Model Profile

Meta-Llama-3-8B-Instruct

Name: Meta-Llama-3-8B-Instruct
Author: meta-llama

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: meta-llama/Meta-Llama-3-8B-Instruct

Author: meta-llama

Origin: huggingface_catalog

Arch: unknown

Benchmark Coverage

Scored use cases: 12

Avg confidence: 26.0%

Evidence points: 79

Raw rows: 119

Weighted rows: 13

Catalog Metadata

Parameters: unknown

Context window: 4096

Downloads: 1,394,471

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

119

Weighted Measurements

Weighted Sources

Raw Source Coverage

repoqa_leaderboard 74multilingual_mmlu_leaderboard 17duckdb_nsql_leaderboard 12llm_trustworthy_leaderboard 8icelandic_llm_leaderboard 7eq_bench 1

Weighted Source Coverage

llm_trustworthy_leaderboard 5duckdb_nsql_leaderboard 2multilingual_mmlu_leaderboard 2repoqa_leaderboard 2eq_bench 1icelandic_llm_leaderboard 1

Best Use Cases for This Model

Use Case	Vertical	Score	Confidence	Evidence	Top Contributor
Jailbreak resistance (eval) use_case.security.jailbreak_resistance_eval	risk_eval	22.9%	35.1%	7	LLM Trustworthy Leaderboard: adv
Overrefusal (eval) use_case.security.overrefusal_eval	risk_eval	22.9%	35.1%	7	LLM Trustworthy Leaderboard: adv
Crisis escalation protocol (eval) use_case.safety.crisis_escalation_protocol	risk_eval	22.9%	35.1%	7	LLM Trustworthy Leaderboard: adv
Refusal profile (eval) use_case.security.refusal_profile_eval	risk_eval	22.9%	35.1%	7	LLM Trustworthy Leaderboard: adv
Scam and social engineering resistance (eval) use_case.security.scam_social_engineering_resistance_eval	risk_eval	22.9%	35.1%	7	LLM Trustworthy Leaderboard: adv
Vulnerability-oriented code review use_case.cyber.vulnerability_review	cybersecurity	16.0%	24.2%	7	LLM Trustworthy Leaderboard: adv
Malware analysis report (defensive) use_case.cyber.malware_analysis_report	cybersecurity	12.8%	19.4%	8	LLM Trustworthy Leaderboard: adv
Debugging assistant use_case.dev.debugging	developer_tools	12.6%	20.4%	6	RepoQA Official Results: overall_average_pass_at_1_pct
Disinformation and manipulation resistance (eval) use_case.security.disinformation_resistance_eval	risk_eval	12.3%	18.8%	7	LLM Trustworthy Leaderboard: adv
Unit test generation use_case.dev.test_generation	developer_tools	11.1%	18.1%	6	RepoQA Official Results: overall_average_pass_at_1_pct
Campaign brief use_case.mkt.campaign_brief	marketing_sales	10.9%	17.7%	5	EQ-Bench Leaderboard: eq_bench_score
Product positioning and messaging use_case.mkt.product_positioning	marketing_sales	10.9%	17.7%	5	EQ-Bench Leaderboard: eq_bench_score

Deployment Fit Calculator

Model

Meta-Llama-3-8B-Instruct

meta-llama/Meta-Llama-3-8B-Instruct

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