Noometry

Model comparison

Devstral 2 vs GLM-5.2

GLM-5.2 has enough public results to be ranked (#44); Devstral 2 does not yet, so treat this comparison as directional.

Last verified . 1 shared benchmarks.

Devstral 2 Mistral AI

36.1

Unranked Sparse

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Summary

  • They share 1 benchmark with published results for both. Devstral 2 scores higher in 0 categories and GLM-5.2 in 1 category; one gap is clear of the uncertainty.
  • The widest gap is in coding, where GLM-5.2 leads 51.3 to 33.2.
  • Devstral 2 is cheaper at $0.40 / $2 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
  • GLM-5.2 accepts more context: 1M tokens versus 262K.

Side by side

Devstral 2GLM-5.2
ProviderMistral AIZ.ai (Zhipu)
Noometry Index36.151.1
Released2025-12-092026-06-13
WeightsOpenOpen
Context window262K1M
Max output262K131K
Input $ / M tokens$0.40$1.40
Output $ / M tokens$2$4.40
Results tracked251

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Category by category

Coding GLM-5.2 leads

Devstral 2: 33.2 (#261), GLM-5.2: 51.3 (#41)

BenchmarkDevstral 2GLM-5.2
LMArena WebDev11971603
SWE-bench Verified—78.7%
DeepSWE—43.8%
FrontierCode—24.5%
SWE-bench Verified (bash only)53.8%—
SciCode—50.5%
WeirdML—70.1%
LMArena Coding—1485
ALE-Bench—1,047

Agentic & Tool Use Not comparable

Devstral 2: —, GLM-5.2: 32.4 (#63)

BenchmarkDevstral 2GLM-5.2
APEX-Agents—45.2%
τ²-bench Banking—37.1%
PostTrainBench—31.7%
GBAEval—0%
Vending-Bench 2—8,314

Reasoning Not comparable

Devstral 2: —, GLM-5.2: 42.3 (#52)

BenchmarkDevstral 2GLM-5.2
ARC-AGI-2—22.8%
SimpleBench—58.8%
Kagi LLM Benchmark—62.6%
NYT Connections (extended)—74.3%
ARC-AGI-1—77%
CritPt—20.9%
Chess Puzzles—21%
EBR-Bench—9.5%
LMArena Hard Prompts—1480
Mystery Game Puzzles—19%
DTBench—93.6%
LMCA—45.8%
Surface Evolver Bench—55.6%
Epoch Capabilities Index—151.78

Math Not comparable

Devstral 2: —, GLM-5.2: 55.7 (#43)

BenchmarkDevstral 2GLM-5.2
FrontierMath (Tiers 1-3)—59.2%
FrontierMath Tier 4—29.3%
MathArena Final-Answer Competitions—67.6%
OTIS Mock AIME 2024-2025—86.4%
ProofBench—35%
LMArena Math—1482

Knowledge Not comparable

Devstral 2: —, GLM-5.2: 57.1 (#40)

BenchmarkDevstral 2GLM-5.2
GPQA Diamond—91.9%
SimpleQA Verified—34.2%
LMArena Expert—1486

Multilingual Not comparable

Devstral 2: —, GLM-5.2: 55.8 (#26)

BenchmarkDevstral 2GLM-5.2
LMArena Non-English—1459
LMArena Chinese—1519
LMArena French—1479
LMArena German—1468
LMArena Japanese—1451
LMArena Korean—1445
LMArena Russian—1466
LMArena Spanish—1477

Instruction Following Not comparable

Devstral 2: —, GLM-5.2: 76.9 (#34)

BenchmarkDevstral 2GLM-5.2
LMArena Instruction Following—1465

Long Context Not comparable

Devstral 2: —, GLM-5.2: 45.3 (#43)

BenchmarkDevstral 2GLM-5.2
LMArena Longer Query—1479

Writing & Preference Not comparable

Devstral 2: —, GLM-5.2: 70.4 (#21)

BenchmarkDevstral 2GLM-5.2
LMArena Text—1470
LMArena Creative Writing—1462
EQ-Bench Creative Writing—1757
EQ-Bench 4—1222
LMArena Multi-Turn—1469

Frequently asked questions

Is Devstral 2 better than GLM-5.2?

GLM-5.2 has enough public results to be ranked (#44); Devstral 2 does not yet, so treat this comparison as directional.

Which is cheaper, Devstral 2 or GLM-5.2?

Devstral 2 is cheaper. It lists at $0.40 per million input tokens and $2 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.

Is Devstral 2 or GLM-5.2 better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 33.2 in the Noometry coding category.

Which has the bigger context window?

GLM-5.2 does, with 1M tokens against 262K.

How many benchmarks do Devstral 2 and GLM-5.2 share?

1 benchmark has published results for both models. Devstral 2 has 2 scored results on Noometry and GLM-5.2 has 51.

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