Model comparison

GLM-4.7-Flash vs MiniMax M1

MiniMax M1 is the stronger model overall, scoring 39.7 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 5.9× less per token, which makes it the better buy when MiniMax M1's lead doesn't matter for your workload.

Last verified October 10, 2026. 16 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.4

Rank #175 Confirmed

MiniMax M1

MiniMax

39.7

Rank #146 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; 2 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where MiniMax M1 leads 53.3 to 47.7.
GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.40 / $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	38.4	39.7
Released	2026-01-19	2025-06-13
Weights	Open	Open
Context window	200K	1M
Max output	131K	40K
Input $ / M tokens	$0.06	$0.40
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: 40.0 (#133), MiniMax M1: 39.2 (#149)

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

Reasoning MiniMax M1 leads

GLM-4.7-Flash: 20.2 (#224), MiniMax M1: 25.8 (#125)

Reasoning benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Hard Prompts	1356	1340
Chess Puzzles	0%	—

Math Too close to call

GLM-4.7-Flash: 34.4 (#159), MiniMax M1: 34.8 (#152)

Math benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Math	1354	1360
OTIS Mock AIME 2024-2025	58.3%	—

Knowledge Too close to call

GLM-4.7-Flash: 35.4 (#177), MiniMax M1: 35.7 (#168)

Knowledge benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Expert	1357	1316
GPQA Diamond	60.5%	—
Vectara Hallucination Rate	9.3%	—

Multilingual Too close to call

GLM-4.7-Flash: 46.8 (#152), MiniMax M1: 46.0 (#157)

Multilingual benchmarks
Benchmark	GLM-4.7-Flash	MiniMax M1
LMArena Non-English	1331	1320
LMArena Chinese	1403	1361
LMArena French	1332	1369
LMArena German	1336	1350
LMArena Korean	1284	1263
LMArena Russian	1333	1330
LMArena Spanish	1351	1354
LMArena Japanese	—	1220

Instruction Following Too close to call

GLM-4.7-Flash: 70.3 (#162), MiniMax M1: 69.5 (#169)

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 (#143), MiniMax M1: 41.4 (#136)

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: 47.7 (#206), MiniMax M1: 53.3 (#155)

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 $0.40 and $2.20.

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

They score almost the same on coding (40.0 vs 39.2); 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.