Model comparison

MiniMax-M2.7 vs Qwen3.5-9B

MiniMax-M2.7 is the stronger model overall, scoring 37.7 to 33.8 on the Noometry Index. Qwen3.5-9B costs 4.7× less per token, which makes it the better buy when MiniMax-M2.7's lead doesn't matter for your workload.

Last verified October 10, 2026. 4 shared benchmarks.

MiniMax-M2.7

MiniMax

37.7

Rank #196 Confirmed

Qwen3.5-9B

Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

They share 4 benchmarks with published results for both. MiniMax-M2.7 scores higher in 2 categories and Qwen3.5-9B in 3 categories; 5 gaps are clear of the uncertainty.
The widest gap is in agentic & tool use, where MiniMax-M2.7 leads 25.1 to 14.5.
The biggest single-benchmark swing is Terminal-Bench: 45.1% for MiniMax-M2.7 and 9.2% for Qwen3.5-9B.
Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.30 / $1.20 for MiniMax-M2.7.
Qwen3.5-9B accepts more context: 262K tokens versus 205K.

Side by side

MiniMax-M2.7 and Qwen3.5-9B specifications
	MiniMax-M2.7	Qwen3.5-9B
Provider	MiniMax	Alibaba (Qwen)
Noometry Index	37.7	33.8
Released	2026-03-18	2026-02-23
Weights	Open	Open
Context window	205K	262K
Max output	131K	66K
Input $ / M tokens	$0.30	$0.10
Output $ / M tokens	$1.20	$0.15
Results tracked	30	10

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Category by category

Coding MiniMax-M2.7 leads

MiniMax-M2.7: 41.8 (#120), Qwen3.5-9B: 35.9 (#217)

Coding benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
SciCode	47%	27.5%
LMArena WebDev	1398	—
WeirdML	37%	—
LMArena Coding	1454	—
ALE-Bench	599.25	—

Agentic & Tool Use MiniMax-M2.7 leads

MiniMax-M2.7: 25.1 (#111), Qwen3.5-9B: 14.5 (#151)

Agentic & Tool Use benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
Terminal-Bench	45.1%	9.2%
ExploitBench	13.3%	—
GBAEval	0%	—

Reasoning Qwen3.5-9B leads

MiniMax-M2.7: 19.7 (#253), Qwen3.5-9B: 23.1 (#182)

Reasoning benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
CritPt	0.6%	0.3%
Epoch Capabilities Index	145.85	139.46
NYT Connections (extended)	24.7%	—
Chess Puzzles	—	12%
Thematic Generalization	39.3%	—
LMArena Hard Prompts	1422	—
DTBench	—	71.2%
LMCA	—	24.5%

Math Qwen3.5-9B leads

MiniMax-M2.7: 25.9 (#263), Qwen3.5-9B: 34.8 (#192)

Math benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
MathArena Final-Answer Competitions	—	48.5%
OTIS Mock AIME 2024-2025	—	61.7%
ProofBench	3%	—
LMArena Math	1420	—

Knowledge Qwen3.5-9B leads

MiniMax-M2.7: 37.7 (#152), Qwen3.5-9B: 46.0 (#84)

Knowledge benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
GPQA Diamond	—	79%
Vectara Hallucination Rate	12.9%	—
LMArena Expert	1444	—

Multilingual Not comparable

MiniMax-M2.7: 50.3 (#123), Qwen3.5-9B: —

Multilingual benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
LMArena Non-English	1382	—
LMArena Chinese	1441	—
LMArena French	1421	—
LMArena German	1398	—
LMArena Japanese	1262	—
LMArena Korean	1313	—
LMArena Russian	1383	—
LMArena Spanish	1403	—

Instruction Following Not comparable

MiniMax-M2.7: 74.1 (#103), Qwen3.5-9B: —

Instruction Following benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
LMArena Instruction Following	1405	—

Long Context Not comparable

MiniMax-M2.7: 43.3 (#99), Qwen3.5-9B: —

Long Context benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
LMArena Longer Query	1419	—

Writing & Preference Not comparable

MiniMax-M2.7: 58.9 (#112), Qwen3.5-9B: —

Writing & Preference benchmarks
Benchmark	MiniMax-M2.7	Qwen3.5-9B
LMArena Text	1405	—
LMArena Creative Writing	1354	—
LMArena Multi-Turn	1412	—

Frequently asked questions

Is MiniMax-M2.7 better than Qwen3.5-9B?

Which is cheaper, MiniMax-M2.7 or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; MiniMax-M2.7 lists at $0.30 and $1.20.

Is MiniMax-M2.7 or Qwen3.5-9B better for coding?

MiniMax-M2.7 scores higher on coding benchmarks: 41.8 versus 35.9 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 205K.

How many benchmarks do MiniMax-M2.7 and Qwen3.5-9B share?

4 benchmarks have published results for both models. MiniMax-M2.7 has 30 scored results on Noometry and Qwen3.5-9B has 10.