# Llama 3.2 1B vs Mercury 2.5

> Mercury 2.5 is the stronger model overall, scoring 33.5 to 20.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-2-1b-vs-mercury-2-5
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in coding, where Mercury 2.5 leads 39.5 to 21.1.
- Both cost about the same: $0.027 input and $0.20 output per million tokens.
- Mercury 2.5 accepts more context: 260K tokens versus 60K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 20.1 | 33.5 |
| Rank | 354 | 242 |
| Context | 60K | 260K |
| Input $/M | $0.027 | $0.04 |
| Output $/M | $0.20 | $0.15 |
| Weights | Open | Proprietary |

## Coding

- Llama 3.2 1B: 21.1 (#338)
- Mercury 2.5: 39.5 (#156)

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| SciCode | — | 38.5% |
| BigCodeBench Instruct | 8.2% | — |
| LMArena Coding | 1070 | — |
| BigCodeBench Complete | 11.3% | — |
| ALE-Bench | — | 301.65 |

## Agentic & Tool Use

- Llama 3.2 1B: 14.6 (#150)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 10.8% | — |
| BALROG | 6.6% | — |

## Reasoning

- Llama 3.2 1B: 16.2 (#308)
- Mercury 2.5: 22.4 (#193)

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1044 | — |
| Epoch Capabilities Index | 101.99 | — |

## Math

- Llama 3.2 1B: 10.4 (#313)
- Mercury 2.5: 23.3 (#272)

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | — |
| ProofBench | — | 3% |
| LMArena Math | 1086 | — |

## Knowledge

- Llama 3.2 1B: 7.2 (#312)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| GPQA Diamond | 23.9% | — |
| LMArena Expert | 1007 | — |

## Multilingual

- Llama 3.2 1B: 23.8 (#292)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 973 | — |
| LMArena Chinese | 959 | — |
| LMArena German | 1014 | — |
| LMArena Russian | 941 | — |

## Instruction Following

- Llama 3.2 1B: 52.4 (#290)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| LMArena Instruction Following | 1031 | — |

## Long Context

- Llama 3.2 1B: 31.9 (#274)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| LMArena Longer Query | 1050 | — |

## Writing & Preference

- Llama 3.2 1B: 21.3 (#310)
- Mercury 2.5: —

| Benchmark | Llama 3.2 1B | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1055 | — |
| LMArena Creative Writing | 1033 | — |
| EQ-Bench Creative Writing | 200 | — |
| LMArena Multi-Turn | 1030 | — |

## FAQ

### Is Llama 3.2 1B better than Mercury 2.5?

Mercury 2.5 is the stronger model overall, scoring 33.5 to 20.1 on the Noometry Index.

### Which is cheaper, Llama 3.2 1B or Mercury 2.5?

Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; Llama 3.2 1B lists at $0.027 and $0.20.

### Is Llama 3.2 1B or Mercury 2.5 better for coding?

Mercury 2.5 scores higher on coding benchmarks: 39.5 versus 21.1 in the Noometry coding category.

### Which has the bigger context window?

Mercury 2.5 does, with 260K tokens against 60K.

### How many benchmarks do Llama 3.2 1B and Mercury 2.5 share?

0 benchmarks have published results for both models. Llama 3.2 1B has 22 scored results on Noometry and Mercury 2.5 has 4.