Last refreshed 2026-07-09. Next refresh: weekly.
Why use Llama 4 Scout 17B-16E Instruct on GCP Vertex AI?
GCP Vertex AI offers Llama 4 Scout 17B-16E Instruct with pay-as-you-go pricing at $0.20/1M input tokens. Vertex AI is Google Cloud's managed AI platform, offering access to Gemini models and hundreds of partner models alongside tools for fine-tuning, grounding, vector search, and end-to-end MLOps pipelines.
Compare Llama 4 Scout 17B-16E Instruct across 12 providers to find the best fit for your use caseInput / 1M
$0.20
Output / 1M
$0.65
Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install google-cloud-aiplatformAuth
export GOOGLE_CLOUD_PROJECT=...Call
import os
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")Model ID
llama-4-scout-17b-16e-instructRequest example
import os
import vertexai
from vertexai.generative_models import GenerativeModel
# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("llama-4-scout-17b-16e-instruct")
response = model.generate_content("Hello")
print(response.text)Gotchas
- For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".
- The examples expect GOOGLE_CLOUD_PROJECT; rename it only if your application config maps the new variable.
Compare Llama 4 Scout 17B-16E Instruct Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Cloudflare Workers AI | $0.27 | $0.85 |
| OpenRouter | $0.08 | $0.30 |
| Together AI | — | — |
| Fireworks AI | — | — |
| DeepInfra | $0.08 | $0.30 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.65 |
Capabilities
VisionMultimodalStructured Outputs
About Llama 4 Scout 17B-16E Instruct
Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.
Model Specs
Released2025-04-05
Parameters109B (17B active)
Context10m
ArchitectureMixture of Experts
Knowledge cutoff2024-08