Noometry

Model comparison

MiniMax-M2.7 vs Qwen3 14B

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 35.5 on the Noometry Index.

Last verified . 4 shared benchmarks.

MiniMax-M2.7 MiniMax

37.7

Rank #196 Confirmed

Qwen3 14B Alibaba (Qwen)

35.5

Rank #225 Confirmed

Summary

  • They share 4 benchmarks with published results for both. MiniMax-M2.7 scores higher in 3 categories and Qwen3 14B in 3 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in math, where Qwen3 14B leads 38.6 to 25.9.
  • The biggest single-benchmark swing is SciCode: 47% for MiniMax-M2.7 and 31.6% for Qwen3 14B.
  • MiniMax-M2.7 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.35 / $1.40 for Qwen3 14B.
  • MiniMax-M2.7 accepts more context: 205K tokens versus 131K.

Side by side

MiniMax-M2.7Qwen3 14B
ProviderMiniMaxAlibaba (Qwen)
Noometry Index37.735.5
Released2026-03-182025-04
WeightsOpenOpen
Context window205K131K
Max output131K8K
Input $ / M tokens$0.30$0.35
Output $ / M tokens$1.20$1.40
Results tracked3012

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Category by category

Coding MiniMax-M2.7 leads

MiniMax-M2.7: 41.8 (#120), Qwen3 14B: 37.3 (#195)

BenchmarkMiniMax-M2.7Qwen3 14B
SciCode47%31.6%
LMArena WebDev1398—
WeirdML37%—
LMArena Coding1454—
ALE-Bench599.25—

Agentic & Tool Use Qwen3 14B leads

MiniMax-M2.7: 25.1 (#111), Qwen3 14B: 29.6 (#83)

BenchmarkMiniMax-M2.7Qwen3 14B
Terminal-Bench45.1%—
Berkeley Function Calling Leaderboard—41%
ExploitBench13.3%—
GBAEval0%—

Reasoning MiniMax-M2.7 leads

MiniMax-M2.7: 19.7 (#253), Qwen3 14B: 18.5 (#280)

BenchmarkMiniMax-M2.7Qwen3 14B
CritPt0.6%0%
Epoch Capabilities Index145.85138.23
Kagi LLM Benchmark—49.1%
NYT Connections (extended)24.7%—
Chess Puzzles—4%
Thematic Generalization39.3%—
LMArena Hard Prompts1422—
DTBench—64%
LMCA—18.2%

Math Qwen3 14B leads

MiniMax-M2.7: 25.9 (#263), Qwen3 14B: 38.6 (#133)

BenchmarkMiniMax-M2.7Qwen3 14B
OTIS Mock AIME 2024-2025—66.4%
ProofBench3%—
LMArena Math1420—

Knowledge Qwen3 14B leads

MiniMax-M2.7: 37.7 (#152), Qwen3 14B: 39.3 (#134)

BenchmarkMiniMax-M2.7Qwen3 14B
Vectara Hallucination Rate12.9%5.4%
GPQA Diamond—63.8%
LMArena Expert1444—

Multilingual Not comparable

MiniMax-M2.7: 50.3 (#123), Qwen3 14B: —

BenchmarkMiniMax-M2.7Qwen3 14B
LMArena Non-English1382—
LMArena Chinese1441—
LMArena French1421—
LMArena German1398—
LMArena Japanese1262—
LMArena Korean1313—
LMArena Russian1383—
LMArena Spanish1403—

Instruction Following Not comparable

MiniMax-M2.7: 74.1 (#103), Qwen3 14B: —

BenchmarkMiniMax-M2.7Qwen3 14B
LMArena Instruction Following1405—

Long Context MiniMax-M2.7 leads

MiniMax-M2.7: 43.3 (#99), Qwen3 14B: 38.1 (#204)

BenchmarkMiniMax-M2.7Qwen3 14B
Fiction.LiveBench—62.5%
LMArena Longer Query1419—

Writing & Preference Not comparable

MiniMax-M2.7: 58.9 (#112), Qwen3 14B: —

BenchmarkMiniMax-M2.7Qwen3 14B
LMArena Text1405—
LMArena Creative Writing1354—
LMArena Multi-Turn1412—

Frequently asked questions

Is MiniMax-M2.7 better than Qwen3 14B?

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 35.5 on the Noometry Index.

Which is cheaper, MiniMax-M2.7 or Qwen3 14B?

MiniMax-M2.7 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; Qwen3 14B lists at $0.35 and $1.40.

Is MiniMax-M2.7 or Qwen3 14B better for coding?

MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 37.3 in the Noometry coding category.

Which has the bigger context window?

MiniMax-M2.7 does, with 205K tokens against 131K.

How many benchmarks do MiniMax-M2.7 and Qwen3 14B share?

4 benchmarks have published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Qwen3 14B has 12.

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