Qwen3 235B A22B Thinking 2507 vs GLM 4.7

Qwen3 235B A22B Thinking 2507 and GLM 4.7 match in llmrun Score, with values of 108.1 versus 108.3; neither fits 24 GB.

Model A · Alibaba

Qwen3 235B A22B Thinking 2507

108.1llmrun Score

235.1B · 22.2B active · 256K context · Apache 2.0 · Jul 2025

ChatFunctions

Model B · Z.ai

GLM 4.7

108.3llmrun Score

358.3B · 35.6B active · 198K context · MIT · Dec 2025

ChatFunctions

Which should you choose?

Choose Qwen3 235B A22B Thinking 2507 if you want…

Fits a Mac 128 GB
Q3_K_L · 122.4 GB; GLM 4.7 needs 101.4 GB at its smallest quant
Lighter on memory
141.6 vs 215.6 GB at Q4_K_M

Choose GLM 4.7 if you want…

Newer release
Dec 2025 vs Jul 2025

On your hardware

Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.

MemoryQwen3 235B A22B Thinking 2507GLM 4.7

8 GB

RTX 4060 · 8 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

12 GB

RTX 3060 12GB · 12 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

24 GBreference

RTX 4090 · 24 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

32 GB

RTX 5090 · 32 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

48 GB

RTX A6000 · 48 GB tier

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 32 GB

Mac Mini M4 · Macs

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 64 GB

Mac Studio M4 Max · Macs

Qwen3 235B A22B Thinking 2507

Doesn't fit

smallest quant needs 72.4 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 128 GB

Mac Studio M4 Max · Macs

Qwen3 235B A22B Thinking 2507

Q3_K_L · ~21 tok/s

122.4 GB · up to 32Kbetter quant

GLM 4.7

IQ2_M · ~20 tok/s

123.8 GB · up to 16K

Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).

llmrun Score

with its 90% range · bars share one scale

Qwen3 235B A22B Thinking 2507 GLM 4.7

Overall

Qwen3 235B A22B Thinking 2507

108.1105–112

GLM 4.7

108.3105–112

Coding

Qwen3 235B A22B Thinking 2507

102.693–113

GLM 4.7

101.388–115

Agents

Qwen3 235B A22B Thinking 2507

no data

GLM 4.7

105.898–114

Math

Qwen3 235B A22B Thinking 2507

no data

GLM 4.7

111.1104–118

Science

Qwen3 235B A22B Thinking 2507

107.799–116

GLM 4.7

111.2102–120

Reasoning

Qwen3 235B A22B Thinking 2507

105.998–113

GLM 4.7

104.392–116

Qwen3 235B A22B Thinking 2507 · #31 of 92 open models · #15 of 71 that fit ≤192 GB

GLM 4.7 · #29 of 92 open models · #18 of 77 that fit ≤256 GB

Benchmarks

7 shared boards: Qwen3 235B A22B Thinking 2507 leads 3, GLM 4.7 leads 4 · Benchmarks imported Oct 2026

BoardQwen3 235B A22B Thinking 2507GLM 4.7

GPQA Diamond

Qwen3 235B A22B Thinking 2507

80.0%#24/97 open

IndependentEpoch AI · Jul 2025

GLM 4.7

83.3%#23/97 open

IndependentEpoch AI · Dec 2025

LMArena Text

Qwen3 235B A22B Thinking 2507

1400.0#48/186 open

ArenaLMArena · Oct 2026

GLM 4.7

1441.2#18/186 open

ArenaLMArena · Oct 2026

AIME 2024/2025

Qwen3 235B A22B Thinking 2507

86.7%#18/85 open

IndependentEpoch AI · Jul 2025

GLM 4.7

83.3%#21/85 open

IndependentEpoch AI · Dec 2025

SciCode

Qwen3 235B A22B Thinking 2507

42.4%#26/65 open

Lab-reportedEpoch AI · Jul 2025

GLM 4.7

45.1%#20/65 open

Lab-reportedEpoch AI · Dec 2025

SimpleQA

Qwen3 235B A22B Thinking 2507

40.4%#5/15 open

IndependentEpoch AI · Jul 2025

GLM 4.7

32.2%#13/15 open

IndependentEpoch AI · Dec 2025

Chess Puzzles

Qwen3 235B A22B Thinking 2507

12.0%#22/67 open

IndependentEpoch AI · Jul 2025

GLM 4.7

6.0%#28/67 open

IndependentEpoch AI · Dec 2025

CritPt

Qwen3 235B A22B Thinking 2507

0.0%#62/65 open

Lab-reportedEpoch AI · Jul 2025

GLM 4.7

1.7%#28/65 open

Lab-reportedEpoch AI · Dec 2025

14 more boards (other shared and single-model boards)

Vending-Bench 2

Qwen3 235B A22B Thinking 2507

-11.3#15/17 open

Lab-reportedEpoch AI · Jul 2025

GLM 4.7

2376.8#9/17 open

Lab-reportedEpoch AI · Dec 2025

Only Qwen3 235B A22B Thinking 2507 (6)

Only GLM 4.7 (7)

VRAM by quantization

Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.

