Model comparison

GLM-5 vs Qwen3.5 122B-A10B

GLM-5 is the stronger model overall, scoring 45.9 to 41.6 on the Noometry Index.

Last verified October 10, 2026. 20 shared benchmarks.

GLM-5 Z.ai (Zhipu)

45.9

Rank #59 Confirmed

Qwen3.5 122B-A10B

Alibaba (Qwen)

41.6

Rank #120 Confirmed

Summary

They share 20 benchmarks with published results for both. GLM-5 scores higher in 8 categories and Qwen3.5 122B-A10B in 0 categories; 8 gaps are clear of the uncertainty.
The widest gap is in knowledge, where GLM-5 leads 52.2 to 38.2.
The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 51.7% for Qwen3.5 122B-A10B.
Qwen3.5 122B-A10B is cheaper at $0.40 / $3.20 per million input/output tokens, against $1 / $3.20 for GLM-5.
Qwen3.5 122B-A10B accepts more context: 262K tokens versus 205K.

Side by side

GLM-5 and Qwen3.5 122B-A10B specifications
	GLM-5	Qwen3.5 122B-A10B
Provider	Z.ai (Zhipu)	Alibaba (Qwen)
Noometry Index	45.9	41.6
Released	2026-02-11	2026-02-23
Weights	Open	Open
Context window	205K	262K
Max output	131K	66K
Input $ / M tokens	$1	$0.40
Output $ / M tokens	$3.20	$3.20
Results tracked	45	27

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Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#47), Qwen3.5 122B-A10B: 38.8 (#155)

Coding benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena WebDev	1434	1360
LMArena Coding	1461	1436
SWE-bench Verified	72.1%	—
SWE-bench Verified (bash only)	72.8%	—
SWE-bench Multilingual	69.7%	—
SciCode	—	35.6%
WeirdML	48.2%	—
ALE-Bench	765.62	—

Agentic & Tool Use Not comparable

GLM-5: 30.9 (#65), Qwen3.5 122B-A10B: —

Agentic & Tool Use benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
Terminal-Bench	52.4%	—
τ²-bench Airline	82.5%	—
τ²-bench Banking	9.8%	—
τ²-bench Retail	73.7%	—
τ²-bench Telecom	86.8%	—
Vending-Bench 2	4,432	—

Reasoning GLM-5 leads

GLM-5: 27.6 (#100), Qwen3.5 122B-A10B: 26.4 (#121)

Reasoning benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
NYT Connections (extended)	74.8%	51.7%
LMArena Hard Prompts	1451	1421
ARC-AGI-2	4.9%	—
SimpleBench	53.2%	—
Kagi LLM Benchmark	75%	—
ARC-AGI-1	44.7%	—
CritPt	—	0.9%
Chess Puzzles	10%	—
Thematic Generalization	—	51.2%
Mystery Game Puzzles	—	17%
DTBench	—	84.3%
LMCA	—	32.2%
Epoch Capabilities Index	145.84	—
ForecastBench	61	—

Math GLM-5 leads

GLM-5: 44.8 (#66), Qwen3.5 122B-A10B: 36.4 (#114)

Math benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Math	1440	1432
MathArena Final-Answer Competitions	65.7%	—
OTIS Mock AIME 2024-2025	80%	—
FrontierMath (Feb 2025 set)	16.4%	—
FrontierMath Tier 4 (v1)	2.1%	—

Knowledge GLM-5 leads

GLM-5: 52.2 (#59), Qwen3.5 122B-A10B: 38.2 (#138)

Knowledge benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
Vectara Hallucination Rate	10.1%	11.2%
LMArena Expert	1454	1431
GPQA Diamond	87.8%	—

Multimodal Not comparable

GLM-5: —, Qwen3.5 122B-A10B: 39.0 (#52)

Multimodal benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Vision	—	1245

Multilingual GLM-5 leads

GLM-5: 53.9 (#57), Qwen3.5 122B-A10B: 51.8 (#101)

Multilingual benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Non-English	1430	1400
LMArena Chinese	1511	1462
LMArena French	1455	1442
LMArena German	1445	1425
LMArena Japanese	1416	1364
LMArena Korean	1421	1353
LMArena Russian	1436	1400
LMArena Spanish	1452	1423

Instruction Following GLM-5 leads

GLM-5: 75.4 (#64), Qwen3.5 122B-A10B: 74.0 (#109)

Instruction Following benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Instruction Following	1427	1399

Long Context GLM-5 leads

GLM-5: 44.6 (#58), Qwen3.5 122B-A10B: 43.0 (#105)

Long Context benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Longer Query	1446	1410
CL-bench	18.7%	—

Writing & Preference GLM-5 leads

GLM-5: 66.2 (#38), Qwen3.5 122B-A10B: 60.2 (#98)

Writing & Preference benchmarks
Benchmark	GLM-5	Qwen3.5 122B-A10B
LMArena Text	1446	1417
LMArena Creative Writing	1438	1369
LMArena Multi-Turn	1456	1416
EQ-Bench Creative Writing	1601	—

Frequently asked questions

Is GLM-5 better than Qwen3.5 122B-A10B?

GLM-5 is the stronger model overall, scoring 45.9 to 41.6 on the Noometry Index.

Which is cheaper, GLM-5 or Qwen3.5 122B-A10B?

Qwen3.5 122B-A10B is cheaper. It lists at $0.40 per million input tokens and $3.20 per million output tokens; GLM-5 lists at $1 and $3.20.

Is GLM-5 or Qwen3.5 122B-A10B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 38.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5 122B-A10B does, with 262K tokens against 205K.

How many benchmarks do GLM-5 and Qwen3.5 122B-A10B share?

20 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen3.5 122B-A10B has 27.