Toolbit.aiToolbit.ai

Find, compare, and explore the best AI tools to match your specific tasks and use cases.

Explore

  • AI Search
  • Compare ToolsNew
  • Browse Categories
  • Trending Tools
  • Most Popular
  • New Additions

Resources

  • Updates HubNew
  • AI News
  • ModelsNew
  • Blog Articles
  • NewsletterNew

Company

  • Launch a Tool
  • Advertise with Us
  • Guest Post
  • Contact Us
© 2026 Toolbit.ai. All rights reserved.
Privacy PolicyTerms & ConditionsDisclaimer
There's An AI For That favicon
There's An AI For That•The front page of AI for everyone
Toolbit.ai
Toolbit.ai
UpdatesNew
Blog
Toolbit.ai
Toolbit.ai
Toolbit.ai
Toolbit.ai
UpdatesNew
Blog
Sign in
  1. Home
  2. Updates
  3. Models
  4. Llama 3.2 1B Instruct
Meta
Released September 25, 2024Cutoff December 2023

Llama 3.2 1B Instruct

Meta's Llama 3.2 1B Instruct is a 1B-parameter open model built via pruning and knowledge distillation, designed for mobile/edge deployment and agentic retrieval tasks.

Visit MetaAnnouncement
Inputs
Text
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Llama 3.2 1B Instruct - On-Device Instruction-Tuned Model

Llama 3.2 1B Instruct is Meta's smallest open-weight text model, purpose-built for deployment in highly constrained environments such as mobile devices and edge hardware. It is the product of a documented pruning-then-distillation pipeline rather than training at this scale from scratch.

Deployment Target

Officially scoped to highly constrained environments, including mobile devices. Meta explicitly documents that 1B-scale systems carry a different alignment profile and safety/helpfulness tradeoff than larger systems, and recommends pairing the model with Llama Guard 3-1B or its mobile-optimized variant as a lightweight safeguard.

Intended Use Cases

Documented applications include assistant-like chat, agentic retrieval and summarization, mobile AI writing assistants, and query/prompt rewriting — use cases specifically suited to on-device inference constraints.

Safety Design

Meta conducted recurring red-teaming exercises and built dedicated adversarial evaluation datasets for this size class, recognizing that constrained-environment deployment requires tailored safety evaluation rather than direct application of larger-model safeguards.

Benchmark Performance

Independent evaluations · Artificial Analysis

1.0%
Intelligence

Accuracy & Capability Details

GPQA - Graduate Science19.6%
Humanity's Last Exam5.5%
SciCode - Scientific Coding1.7%
Instruction Following22.8%
Long Context Reasoning6.0%
τ²-Bench - Agentic Tasks0.0%
TerminalBench - System Control0.0%
Specs
Context window
131Ktokens
Input pricing
$0.05per 1M tokens
Output pricing
$0.05per 1M tokens

Prices in USD.

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderMetaAnthropicAnthropic
Release DateSeptember 25, 2024July 24, 2026June 9, 2026
Knowledge CutoffDec 2023May 2026-
Context & Limits
Context Window131K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.05
Best Input Pricing
$5$10
Output Pricing
$0.05
Best Output Pricing
$25$50
Modalities
Inputs
text
textimage
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index1.0
63.1
Best Intelligence Index
62.1
Coding Index-
78.0
Best Coding Index
76.5
Agentic Index-
59.2
Best Agentic Index
56.6
Llama 3.2 1B Instruct
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

20%
Llama 3.2 1B Instruct
GPQA Benchmark
Score: 20%
Llama 3.2 1B Instruct
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

6%
Llama 3.2 1B Instruct
Humanity's Last Exam
Score: 6%
Llama 3.2 1B Instruct
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

6%
Llama 3.2 1B Instruct
Long Context Reasoning
Score: 6%
Llama 3.2 1B Instruct
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

Back to all models