# Grok 4.5 vs Qwen3 14B

> Grok 4.5 is the stronger model overall, scoring 55.0 to 35.0 on the Noometry Index. Qwen3 14B costs 4.9× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/grok-4-5-vs-qwen3-14b
- Last updated: 2026-10-10
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. Grok 4.5 scores higher in 6 categories and Qwen3 14B in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.5 leads 56.0 to 18.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 83.5% for Grok 4.5 and 49.1% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $2 / $6 for Grok 4.5.
- Grok 4.5 accepts more context: 500K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.5 | Qwen3 14B |
|---|---|---|
| Provider | xAI | Alibaba (Qwen) |
| Noometry Index | 55.0 | 35.0 |
| Rank | 22 | 222 |
| Context | 500K | 131K |
| Input $/M | $2 | $0.35 |
| Output $/M | $6 | $1.40 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.5: 51.7 (#34)
- Qwen3 14B: 36.7 (#191)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| SciCode | 54.1% | 31.6% |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.4% | — |
| LMArena WebDev | 1552 | — |
| WeirdML | 46.4% | — |
| LMArena Coding | 1473 | — |
| ALE-Bench | 1,309 | — |

## Agentic & Tool Use

- Grok 4.5: 44.4 (#15)
- Qwen3 14B: 29.4 (#78)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| APEX-Agents | 56.2% | — |
| Berkeley Function Calling Leaderboard | — | 41% |
| τ²-bench Banking | 47.9% | — |
| PostTrainBench | 23.4% | — |
| GBAEval | 65.4% | — |
| GDP.pdf | 14% | — |
| LMArena Search | 1213 | — |
| Vending-Bench 2 | 3,887 | — |

## Reasoning

- Grok 4.5: 56.0 (#23)
- Qwen3 14B: 18.1 (#272)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 83.5% | 49.1% |
| CritPt | 15.4% | 0% |
| Chess Puzzles | 36% | 4% |
| DTBench | 96.5% | 64% |
| LMCA | 45.2% | 18.2% |
| Epoch Capabilities Index | 154.02 | 138.23 |
| ARC-AGI-2 | 52.6% | — |
| SimpleBench | 70% | — |
| NYT Connections (extended) | 79.9% | — |
| ARC-AGI-1 | 87.2% | — |
| LMArena Hard Prompts | 1462 | — |
| Surface Evolver Bench | 74.4% | — |

## Math

- Grok 4.5: 60.7 (#29)
- Qwen3 14B: 37.0 (#102)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 97.8% | 66.4% |
| FrontierMath (Tiers 1-3) | 57.2% | — |
| FrontierMath Tier 4 | 24.4% | — |
| ProofBench | 31% | — |
| LMArena Math | 1457 | — |

## Knowledge

- Grok 4.5: 62.3 (#21)
- Qwen3 14B: 39.2 (#124)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 93.4% | 63.8% |
| SimpleQA Verified | 48.3% | — |
| Vectara Hallucination Rate | — | 5.4% |
| LMArena Expert | 1466 | — |

## Multimodal

- Grok 4.5: 37.8 (#63)
- Qwen3 14B: —

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1287 | — |
| Blueprint-Bench 2 | 27.3% | — |
| Furniture Assembly | 22.5% | — |
| LMArena Document | 1452 | — |

## Multilingual

- Grok 4.5: 54.5 (#43)
- Qwen3 14B: —

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1439 | — |
| LMArena Chinese | 1497 | — |
| LMArena French | 1458 | — |
| LMArena German | 1448 | — |
| LMArena Japanese | 1425 | — |
| LMArena Korean | 1402 | — |
| LMArena Russian | 1447 | — |
| LMArena Spanish | 1452 | — |

## Instruction Following

- Grok 4.5: 76.3 (#45)
- Qwen3 14B: —

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1446 | — |

## Long Context

- Grok 4.5: 44.8 (#54)
- Qwen3 14B: 38.0 (#201)

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1463 | — |

## Writing & Preference

- Grok 4.5: 65.9 (#40)
- Qwen3 14B: —

| Benchmark | Grok 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1448 | — |
| LMArena Creative Writing | 1442 | — |
| EQ-Bench Creative Writing | 1579 | — |
| LMArena Multi-Turn | 1457 | — |

## FAQ

### Is Grok 4.5 better than Qwen3 14B?

Grok 4.5 is the stronger model overall, scoring 55.0 to 35.0 on the Noometry Index. Qwen3 14B costs 4.9× less per token, which makes it the better buy when Grok 4.5's lead doesn't matter for your workload.

### Which is cheaper, Grok 4.5 or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Grok 4.5 lists at $2 and $6.

### Is Grok 4.5 or Qwen3 14B better for coding?

Grok 4.5 scores higher on coding benchmarks: 51.7 versus 36.7 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.5 does, with 500K tokens against 131K.

### How many benchmarks do Grok 4.5 and Qwen3 14B share?

9 benchmarks have published results for both models. Grok 4.5 has 52 scored results on Noometry and Qwen3 14B has 12.