Gemma 2 9B — Google | Modeldex

Gemma 2 9B

Active

Open-weights 9B model from Google, competitive with much larger models.

Updated 3 days agoStructured data from Modeldex catalog

Open source

Not enough benchmark coverage yet for an Intelligence Index — needs at least 3 results across 2 categories.

Overview

Gemma 2 9B achieves competitive performance with models several times its size, making it a practical choice for resource-constrained self-hosted deployments.

History

Gemma 2 9B was released on 2024-07-31.

Training & availability

Weights are publicly available under the Gemma Terms of Use license, making this an open-weight model suitable for on-prem deployment and fine-tuning.

Capabilities

Context window: 8K tokens.
Max output: 8K tokens.
Input modalities: text.

Recommended for: open-source.

Limitations

The context window (8K tokens) is modest by 2026 standards — unsuitable for processing long documents in a single request.
Text-only — cannot process images, audio, or video inputs.

Quick start

Minimal example using the google API. Copy, paste, replace the key.

from google import genai

client = genai.Client(api_key="...")
resp = client.models.generate_content(
    model="gemma-2.9b",
    contents="Explain quantum computing in one sentence.",
)
print(resp.text)

Cost calculator

Estimate your monthly bill. Presets are typical workload sizes.

Input tokens / month5.0M

@ $0.2/1M

Output tokens / month2.0M

@ $0.2/1M

Input cost

5.0M × $0.2/1M

Output cost

$0.4

2.0M × $0.2/1M

Total / month

$1.4

$16.8 / year

Integrations & tooling support

Tool calling: Not supported
Structured outputs: Not supported

Price vs quality

Budget pricing

Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.