Noometry

Model comparison

GLM-4.6 vs MiMo-V2-Flash

GLM-4.6 and MiMo-V2-Flash score almost the same on the Noometry Index (41.4 vs 41.3), so choose on price, context window or the category you care about most.

Last verified . 21 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

MiMo-V2-Flash Xiaomi

41.3

Rank #138 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and MiMo-V2-Flash in 1 category; 4 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-4.6 leads 40.1 to 36.1.
  • The biggest single-benchmark swing is SciCode: 38.4% for GLM-4.6 and 25.9% for MiMo-V2-Flash.
  • MiMo-V2-Flash is cheaper at $0.14 / $0.28 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
  • MiMo-V2-Flash accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.6MiMo-V2-Flash
ProviderZ.ai (Zhipu)Xiaomi
Noometry Index41.441.3
Released2025-09-302025-12-16
WeightsOpenOpen
Context window205K262K
Max output131K66K
Input $ / M tokens$0.60$0.14
Output $ / M tokens$2.20$0.28
Results tracked2921

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), MiMo-V2-Flash: 36.1 (#211)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena WebDev13401330
SciCode38.4%25.9%
LMArena Coding14491443
ALE-Bench340.82737.95
SWE-bench Verified (bash only)55.4%—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), MiMo-V2-Flash: —

BenchmarkGLM-4.6MiMo-V2-Flash
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning MiMo-V2-Flash leads

GLM-4.6: 23.7 (#172), MiMo-V2-Flash: 24.9 (#157)

BenchmarkGLM-4.6MiMo-V2-Flash
CritPt1.1%0%
LMArena Hard Prompts14401420
Kagi LLM Benchmark47.4%—

Math Too close to call

GLM-4.6: 39.1 (#111), MiMo-V2-Flash: 38.3 (#139)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Math14321396
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge Too close to call

GLM-4.6: 40.2 (#124), MiMo-V2-Flash: 39.7 (#131)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Expert14311425
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), MiMo-V2-Flash: 51.0 (#113)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Non-English14261392
LMArena Chinese14991462
LMArena French14591429
LMArena German14471395
LMArena Japanese13931325
LMArena Korean14001358
LMArena Russian14191387
LMArena Spanish14361420

Instruction Following Too close to call

GLM-4.6: 74.3 (#98), MiMo-V2-Flash: 73.5 (#120)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Instruction Following14101392

Long Context Too close to call

GLM-4.6: 43.4 (#94), MiMo-V2-Flash: 43.0 (#110)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Longer Query14221409

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), MiMo-V2-Flash: 59.7 (#106)

BenchmarkGLM-4.6MiMo-V2-Flash
LMArena Text14401411
LMArena Creative Writing14111375
LMArena Multi-Turn14271404
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than MiMo-V2-Flash?

GLM-4.6 and MiMo-V2-Flash score almost the same on the Noometry Index (41.4 vs 41.3), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.6 or MiMo-V2-Flash?

MiMo-V2-Flash is cheaper. It lists at $0.14 per million input tokens and $0.28 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or MiMo-V2-Flash better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 36.1 in the Noometry coding category.

Which has the bigger context window?

MiMo-V2-Flash does, with 262K tokens against 205K.

How many benchmarks do GLM-4.6 and MiMo-V2-Flash share?

21 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and MiMo-V2-Flash has 21.

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