# Inkling vs Llama 3.2 3B

> Inkling is the stronger model overall, scoring 44.1 to 28.9 on the Noometry Index. Llama 3.2 3B costs 21× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/inkling-vs-llama-3-2-3b
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. Inkling scores higher in 8 categories and Llama 3.2 3B in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Inkling leads 65.2 to 24.7.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Llama 3.2 3B accepts more context: 131K tokens versus 66K.

## Snapshot

| | Inkling | Llama 3.2 3B |
|---|---|---|
| Provider | Thinking Machines Lab | Meta |
| Noometry Index | 44.1 | 28.9 |
| Rank | 80 | 321 |
| Context | 66K | 131K |
| Input $/M | $1.87 | $0.05 |
| Output $/M | $4.68 | $0.33 |
| Weights | Open | Open |

## Coding

- Inkling: 34.5 (#234)
- Llama 3.2 3B: 27.6 (#319)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1464 | 1098 |
| FrontierCode | 14% | — |
| LMArena WebDev | 1413 | — |
| FrontierSWE | 4.1% | — |
| SciCode | 47% | — |
| WeirdML | 32.3% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 946 | — |

## Agentic & Tool Use

- Inkling: 29.6 (#85)
- Llama 3.2 3B: 20.1 (#143)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| APEX-Agents | 33.8% | — |
| Berkeley Function Calling Leaderboard | — | 21.9% |
| τ²-bench Banking | 25% | — |
| BALROG | — | 10.1% |

## Reasoning

- Inkling: 40.4 (#56)
- Llama 3.2 3B: 21.0 (#228)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1095 |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| ARC-AGI-1 | 79.5% | — |
| CritPt | 5.4% | — |
| Chess Puzzles | 21% | — |
| DTBench | 87.5% | — |
| LMCA | 37.6% | — |
| Epoch Capabilities Index | 148.54 | — |

## Math

- Inkling: 31.3 (#225)
- Llama 3.2 3B: 32.4 (#214)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1479 | 1126 |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| FrontierMath Tier 4 | 4.9% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| ProofBench | 0% | — |

## Knowledge

- Inkling: 55.1 (#49)
- Llama 3.2 3B: 29.7 (#235)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1465 | 1090 |
| GPQA Diamond | 88.3% | — |
| SimpleQA Verified | 40.3% | — |

## Multilingual

- Inkling: 54.0 (#52)
- Llama 3.2 3B: 26.2 (#281)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1434 | 1019 |
| LMArena Chinese | 1490 | 1017 |
| LMArena German | 1446 | 1056 |
| LMArena Russian | 1429 | 949 |
| LMArena French | 1458 | — |
| LMArena Japanese | 1429 | — |
| LMArena Korean | 1404 | — |
| LMArena Spanish | 1448 | — |

## Instruction Following

- Inkling: 75.1 (#71)
- Llama 3.2 3B: 56.0 (#275)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1426 | 1089 |

## Long Context

- Inkling: 43.8 (#86)
- Llama 3.2 3B: 33.4 (#261)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1434 | 1100 |

## Writing & Preference

- Inkling: 65.2 (#51)
- Llama 3.2 3B: 24.7 (#307)

| Benchmark | Inkling | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1441 | 1110 |
| LMArena Creative Writing | 1387 | 1094 |
| EQ-Bench Creative Writing | 1611 | 595 |
| LMArena Multi-Turn | 1436 | 1105 |
| EQ-Bench 4 | 1226 | — |

## FAQ

### Is Inkling better than Llama 3.2 3B?

Inkling is the stronger model overall, scoring 44.1 to 28.9 on the Noometry Index. Llama 3.2 3B costs 21× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

### Which is cheaper, Inkling or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Llama 3.2 3B better for coding?

Inkling scores higher on coding benchmarks: 34.5 versus 27.6 in the Noometry coding category.

### Which has the bigger context window?

Llama 3.2 3B does, with 131K tokens against 66K.

### How many benchmarks do Inkling and Llama 3.2 3B share?

14 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Llama 3.2 3B has 18.