InferX Catalog | gemma-3-1b-it

gemma-3-1b-it

a compact instruction-tuned model designed for fast and efficient general-purpose tasks

google text text2text low-latency

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google/gemma-3-1b-it is a lightweight 1B instruction-tuned model from Google’s Gemma 3 family, optimized for fast inference and low resource usage while supporting chat, reasoning, and basic coding tasks, making it ideal for edge deployments, agents, and cost-efficient production workloads.

Metadata

Provider

google

Modality

text

API type

text2text

Source

huggingface / google/gemma-3-1b-it

Created

2026-03-30 00:51:59 UTC

Updated

2026-04-13 01:07:43 UTC

Catalog version

4

Visibility

Published

Specifications

Parameters

1.00B

MoE

No

Max model length

2000

Image

vllm/vllm-openai:v0.16.0

Default Deploy Config

GPU count

1

vRAM

26000 MB

Summary

1xGPU 26000 MB

Recommended Use Cases

Chatbot
Reasoning assistant
Coding assistant

Model Spec

{
    "image": "vllm/vllm-openai:v0.16.0",
    "commands": [
        "--model",
        "google/gemma-3-1b-it",
        "--trust-remote-code",
        "--gpu-memory-utilization",
        "0.95",
        "--max-model-len",
        "2000",
        "--tensor-parallel-size=1"
    ],
    "resources": {
        "GPU": {
            "Count": 1,
            "vRam": 26000
        }
    },
    "envs": [],
    "policy": {
        "Obj": {
            "min_replica": 0,
            "max_replica": 1,
            "standby_per_node": 1,
            "parallel": 50,
            "queue_len": 100,
            "queue_timeout": 30.0,
            "scalein_timeout": 1.0,
            "scaleout_policy": {
                "WaitQueueRatio": {
                    "wait_ratio": 0.1
                }
            },
            "runtime_config": {
                "graph_sync": false
            }
        }
    },
    "sample_query": {
        "body": {
            "model": "google/gemma-3-1b-it",
            "stream": "true",
            "max_tokens": "1000",
            "temperature": "0"
        },
        "path": "v1/completions",
        "prompt": "write a quick sort algorithm.",
        "apiType": "text2text",
        "dataUrl": "",
        "prompts": [
            "Write a Python function that computes Fibonacci numbers. Explain time complexity.",
            "Translate the following Chinese text to English: \u4eca\u5929\u5929\u6c14\u5f88\u597d\u3002",
            "Explain general relativity in simple language.",
            "Write a legal contract clause about liability and indemnification.",
            "Summarize the plot of a fantasy novel involving dragons.",
            "Solve this calculus integral: \u222b x^3 log(x) dx",
            "Generate a JSON schema describing a user profile.",
            "Explain why emojis like \ud83d\ude00\ud83d\udd25\ud83d\ude80 represent byte-level tokens."
        ],
        "loadingTimeout": 90
    }
}