Llama 3.3 70B

v2024-12

Meta

Modelopen-sourcemathematicsself-hostedprivacy
85
Strong
About This Model

Meta's powerful 70B parameter Llama 3.3 model offering strong performance with open-source flexibility. Excellent balance of capability and resource efficiency for self-hosted deployments.

Last Evaluated: November 8, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+

Strong mathematical reasoning (77% MATH). Good balance for self-hosted deployments.

task accuracy code

Coding benchmarks

Evidence
HumanEval Benchmark45% pass rate (estimated)
mediumVerified: 2025-11-08
task accuracy reasoning

Mathematical benchmarks

Evidence
MATH Benchmark77% on mathematical reasoning
highVerified: 2025-11-08
task accuracy general

Knowledge testing

Evidence
MMLU Benchmark50.5% on multitask understanding
highVerified: 2025-11-08
output consistency

Internal testing

Evidence
Meta Internal TestingGood consistency
mediumVerified: 2025-11-08
latency p50

Median latency

Evidence
Community benchmarking~1.4s on standard hardware
mediumVerified: 2025-11-08
latency p95

95th percentile

Evidence
mediumVerified: 2025-11-08
context window

Official specification

Evidence
Meta Documentation128K context
highVerified: 2025-11-08
uptime

Deployment-dependent

Evidence
Self-hosted modelUser-controlled uptime
mediumVerified: 2025-11-08
🛡️Security
+

Good baseline security with self-hosted control.

prompt injection resistance

Adversarial testing

Evidence
Meta Safety TestingGood baseline resistance
mediumVerified: 2025-11-08
jailbreak resistance

Safety testing

Evidence
Meta SafetyBuilt-in safety
mediumVerified: 2025-11-08
data leakage prevention

Deployment analysis

Evidence
Self-hostedFull data control
highVerified: 2025-11-08
output safety

Safety benchmarks

Evidence
Meta SafetySafety training applied
mediumVerified: 2025-11-08
api security

Deployment review

Evidence
DeploymentUser-controlled security
highVerified: 2025-11-08
🔒Privacy & Compliance
+

Exceptional privacy with self-hosted deployment.

data residency

Deployment analysis

Evidence
Open-sourceFull location control
highVerified: 2025-11-08
training data optout

Data flow analysis

Evidence
Self-hostedNo data sent to Meta
highVerified: 2025-11-08
data retention

Deployment analysis

Evidence
Self-hostedFull retention control
highVerified: 2025-11-08
pii handling

Architecture review

Evidence
Self-hostedFull PII control
highVerified: 2025-11-08
compliance certifications

Deployment options

Evidence
Self-hostedCompliance via deployment
highVerified: 2025-11-08
zero data retention

Deployment analysis

Evidence
Self-hostedComplete control
highVerified: 2025-11-08
👁️Trust & Transparency
+

Strong transparency as open-source model.

explainability

Reasoning evaluation

Evidence
Model BehaviorGood explanations
mediumVerified: 2025-11-08
hallucination rate

Community evaluation

Evidence
Community TestingModerate hallucination
mediumVerified: 2025-11-08
bias fairness

Bias benchmarks

Evidence
Meta Responsible AIBias testing applied
mediumVerified: 2025-11-08
uncertainty quantification

Qualitative assessment

Evidence
Model BehaviorGood uncertainty
mediumVerified: 2025-11-08
model card quality

Documentation review

Evidence
Meta Model CardComprehensive card
highVerified: 2025-11-08
training data transparency

Technical documentation

Evidence
Meta Technical ReportGood transparency
highVerified: 2025-11-08
guardrails

Safety system review

Evidence
Open-sourceCustomizable safety
highVerified: 2025-11-08
⚙️Operational Excellence
+

Good operational maturity with mature Llama ecosystem.

api design quality

API review

Evidence
Meta DocumentationStandard inference API
highVerified: 2025-11-08
sdk quality

SDK review

Evidence
Meta GitHubOfficial libraries
highVerified: 2025-11-08
versioning policy

Versioning review

Evidence
Meta ReleasesClear versioning
highVerified: 2025-11-08
monitoring observability

Tool review

Evidence
Community toolsDeployment-dependent
mediumVerified: 2025-11-08
support quality

Support assessment

Evidence
Community SupportActive community
mediumVerified: 2025-11-08
ecosystem maturity

Ecosystem analysis

Evidence
EcosystemMature ecosystem
highVerified: 2025-11-08
license terms

License review

Evidence
Llama LicensePermissive license
highVerified: 2025-11-08
Strengths
  • +Strong mathematical reasoning (77% MATH)
  • +Open-source with permissive licensing
  • +Complete data sovereignty via self-hosting
  • +Large 128K context window
  • +Mature Llama ecosystem and tooling
  • +Good balance of capability and efficiency
Limitations
  • !Moderate general knowledge (50.5% MMLU)
  • !Limited coding capabilities compared to larger models
  • !Requires infrastructure for deployment
  • !No managed API from Meta
  • !Deployment expertise needed
  • !Uptime depends on hosting
Metadata
pricing
input: Self-hosted (infrastructure costs)
output: Self-hosted (infrastructure costs)
notes: Open-source. Typically $0.30-1.00 per 1M tokens with optimized deployment.
context window: 128000
languages
0: English
1: Spanish
2: French
3: German
4: Italian
5: Portuguese
6: Japanese
7: Korean
8: Chinese
9: 100+ languages
modalities
0: text
api endpoint: Self-hosted
open source: true
architecture: Transformer-based
parameters: 70B

Use Case Ratings

code generation

Moderate coding capabilities. Better options for complex development.

customer support

Good for customer support with privacy benefits.

content creation

Good content creation with large context window.

data analysis

Strong mathematical reasoning (77% MATH) for analysis.

research assistant

Good for research with solid knowledge base.

legal compliance

Good for legal with data sovereignty via self-hosting.

healthcare

Good for healthcare with self-hosted HIPAA compliance.

financial analysis

Strong math capabilities for financial modeling.

education

Good for education with strong mathematical reasoning.

creative writing

Adequate creative writing capabilities.