Model Profile

gemma-2b-it

Name: gemma-2b-it
Author: google

4,096 ctxOpen weights

Use this page to decide where this model is a strong fit. Rankings below are benchmark-backed by use case, with explicit confidence and contributor metrics.

Identity

ID: google/gemma-2b-it

Author: google

Origin: huggingface_catalog

Arch: unknown

Benchmark Coverage

Scored use cases: 12

Avg confidence: 23.6%

Evidence points: 55

Raw rows: 12

Weighted rows: 7

Catalog Metadata

Parameters: unknown

Context window: 4096

Downloads: 75,098

Some fit rows have limited benchmark evidence.

7 of 12 scored use cases have low confidence or thin contributor coverage.

Coverage Diagnostics

actively scored

Use-Case Scores

Total Measurements

Weighted Measurements

Weighted Sources

Raw Source Coverage

llm_trustworthy_leaderboard 8artificialanalysis_creative_writing_official 3eq_bench 1

Weighted Source Coverage

llm_trustworthy_leaderboard 5artificialanalysis_creative_writing_official 1eq_bench 1

Best Use Cases for This Model

Use Case	Vertical	Score	Confidence	Evidence	Top Contributor
Overrefusal (eval) use_case.security.overrefusal_eval	risk_eval	21.4%	32.8%	5	LLM Trustworthy Leaderboard: fairness
Jailbreak resistance (eval) use_case.security.jailbreak_resistance_eval	risk_eval	21.4%	32.8%	5	LLM Trustworthy Leaderboard: fairness
Crisis escalation protocol (eval) use_case.safety.crisis_escalation_protocol	risk_eval	21.4%	32.8%	5	LLM Trustworthy Leaderboard: fairness
Scam and social engineering resistance (eval) use_case.security.scam_social_engineering_resistance_eval	risk_eval	21.4%	32.8%	5	LLM Trustworthy Leaderboard: fairness
Refusal profile (eval) use_case.security.refusal_profile_eval	risk_eval	21.4%	32.8%	5	LLM Trustworthy Leaderboard: fairness
Vulnerability-oriented code review use_case.cyber.vulnerability_review	cybersecurity	12.2%	18.7%	5	LLM Trustworthy Leaderboard: fairness
Disinformation and manipulation resistance (eval) use_case.security.disinformation_resistance_eval	risk_eval	11.5%	17.6%	5	LLM Trustworthy Leaderboard: fairness
Personalized sales outreach use_case.mkt.sales_outreach_personalized	marketing_sales	9.6%	20.8%	4	LLM Trustworthy Leaderboard: fairness
Ad copy variants use_case.mkt.ad_copy_variants	marketing_sales	9.6%	20.8%	4	LLM Trustworthy Leaderboard: fairness
Config debugging use_case.sre.config_debugging	devops_sre	9.0%	13.7%	4	LLM Trustworthy Leaderboard: fairness
Terraform generation use_case.sre.iac_terraform	devops_sre	9.0%	13.7%	4	LLM Trustworthy Leaderboard: fairness
Kubernetes manifest generation use_case.sre.iac_k8s	devops_sre	9.0%	13.7%	4	LLM Trustworthy Leaderboard: fairness

Deployment Fit Calculator

Model

gemma-2b-it

google/gemma-2b-it

Hardware

Quantization: 4-bit

2-bit8-bit

Insufficient

Unknown parameter count. Cannot estimate deployment fit.

Required VRAM

~0.0GB

Est. Throughput

0.00 tok/s

Deployment Fit Matrix

GPU	4-bit	6-bit	8-bit
RTX 3060 12GB	Insufficient	Insufficient	Insufficient
RTX 3090 24GB	Insufficient	Insufficient	Insufficient
RTX 4090 24GB	Insufficient	Insufficient	Insufficient
Mac Studio M2 Ultra 192GB	Insufficient	Insufficient	Insufficient