdated Sep 12