Compare the listed model data for Llama 3.2 1B Instruct by Meta Llama and Phi-3 Mini 4K Instruct by microsoft. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
Llama 3.2 1B Instruct: 128K tokens; Phi-3 Mini 4K Instruct: 4K tokens (128K in long-context variant). Llama 3.2 1B Instruct has the larger listed context window. Llama 3.2 1B Instruct is listed for no specific capability flags; Phi-3 Mini 4K Instruct is listed for coding. Shared catalog benchmark entries: MMLU: Llama 3.2 1B Instruct 49.3%; Phi-3 Mini 4K Instruct 68.8%; HumanEval: Llama 3.2 1B Instruct 38.4%; Phi-3 Mini 4K Instruct 60.4%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
The listed context windows are 128K tokens and 4K tokens (128K in long-context variant); the larger is 32,000× the smaller.
On shared numeric benchmark entries, MMLU: Llama 3.2 1B Instruct − Phi-3 Mini 4K Instruct = -19.5 percentage points (49.3% vs 68.8%); HumanEval: Llama 3.2 1B Instruct − Phi-3 Mini 4K Instruct = -22 percentage points (38.4% vs 60.4%).
The first listed parameter quantities are 1B and 3.8B; the larger quantity is 3.8× the smaller. Total and active MoE parameters are not directly equivalent.
The catalog release dates are September 2024 and April 2024, about 5 months apart at the precision supplied.
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose Llama 3.2 1B Instruct if…
Choose Llama 3.2 1B Instruct when your task aligns with catalog-listed uses or strengths such as On-device AI in mobile apps requiring privacy, IoT AI assistants, Ultra-compact — runs on CPU, mobile, embedded hardware, 128K context at 1B scale.
Choose Phi-3 Mini 4K Instruct if…
Choose Phi-3 Mini 4K Instruct when your task aligns with catalog-listed uses or strengths such as On-device AI assistants on smartphones and laptops, Educational tools requiring lightweight fast AI, Resource-constrained enterprise deployments, Mathematical tutoring on consumer hardware.
Feature Comparison — Llama 3.2 1B Instruct vs Phi-3 Mini 4K Instruct
Catalog specifications for Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct
Specification
Llama 3.2 1B Instruct
Phi-3 Mini 4K Instruct
Provider
Meta Llama
microsoft
Parameters
1B
3.8B
Context window
128K tokens
4K tokens (128K in long-context variant)
Maximum output
Not listed
Not listed
Catalog pricing
Free — Llama 3.2 Community License
MIT — free. Azure AI charges for cloud hosting.
Listed input/output cost per 1M tokens
Separate numeric input/output rates not listed
Separate numeric input/output rates not listed
License
Llama 3.2 Community License
MIT
Coding support
Not listed
Listed
Reasoning support
Not listed
Not listed
Vision input
Not listed
Not listed
Multimodal
Not listed
Not listed
Open weights
Yes
Yes
Benchmark: MMLU
49.3%
68.8%
Benchmark: HumanEval
38.4%
60.4%
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct?
Llama 3.2 1B Instruct: 128K tokens; Phi-3 Mini 4K Instruct: 4K tokens (128K in long-context variant). Llama 3.2 1B Instruct has the larger listed context window. Llama 3.2 1B Instruct is listed for no specific capability flags; Phi-3 Mini 4K Instruct is listed for coding. Shared catalog benchmark entries: MMLU: Llama 3.2 1B Instruct 49.3%; Phi-3 Mini 4K Instruct 68.8%; HumanEval: Llama 3.2 1B Instruct 38.4%; Phi-3 Mini 4K Instruct 60.4%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct?
MMLU: Llama 3.2 1B Instruct 49.3%; Phi-3 Mini 4K Instruct 68.8%; HumanEval: Llama 3.2 1B Instruct 38.4%; Phi-3 Mini 4K Instruct 60.4%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Llama 3.2 1B Instruct: 128K tokens; Phi-3 Mini 4K Instruct: 4K tokens (128K in long-context variant). Llama 3.2 1B Instruct has the larger listed context window.
What are the listed costs per million tokens for Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct?
Llama 3.2 1B Instruct: Separate numeric input/output rates not listed (Free — Llama 3.2 Community License). Phi-3 Mini 4K Instruct: Separate numeric input/output rates not listed (MIT — free. Azure AI charges for cloud hosting.). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct?
The catalog lists Llama 3.2 1B Instruct as September 2024 and Phi-3 Mini 4K Instruct as April 2024, about 5 months apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.
Create your free LITHOVEX account and compare Llama 3.2 1B Instruct and Phi-3 Mini 4K Instruct on your actual tasks. No credit card, no API key, no subscriptions needed.