Noometry

Model comparison

Grok-2 (Dec 2024) vs Qwen3 14B

Qwen3 14B is the stronger model overall, scoring 35.5 to 33.7 on the Noometry Index.

Last verified . 4 shared benchmarks.

Grok-2 (Dec 2024) xAI

33.7

Rank #239 Confirmed

Qwen3 14B Alibaba (Qwen)

35.5

Rank #225 Confirmed

Summary

  • They share 4 benchmarks with published results for both. Grok-2 (Dec 2024) scores higher in 1 category and Qwen3 14B in 4 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3 14B leads 38.6 to 20.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 11.5% for Grok-2 (Dec 2024) and 66.4% for Qwen3 14B.
  • Qwen3 14B has downloadable open weights; the other is API-only.

Side by side

Grok-2 (Dec 2024)Qwen3 14B
ProviderxAIAlibaba (Qwen)
Noometry Index33.735.5
Released2024-08-132025-04
WeightsProprietaryOpen
Context window—131K
Max output—8K
Input $ / M tokens—$0.35
Output $ / M tokens—$1.40
Results tracked3412

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Category by category

Coding Qwen3 14B leads

Grok-2 (Dec 2024): 33.3 (#258), Qwen3 14B: 37.3 (#195)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
SciCode—31.6%
WeirdML22.2%—
LiveBench Coding46.4%—
LMArena Coding1287—

Agentic & Tool Use Not comparable

Grok-2 (Dec 2024): —, Qwen3 14B: 29.6 (#83)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
Berkeley Function Calling Leaderboard—41%

Reasoning Qwen3 14B leads

Grok-2 (Dec 2024): 16.9 (#299), Qwen3 14B: 18.5 (#280)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
DTBench65.2%64%
Epoch Capabilities Index130.48138.23
SimpleBench22.7%—
Kagi LLM Benchmark—49.1%
CritPt—0%
Chess Puzzles—4%
LiveBench Reasoning54.8%—
LMArena Hard Prompts1272—
LiveBench Data Analysis54.5%—
LMCA—18.2%
LiveBench54.3%—

Math Qwen3 14B leads

Grok-2 (Dec 2024): 20.8 (#284), Qwen3 14B: 38.6 (#133)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
OTIS Mock AIME 2024-202511.5%66.4%
LiveBench Math54.9%—
LMArena Math1283—
MATH Level 563.5%—
FrontierMath (Feb 2025 set)0.7%—

Knowledge Qwen3 14B leads

Grok-2 (Dec 2024): 29.8 (#233), Qwen3 14B: 39.3 (#134)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
GPQA Diamond53.8%63.8%
Confabulations20.1%—
Vectara Hallucination Rate—5.4%
LMArena Expert1254—

Multilingual Not comparable

Grok-2 (Dec 2024): 43.1 (#188), Qwen3 14B: —

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
LMArena Non-English1282—
LMArena Chinese1289—
LMArena French1318—
LMArena German1287—
LMArena Japanese1244—
LMArena Korean1237—
LMArena Russian1286—
LMArena Spanish1281—

Instruction Following Not comparable

Grok-2 (Dec 2024): 66.9 (#202), Qwen3 14B: —

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
LiveBench Instruction Following69.6%—
LMArena Instruction Following1270—

Long Context Too close to call

Grok-2 (Dec 2024): 38.8 (#190), Qwen3 14B: 38.1 (#204)

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
Fiction.LiveBench—62.5%
LMArena Longer Query1276—

Writing & Preference Not comparable

Grok-2 (Dec 2024): 48.6 (#198), Qwen3 14B: —

BenchmarkGrok-2 (Dec 2024)Qwen3 14B
LMArena Text1305—
LMArena Creative Writing1284—
Short-Story Creative Writing63.6%—
LMArena Multi-Turn1290—
LiveBench Language45.6%—

Frequently asked questions

Is Grok-2 (Dec 2024) better than Qwen3 14B?

Qwen3 14B is the stronger model overall, scoring 35.5 to 33.7 on the Noometry Index.

Is Grok-2 (Dec 2024) or Qwen3 14B better for coding?

Qwen3 14B scores higher on coding benchmarks: 37.3 versus 33.3 in the Noometry coding category.

How many benchmarks do Grok-2 (Dec 2024) and Qwen3 14B share?

4 benchmarks have published results for both models. Grok-2 (Dec 2024) has 34 scored results on Noometry and Qwen3 14B has 12.

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