Model comparison

Codestral vs GLM-5.2

GLM-5.2 is the stronger model overall, scoring 51.1 to 30.6 on the Noometry Index. Codestral costs 4.8× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.

Last verified October 10, 2026. 2 shared benchmarks.

Codestral

Mistral AI

30.6

Rank #290 Reported

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Summary

They share 2 benchmarks with published results for both. Codestral scores higher in 0 categories and GLM-5.2 in 2 categories; 2 gaps are clear of the uncertainty.
The widest gap is in coding, where GLM-5.2 leads 51.3 to 27.3.
The biggest single-benchmark swing is Kagi LLM Benchmark: 32.5% for Codestral and 62.6% for GLM-5.2.
Codestral is cheaper at $0.30 / $0.90 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
GLM-5.2 accepts more context: 1M tokens versus 256K.
GLM-5.2 has downloadable open weights; the other is API-only.

Side by side

Codestral and GLM-5.2 specifications
	Codestral	GLM-5.2
Provider	Mistral AI	Z.ai (Zhipu)
Noometry Index	30.6	51.1
Released	2024-05-29	2026-06-13
Weights	Proprietary	Open
Context window	256K	1M
Max output	8K	131K
Input $ / M tokens	$0.30	$1.40
Output $ / M tokens	$0.90	$4.40
Results tracked	7	51

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Category by category

Coding GLM-5.2 leads

Codestral: 27.3 (#321), GLM-5.2: 51.3 (#41)

Coding benchmarks
Benchmark	Codestral	GLM-5.2
ALE-Bench	137.78	1,047
SWE-bench Verified	—	78.7%
DeepSWE	—	43.8%
FrontierCode	—	24.5%
Aider Polyglot	11.1%	—
LMArena WebDev	—	1603
SciCode	—	50.5%
WeirdML	—	70.1%
BigCodeBench Instruct	41.8%	—
LMArena Coding	—	1485
BigCodeBench Complete	52.5%	—
HumanEval+	73.8%	—
MBPP+	61.9%	—

Agentic & Tool Use Not comparable

Codestral: —, GLM-5.2: 32.4 (#63)

Agentic & Tool Use benchmarks
Benchmark	Codestral	GLM-5.2
APEX-Agents	—	45.2%
τ²-bench Banking	—	37.1%
PostTrainBench	—	31.7%
GBAEval	—	0%
Vending-Bench 2	—	8,314

Reasoning GLM-5.2 leads

Codestral: 19.8 (#251), GLM-5.2: 42.3 (#52)

Reasoning benchmarks
Benchmark	Codestral	GLM-5.2
Kagi LLM Benchmark	32.5%	62.6%
ARC-AGI-2	—	22.8%
SimpleBench	—	58.8%
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

Codestral: —, GLM-5.2: 55.7 (#43)

Math benchmarks
Benchmark	Codestral	GLM-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

Codestral: —, GLM-5.2: 57.1 (#40)

Knowledge benchmarks
Benchmark	Codestral	GLM-5.2
GPQA Diamond	—	91.9%
SimpleQA Verified	—	34.2%
LMArena Expert	—	1486

Multilingual Not comparable

Codestral: —, GLM-5.2: 55.8 (#26)

Multilingual benchmarks
Benchmark	Codestral	GLM-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

Codestral: —, GLM-5.2: 76.9 (#34)

Instruction Following benchmarks
Benchmark	Codestral	GLM-5.2
LMArena Instruction Following	—	1465

Long Context Not comparable

Codestral: —, GLM-5.2: 45.3 (#43)

Long Context benchmarks
Benchmark	Codestral	GLM-5.2
LMArena Longer Query	—	1479

Writing & Preference Not comparable

Codestral: —, GLM-5.2: 70.4 (#21)

Writing & Preference benchmarks
Benchmark	Codestral	GLM-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 Codestral better than GLM-5.2?

Which is cheaper, Codestral or GLM-5.2?

Codestral is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.

Is Codestral or GLM-5.2 better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 27.3 in the Noometry coding category.

Which has the bigger context window?

GLM-5.2 does, with 1M tokens against 256K.

How many benchmarks do Codestral and GLM-5.2 share?

2 benchmarks have published results for both models. Codestral has 7 scored results on Noometry and GLM-5.2 has 51.