Model comparison

GLM-4.7-Flash vs MiniMax M1

MiniMax M1 is the stronger model overall, scoring 40.3 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 6.6× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.

Last verified October 12, 2026. 16 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

MiniMax M1

MiniMax

40.3

Rank #150 Confirmed

Summary

They share 16 benchmarks with published results for both. GLM-4.7-Flash scores higher in 3 categories and MiniMax M1 in 5 categories; 3 gaps are clear of the uncertainty.
The widest gap is in reasoning, where MiniMax M1 leads 26.9 to 20.9.
GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.55 / $2.20 for MiniMax M1.
MiniMax M1 accepts more context: 1M tokens versus 200K.

Side by side

GLM-4.7-Flash and MiniMax M1 specifications
	GLM-4.7-Flash	MiniMax M1
Provider	Z.ai (Zhipu)	MiniMax
Noometry Index	38.8	40.3
Released	2026-01-19	2025-06-13
Weights	Open	Open
Context window	200K	1M
Max output	131K	40K
Input $ / M tokens	$0.06	$0.55
Output $ / M tokens	$0.40	$2.20
Results tracked	21	18

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Category by category

Coding Too close to call

GLM-4.7-Flash: 40.6 (#135), MiniMax M1: 39.9 (#153)

Coding benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Coding	1383	1359

Reasoning MiniMax M1 leads

GLM-4.7-Flash: 20.9 (#229), MiniMax M1: 26.9 (#126)

Reasoning benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Hard Prompts	1356	1339
Chess Puzzles	0%	—

Math MiniMax M1 leads

GLM-4.7-Flash: 36.1 (#173), MiniMax M1: 37.5 (#151)

Math benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Math	1355	1361
OTIS Mock AIME 2024-2025	58.3%	—

Knowledge Too close to call

GLM-4.7-Flash: 35.5 (#184), MiniMax M1: 36.4 (#170)

Knowledge benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Expert	1357	1317
GPQA Diamond	60.5%	—
Vectara Hallucination Rate	9.3%	—

Multilingual Too close to call

GLM-4.7-Flash: 46.5 (#158), MiniMax M1: 45.8 (#163)

Multilingual benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Non-English	1330	1319
LMArena Chinese	1403	1360
LMArena French	1332	1370
LMArena German	1337	1350
LMArena Korean	1283	1266
LMArena Russian	1332	1329
LMArena Spanish	1350	1353
LMArena Japanese	—	1217

Instruction Following Too close to call

GLM-4.7-Flash: 70.1 (#167), MiniMax M1: 69.3 (#174)

Instruction Following benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Instruction Following	1327	1312

Long Context Too close to call

GLM-4.7-Flash: 40.9 (#148), MiniMax M1: 41.4 (#141)

Long Context benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Longer Query	1345	1326
Fiction.LiveBench	—	69.4%

Writing & Preference MiniMax M1 leads

GLM-4.7-Flash: 47.4 (#210), MiniMax M1: 53.1 (#161)

Writing & Preference benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Text	1351	1343
LMArena Creative Writing	1297	1298
LMArena Multi-Turn	1342	1335
EQ-Bench Creative Writing	1125	—

Frequently asked questions

Is GLM-4.7-Flash better than MiniMax M1?

Which is cheaper, GLM-4.7-Flash or MiniMax M1?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; MiniMax M1 lists at $0.55 and $2.20.

Is GLM-4.7-Flash or MiniMax M1 better for coding?

They score almost the same on coding (40.6 vs 39.9); test both on your own repository before choosing.

Which has the bigger context window?

MiniMax M1 does, with 1M tokens against 200K.

How many benchmarks do GLM-4.7-Flash and MiniMax M1 share?

16 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and MiniMax M1 has 18.