# Inkling vs Qwen3 14B

> Inkling is the stronger model overall, scoring 44.1 to 35.5 on the Noometry Index. Qwen3 14B costs 4.2× 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-qwen3-14b
- Last updated: 2026-10-10
- Shared benchmarks: 8

## Summary

- They share 8 benchmarks with published results for both. Inkling scores higher in 3 categories and Qwen3 14B in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Inkling leads 40.4 to 18.5.
- The biggest single-benchmark swing is GPQA Diamond: 88.3% for Inkling and 63.8% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1.87 / $4.68 for Inkling.
- Qwen3 14B accepts more context: 131K tokens versus 66K.

## Snapshot

| | Inkling | Qwen3 14B |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 44.1 | 35.5 |
| Rank | 80 | 225 |
| Context | 66K | 131K |
| Input $/M | $1.87 | $0.35 |
| Output $/M | $4.68 | $1.40 |
| Weights | Open | Open |

## Coding

- Inkling: 34.5 (#234)
- Qwen3 14B: 37.3 (#195)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| SciCode | 47% | 31.6% |
| FrontierCode | 14% | — |
| LMArena WebDev | 1413 | — |
| FrontierSWE | 4.1% | — |
| WeirdML | 32.3% | — |
| LMArena Coding | 1464 | — |
| ALE-Bench | 946 | — |

## Agentic & Tool Use

- Inkling: 29.6 (#85)
- Qwen3 14B: 29.6 (#83)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| APEX-Agents | 33.8% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
| τ²-bench Banking | 25% | — |

## Reasoning

- Inkling: 40.4 (#56)
- Qwen3 14B: 18.5 (#280)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| CritPt | 5.4% | 0% |
| Chess Puzzles | 21% | 4% |
| DTBench | 87.5% | 64% |
| LMCA | 37.6% | 18.2% |
| Epoch Capabilities Index | 148.54 | 138.23 |
| ARC-AGI-2 | 36.5% | — |
| SimpleBench | 50% | — |
| Kagi LLM Benchmark | — | 49.1% |
| ARC-AGI-1 | 79.5% | — |
| LMArena Hard Prompts | 1451 | — |

## Math

- Inkling: 31.3 (#225)
- Qwen3 14B: 38.6 (#133)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 66.4% |
| FrontierMath (Tiers 1-3) | 33.3% | — |
| FrontierMath Tier 4 | 4.9% | — |
| ProofBench | 0% | — |
| LMArena Math | 1479 | — |

## Knowledge

- Inkling: 55.1 (#49)
- Qwen3 14B: 39.3 (#134)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 88.3% | 63.8% |
| SimpleQA Verified | 40.3% | — |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1465 | — |

## Multilingual

- Inkling: 54.0 (#52)
- Qwen3 14B: —

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1434 | — |
| LMArena Chinese | 1490 | — |
| LMArena French | 1458 | — |
| LMArena German | 1446 | — |
| LMArena Japanese | 1429 | — |
| LMArena Korean | 1404 | — |
| LMArena Russian | 1429 | — |
| LMArena Spanish | 1448 | — |

## Instruction Following

- Inkling: 75.1 (#71)
- Qwen3 14B: —

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1426 | — |

## Long Context

- Inkling: 43.8 (#86)
- Qwen3 14B: 38.1 (#204)

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1434 | — |

## Writing & Preference

- Inkling: 65.2 (#51)
- Qwen3 14B: —

| Benchmark | Inkling | Qwen3 14B |
|---|---|---|
| LMArena Text | 1441 | — |
| LMArena Creative Writing | 1387 | — |
| EQ-Bench Creative Writing | 1611 | — |
| EQ-Bench 4 | 1226 | — |
| LMArena Multi-Turn | 1436 | — |

## FAQ

### Is Inkling better than Qwen3 14B?

Inkling is the stronger model overall, scoring 44.1 to 35.5 on the Noometry Index. Qwen3 14B costs 4.2× less per token, which makes it the better buy when Inkling's lead doesn't matter for your workload.

### Which is cheaper, Inkling or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Inkling lists at $1.87 and $4.68.

### Is Inkling or Qwen3 14B better for coding?

Qwen3 14B scores higher on coding benchmarks: 37.3 versus 34.5 in the Noometry coding category.

### Which has the bigger context window?

Qwen3 14B does, with 131K tokens against 66K.

### How many benchmarks do Inkling and Qwen3 14B share?

8 benchmarks have published results for both models. Inkling has 41 scored results on Noometry and Qwen3 14B has 12.