Google Cloud

Vertex AI Model Garden Complete Guide: Claude, Llama, Gemini & Imagen on GCP

2026-05-24
NicheeLab Editorial Team

Vertex AI Model Garden is Google Cloud's catalog of pre-trained models. You can use Google's own models (Gemini / Imagen / Chirp), third-party models (Anthropic Claude), and open-source models (Llama / Mistral / Gemma / DeepSeek and more, 100+ total) through a unified interface.

Model Categories

CategoryKey ModelsUse Cases
Google foundation modelsGemini 2.0 Flash / Pro / UltraGeneral-purpose LLM
Google image generationImagen 3Text → image
Google audioChirp 2 (STT), Journey (TTS)Speech processing
Google videoVeoText → video
AnthropicClaude Opus 4 / Sonnet 4 / HaikuHigh-quality chat and code
Meta (open)Llama 3.3 / 4 (70B / 405B)Self-hosted LLM
MistralMistral Large / CodestralEuropean LLM and code
Google openGemma 2 / CodeGemmaLightweight OSS LLM
DeepSeekDeepSeek R1Reasoning-focused OSS
Embeddingstext-embedding-005、text-multilingual-embedding-002RAG / search

Anthropic Claude on Vertex AI

from anthropic import AnthropicVertex

client = AnthropicVertex(region="us-east5", project_id="my-project")

message = client.messages.create(
    model="claude-opus-4@20251020",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Name 3 benefits of GCP"}],
)
print(message.content[0].text)

Open Model 1-Click Deploy

# Console: Model Garden → Llama 3.3 70B → Deploy
# Or via API
from google.cloud import aiplatform as ai

model = ai.Model.upload(
    display_name="llama-3-70b",
    artifact_uri="gs://vertex-model-garden-public/llama-3-70b",
    serving_container_image_uri="us-docker.pkg.dev/vertex-ai/prediction/text-generation-inference-cu125.0-1.ubuntu2204.py310",
)

endpoint = model.deploy(
    machine_type="g2-standard-12",
    accelerator_type="NVIDIA_L4",
    accelerator_count=1,
    min_replica_count=1,
)

prediction = endpoint.predict(instances=[{"prompt": "Hello", "max_tokens": 100}])

Fine-tuning Options

MethodTarget ModelsUse Cases
Supervised TuningGemini / LlamaUnify response style
RLHFGeminiAlignment via human evaluation
DistillationGemini Pro → FlashLightweighting large models
LoRA / AdapterOSSLightweight, cost-efficient

Pricing Comparison (2026)

ModelInput ($/M tok)Output ($/M tok)
Gemini 2.0 Flash$0.075$0.30
Gemini 2.0 Pro$1.25$5.00
Claude Haiku 4$0.80$4.00
Claude Sonnet 4$3.00$15.00
Llama 3 70B (Endpoint)g2-standard-12 ~$2/h

Imagen 3 (Image Generation)

from vertexai.preview.vision_models import ImageGenerationModel

model = ImageGenerationModel.from_pretrained("imagen-3.0-generate-002")
images = model.generate_images(
    prompt="A futuristic city at sunset, photorealistic",
    number_of_images=4,
    aspect_ratio="16:9",
)
images[0].save("output.png")

Comparison with Other Clouds

ItemModel GardenAWS BedrockAzure AI Foundry
Google modelsExcellent (Gemini / Imagen)
AnthropicExcellentExcellent
Meta LlamaExcellentExcellentGood
MistralExcellentExcellentExcellent
OpenAIExcellent (Azure OpenAI)
100+ OSS modelsExcellentGoodGood

What is Model Garden?

A catalog of pre-trained models on Vertex AI. You can use Google models (Gemini / Imagen / Chirp), third-party models (Claude / Llama / Mistral), and open models (Gemma / DeepSeek, etc.) through a unified interface.

Can I use Anthropic Claude as well?

Yes. Claude Opus 4 / Sonnet 4 / Haiku are available on Vertex AI. The interface matches Anthropic's direct API, plus you get GCP integration benefits like CMEK and VPC SC.

Are Llama / Mistral / DeepSeek available too?

Over 100 open models are selectable. With 1-click deploy, you can serve inference as a Vertex Endpoint. Fine-tuning is also supported.

What is Imagen?

Google's image generation model. Imagen 3 delivers photo-quality output. Pricing on the Vertex AI Imagen API starts at $0.04 per image.

What is Chirp?

Google's Universal Speech Model. Speech-to-Text in 100+ languages, with Chirp 2 substantially improving latency.

What is the pricing model?

Google models bill per token, third-party models follow vendor pricing, and open models bill per Endpoint instance hour (Spot instances give a 70% discount).

What fine-tuning options are available?

Supervised Tuning (Gemini / Llama), RLHF (select models), Distillation (large → small), and LoRA / Adapter (lightweight).

How does it compare to AWS Bedrock?

Bedrock offers AWS integration plus Anthropic / Meta / Mistral. Model Garden adds Google's own models (Gemini / Imagen / Chirp) and 100+ open models on top.

Related Articles: LLM / Vertex AI

Vertex AI 入門|Google Cloud 統合 ML プラットフォームの全機能 (GAIL/PMLE/PCD 必須知識)

Google Cloud Vertex AI の入門解説。Vertex AI Studio / Agent Builder / Model Garden / Search / Pipelines / Training の全機能、Gemini モデルファミリー (Pro/Flash/Ultra)、Azure OpenAI との比較、料金体系、Responsible AI 機能を日本語で整理。

Vertex AI Agent Builder 完全ガイド|Conversational Agents・Vertex AI Search・Tool Use (GCP)

Google Cloud Vertex AI Agent Builder の全機能解説。Conversational Agents (Dialogflow CX 後継)、Vertex AI Search、Tool Use、Grounding、Playbook、料金、ChatGPT GPTs / Copilot Studio 比較を網羅。

GCP Professional Machine Learning Engineer (PMLE) 完全ガイド|Vertex AI・Gemini・MLOps

Google Cloud Professional ML Engineer の 2026-06 新版試験範囲、Vertex AI / Gemini / RAG / Model Garden、AWS MLA・Azure AI-102 比較、学習ロードマップを詳解。

GCP PMLE 試験対策|Vertex AI + Gemini 生成 AI 実装パターン完全ガイド

Google Cloud Professional ML Engineer (PMLE) の Gen AI 領域を実装視点で解説。Gemini ファミリー選定、RAG パターン、Vertex AI Agent Builder、Fine-tuning、Responsible AI を網羅。

Google Cloud is a trademark of Google LLC, and Claude is a trademark of Anthropic, PBC. For the latest information, see the official Model Garden page.

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Author

NicheeLab Editorial Team

NicheeLab editorial team focused on data engineering and cloud certification learning. Content is structured around practical study needs and official exam domains.


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