Noometry

Model comparison

MiMo-V2-Pro vs Qwen3.5-9B

MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 33.3 on the Noometry Index. Qwen3.5-9B costs 4.8× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

MiMo-V2-Pro Xiaomi

42.4

Rank #102 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.3

Rank #235 Confirmed

Summary

  • The widest gap is in coding, where MiMo-V2-Pro leads 43.4 to 35.3.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.43 / $0.87 for MiMo-V2-Pro.
  • MiMo-V2-Pro accepts more context: 1.05M tokens versus 262K.
  • Qwen3.5-9B has downloadable open weights; the other is API-only.

Side by side

MiMo-V2-ProQwen3.5-9B
ProviderXiaomiAlibaba (Qwen)
Noometry Index42.433.3
Released2026-03-182026-02-23
WeightsProprietaryOpen
Context window1.05M262K
Max output131K66K
Input $ / M tokens$0.43$0.10
Output $ / M tokens$0.87$0.15
Results tracked2310

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Category by category

Coding MiMo-V2-Pro leads

MiMo-V2-Pro: 43.4 (#76), Qwen3.5-9B: 35.3 (#213)

BenchmarkMiMo-V2-ProQwen3.5-9B
LMArena WebDev1433—
SciCode—27.5%
LMArena Coding1476—
ALE-Bench785.17—

Agentic & Tool Use Not comparable

MiMo-V2-Pro: —, Qwen3.5-9B: 14.4 (#143)

BenchmarkMiMo-V2-ProQwen3.5-9B
Terminal-Bench—9.2%

Reasoning Qwen3.5-9B leads

MiMo-V2-Pro: 21.3 (#200), Qwen3.5-9B: 22.5 (#178)

BenchmarkMiMo-V2-ProQwen3.5-9B
NYT Connections (extended)25.8%—
CritPt—0.3%
Chess Puzzles—12%
Thematic Generalization45.9%—
LMArena Hard Prompts1457—
DTBench—71.2%
LMCA—24.5%
Epoch Capabilities Index—139.45

Math MiMo-V2-Pro leads

MiMo-V2-Pro: 36.7 (#104), Qwen3.5-9B: 33.5 (#174)

BenchmarkMiMo-V2-ProQwen3.5-9B
MathArena Final-Answer Competitions—48.5%
OTIS Mock AIME 2024-2025—61.7%
LMArena Math1447—

Knowledge Qwen3.5-9B leads

MiMo-V2-Pro: 40.8 (#106), Qwen3.5-9B: 46.0 (#77)

BenchmarkMiMo-V2-ProQwen3.5-9B
GPQA Diamond—79%
LMArena Expert1479—

Multilingual Not comparable

MiMo-V2-Pro: 52.9 (#77), Qwen3.5-9B: —

BenchmarkMiMo-V2-ProQwen3.5-9B
LMArena Non-English1416—
LMArena Chinese1455—
LMArena French1470—
LMArena German1417—
LMArena Japanese1366—
LMArena Korean1401—
LMArena Russian1427—
LMArena Spanish1458—

Instruction Following Not comparable

MiMo-V2-Pro: 76.2 (#46), Qwen3.5-9B: —

BenchmarkMiMo-V2-ProQwen3.5-9B
LMArena Instruction Following1444—

Long Context Not comparable

MiMo-V2-Pro: 41.5 (#133), Qwen3.5-9B: —

BenchmarkMiMo-V2-ProQwen3.5-9B
CL-bench15.7%—
CL-bench Life6.9%—
LMArena Longer Query1455—

Writing & Preference Not comparable

MiMo-V2-Pro: 62.9 (#67), Qwen3.5-9B: —

BenchmarkMiMo-V2-ProQwen3.5-9B
LMArena Text1436—
LMArena Creative Writing1415—
LMArena Multi-Turn1456—

Frequently asked questions

Is MiMo-V2-Pro better than Qwen3.5-9B?

MiMo-V2-Pro is the stronger model overall, scoring 42.4 to 33.3 on the Noometry Index. Qwen3.5-9B costs 4.8× less per token, which makes it the better buy when MiMo-V2-Pro's lead doesn't matter for your workload.

Which is cheaper, MiMo-V2-Pro 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; MiMo-V2-Pro lists at $0.43 and $0.87.

Is MiMo-V2-Pro or Qwen3.5-9B better for coding?

MiMo-V2-Pro scores higher on coding benchmarks: 43.4 versus 35.3 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Pro does, with 1.05M tokens against 262K.

How many benchmarks do MiMo-V2-Pro and Qwen3.5-9B share?

0 benchmarks have published results for both models. MiMo-V2-Pro has 23 scored results on Noometry and Qwen3.5-9B has 10.

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