# Llama 3.2 1B vs Phi-4 Mini

> Phi-4 Mini is the stronger model overall, scoring 30.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 1.9× less per token, which makes it the better buy when Phi-4 Mini's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-2-1b-vs-phi-4-mini
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where Phi-4 Mini leads 25.3 to 7.2.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.075 / $0.30 for Phi-4 Mini.
- Phi-4 Mini accepts more context: 128K tokens versus 60K.

## Snapshot

| | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 20.1 | 30.9 |
| Rank | 354 | 283 |
| Context | 60K | 128K |
| Input $/M | $0.027 | $0.075 |
| Output $/M | $0.20 | $0.30 |
| Weights | Open | Open |

## Coding

- Llama 3.2 1B: 21.1 (#338)
- Phi-4 Mini: 28.1 (#317)

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| SciCode | — | 10.8% |
| BigCodeBench Instruct | 8.2% | — |
| LMArena Coding | 1070 | — |
| BigCodeBench Complete | 11.3% | — |

## Agentic & Tool Use

- Llama 3.2 1B: 14.6 (#150)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |

## Reasoning

- Llama 3.2 1B: 16.2 (#308)
- Phi-4 Mini: 22.4 (#195)

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1044 | — |
| Epoch Capabilities Index | 101.99 | — |

## Math

- Llama 3.2 1B: 10.4 (#313)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | — |
| LMArena Math | 1086 | — |

## Knowledge

- Llama 3.2 1B: 7.2 (#312)
- Phi-4 Mini: 25.3 (#262)

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| GPQA Diamond | 23.9% | — |
| Vectara Hallucination Rate | — | 23.5% |
| LMArena Expert | 1007 | — |

## Multilingual

- Llama 3.2 1B: 23.8 (#292)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 959 | — |
| LMArena German | 1014 | — |
| LMArena Russian | 941 | — |

## Instruction Following

- Llama 3.2 1B: 52.4 (#290)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| LMArena Instruction Following | 1031 | — |

## Long Context

- Llama 3.2 1B: 31.9 (#274)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| LMArena Longer Query | 1050 | — |

## Writing & Preference

- Llama 3.2 1B: 21.3 (#310)
- Phi-4 Mini: —

| Benchmark | Llama 3.2 1B | Phi-4 Mini |
|---|---|---|
| LMArena Text | 1055 | — |
| LMArena Creative Writing | 1033 | — |
| EQ-Bench Creative Writing | 200 | — |
| LMArena Multi-Turn | 1030 | — |

## FAQ

### Is Llama 3.2 1B better than Phi-4 Mini?

Phi-4 Mini is the stronger model overall, scoring 30.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 1.9× less per token, which makes it the better buy when Phi-4 Mini's lead doesn't matter for your workload.

### Which is cheaper, Llama 3.2 1B or Phi-4 Mini?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Phi-4 Mini lists at $0.075 and $0.30.

### Is Llama 3.2 1B or Phi-4 Mini better for coding?

Phi-4 Mini scores higher on coding benchmarks: 28.1 versus 21.1 in the Noometry coding category.

### Which has the bigger context window?

Phi-4 Mini does, with 128K tokens against 60K.

### How many benchmarks do Llama 3.2 1B and Phi-4 Mini share?

0 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Phi-4 Mini has 3.