Model comparison

GLM-4.7 vs Muse Spark 1.1

Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 42.0 on the Noometry Index. GLM-4.7 costs 2.0× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.

Last verified October 11, 2026. 25 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Muse Spark 1.1

Summary

They share 25 benchmarks with published results for both. GLM-4.7 scores higher in 0 categories and Muse Spark 1.1 in 9 categories; 9 gaps are clear of the uncertainty.
The widest gap is in reasoning, where Muse Spark 1.1 leads 47.1 to 24.3.
The biggest single-benchmark swing is ProofBench: 6% for GLM-4.7 and 39% for Muse Spark 1.1.
GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.1.
Muse Spark 1.1 accepts more context: 1.05M tokens versus 205K.
GLM-4.7 has downloadable open weights; the other is API-only.

Side by side

GLM-4.7 and Muse Spark 1.1 specifications
	GLM-4.7	Muse Spark 1.1
Provider	Z.ai (Zhipu)	Meta
Noometry Index	42.0	49.9
Released	2025-12-22	2026-04-08
Weights	Open	Proprietary
Context window	205K	1.05M
Max output	131K	131K
Input $ / M tokens	$0.60	$1.25
Output $ / M tokens	$2.20	$4.25
Results tracked	36	37

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Category by category

Coding Muse Spark 1.1 leads

GLM-4.7: 44.0 (#79), Muse Spark 1.1: 51.3 (#40)

Coding benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena WebDev	1435	1542
SciCode	45.1%	58.8%
LMArena Coding	1454	1498
DeepSWE	—	53.3%
ALE-Bench	399.48	—

Agentic & Tool Use Muse Spark 1.1 leads

GLM-4.7: 26.5 (#103), Muse Spark 1.1: 30.8 (#73)

Agentic & Tool Use benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
Vending-Bench 2	2,377	6,520
Terminal-Bench	33.4%	—
APEX-Agents	—	31.8%
τ²-bench Banking	—	40.5%
GBAEval	—	7.9%
GDP.pdf	—	15%

Reasoning Muse Spark 1.1 leads

GLM-4.7: 24.3 (#164), Muse Spark 1.1: 47.1 (#44)

Reasoning benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
CritPt	1.7%	15.1%
LMArena Hard Prompts	1443	1486
Epoch Capabilities Index	143.51	154.21
SimpleBench	47.7%	—
NYT Connections (extended)	—	84.9%
Chess Puzzles	6%	—
DTBench	—	94.4%
LMCA	—	49.9%
Surface Evolver Bench	—	52.5%

Math Muse Spark 1.1 leads

GLM-4.7: 38.6 (#135), Muse Spark 1.1: 45.5 (#76)

Math benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
ProofBench	6%	39%
LMArena Math	1423	1483
OTIS Mock AIME 2024-2025	83.3%	—
FrontierMath (Feb 2025 set)	2.4%	—
FrontierMath Tier 4 (v1)	0%	—

Knowledge Muse Spark 1.1 leads

GLM-4.7: 47.0 (#80), Muse Spark 1.1: 53.1 (#59)

Knowledge benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
SimpleQA Verified	32.2%	57.8%
LMArena Expert	1424	1478
GPQA Diamond	83.3%	—
Vectara Hallucination Rate	11.7%	—

Multimodal Not comparable

GLM-4.7: —, Muse Spark 1.1: 42.6 (#29)

Multimodal benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena Vision	—	1293
LMArena Document	—	1465

Multilingual Muse Spark 1.1 leads

GLM-4.7: 52.8 (#79), Muse Spark 1.1: 56.7 (#17)

Multilingual benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena Non-English	1417	1472
LMArena Chinese	1495	1518
LMArena French	1432	1494
LMArena German	1424	1466
LMArena Japanese	1439	1451
LMArena Korean	1399	1458
LMArena Russian	1423	1483
LMArena Spanish	1434	1464

Instruction Following Muse Spark 1.1 leads

GLM-4.7: 74.4 (#95), Muse Spark 1.1: 76.5 (#39)

Instruction Following benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena Instruction Following	1411	1457

Long Context Muse Spark 1.1 leads

GLM-4.7: 42.8 (#116), Muse Spark 1.1: 44.8 (#58)

Long Context benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena Longer Query	1432	1462
CL-bench	15.9%	—
CL-bench Life	10.9%	—

Writing & Preference Muse Spark 1.1 leads

GLM-4.7: 60.9 (#93), Muse Spark 1.1: 73.4 (#11)

Writing & Preference benchmarks
Benchmark	GLM-4.7	Muse Spark 1.1
LMArena Text	1435	1479
LMArena Creative Writing	1401	1437
EQ-Bench Creative Writing	1413	1927
LMArena Multi-Turn	1446	1485
EQ-Bench 4	—	1260

Frequently asked questions

Is GLM-4.7 better than Muse Spark 1.1?

Which is cheaper, GLM-4.7 or Muse Spark 1.1?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.

Is GLM-4.7 or Muse Spark 1.1 better for coding?

Muse Spark 1.1 scores higher on coding benchmarks: 51.3 versus 44.0 in the Noometry coding category.

Which has the bigger context window?

Muse Spark 1.1 does, with 1.05M tokens against 205K.

How many benchmarks do GLM-4.7 and Muse Spark 1.1 share?

25 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Muse Spark 1.1 has 37.