QuantQwen3 235B A22B Thinking 2507GLM 4.7

Q2_K

Qwen3 235B A22B Thinking 2507

100 GB85.7 GB file

32K 103 GB · 128K 113 GB

GLM 4.7

153 GB131.2 GB file

32K 158 GB · 128K 173 GB

Q3_K_S

Qwen3 235B A22B Thinking 2507

103 GB101.4 GB file

32K 106 GB · 128K 116 GB

GLM 4.7

157 GB155.0 GB file

32K 162 GB · 128K 178 GB

Q3_K_M

Qwen3 235B A22B Thinking 2507

115 GB112.4 GB file

32K 118 GB · 128K 128 GB

GLM 4.7

175 GB171.3 GB file

32K 180 GB · 128K 196 GB

Q4_0

Qwen3 235B A22B Thinking 2507

118 GB133.1 GB file

32K 121 GB · 128K 130 GB

GLM 4.7

180 GB203.0 GB file

32K 185 GB · 128K 200 GB

Q4_K_M

Qwen3 235B A22B Thinking 2507

142 GB142.2 GB file

32K 145 GB · 128K 154 GB

GLM 4.7

216 GB216.5 GB file

32K 220 GB · 128K 236 GB

Q5_K_M

Qwen3 235B A22B Thinking 2507

168 GB166.8 GB file

32K 171 GB · 128K 180 GB

GLM 4.7

256 GB254.2 GB file

32K 261 GB · 128K 276 GB

Q6_K

Qwen3 235B A22B Thinking 2507

194 GB193.0 GB file

32K 197 GB · 128K 207 GB

GLM 4.7

296 GB294.4 GB file

32K 301 GB · 128K 317 GB

Q8_0

Qwen3 235B A22B Thinking 2507

236 GB249.9 GB file

32K 239 GB · 128K 248 GB

GLM 4.7

359 GB381.0 GB file

32K 364 GB · 128K 379 GB

16 more quants

IQ2_XXS

Qwen3 235B A22B Thinking 2507

not listed

GLM 4.7

99.2 GB115.9 GB file

32K 104 GB · 128K 119 GB

IQ2_XS

Qwen3 235B A22B Thinking 2507

71.0 GB65.6 GB file

32K 74.0 GB · 128K 83.5 GB

GLM 4.7

108 GB101.5 GB file

32K 113 GB · 128K 128 GB

IQ2_S

Qwen3 235B A22B Thinking 2507

74.0 GB66.1 GB file

32K 76.9 GB · 128K 86.4 GB

GLM 4.7

113 GB102.3 GB file

32K 117 GB · 128K 133 GB

IQ2_M

Qwen3 235B A22B Thinking 2507

79.8 GB78.6 GB file

32K 82.8 GB · 128K 92.3 GB

GLM 4.7

122 GB122.4 GB file

32K 126 GB · 128K 142 GB

IQ3_XXS

Qwen3 235B A22B Thinking 2507

91.6 GB93.1 GB file

32K 94.6 GB · 128K 104 GB

GLM 4.7

139 GB145.1 GB file

32K 144 GB · 128K 160 GB

IQ3_XS

Qwen3 235B A22B Thinking 2507

97.5 GB96.9 GB file

32K 100 GB · 128K 110 GB

GLM 4.7

148 GB148.7 GB file

32K 153 GB · 128K 169 GB

IQ3_S

Qwen3 235B A22B Thinking 2507

not listed

GLM 4.7

153 GB154.6 GB file

32K 158 GB · 128K 173 GB

IQ3_M

Qwen3 235B A22B Thinking 2507

106 GB107.3 GB file

32K 109 GB · 128K 119 GB

GLM 4.7

162 GB164.8 GB file

32K 167 GB · 128K 182 GB

Q3_K_L

Qwen3 235B A22B Thinking 2507

121 GB111.2 GB file

32K 124 GB · 128K 133 GB

GLM 4.7

184 GB170.6 GB file

32K 189 GB · 128K 205 GB

IQ4_XS

Qwen3 235B A22B Thinking 2507

127 GB125.5 GB file

32K 130 GB · 128K 139 GB

GLM 4.7

193 GB191.6 GB file

32K 198 GB · 128K 213 GB

IQ4_NL

Qwen3 235B A22B Thinking 2507

133 GB133.1 GB file

32K 136 GB · 128K 145 GB

GLM 4.7

202 GB202.5 GB file

32K 207 GB · 128K 222 GB

Q4_1

Qwen3 235B A22B Thinking 2507

133 GB147.2 GB file

32K 136 GB · 128K 145 GB

GLM 4.7

202 GB224.6 GB file

32K 207 GB · 128K 222 GB

Q4_K_S

Qwen3 235B A22B Thinking 2507

133 GB133.7 GB file

32K 136 GB · 128K 145 GB

GLM 4.7

202 GB203.7 GB file

32K 207 GB · 128K 222 GB

Q4_K_L

Qwen3 235B A22B Thinking 2507

not listed

GLM 4.7

220 GB219.1 GB file

32K 225 GB · 128K 240 GB

Q5_K_S

Qwen3 235B A22B Thinking 2507

162 GB161.9 GB file

32K 165 GB · 128K 175 GB

GLM 4.7

247 GB247.0 GB file

32K 252 GB · 128K 267 GB

BF16

Qwen3 235B A22B Thinking 2507

471 GB470.3 GB file

32K 474 GB · 128K 483 GB

GLM 4.7

717 GB716.8 GB file

32K 722 GB · 128K 738 GB

How to run each

Qwen3 235B A22B Thinking 2507

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Qwen3-235B-A22B-Thinking-2507-GGUF:Q4_K_M

All ways to run Qwen3 235B A22B Thinking 2507 →

GLM 4.7

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-4.7-GGUF:Q4_K_M

All ways to run GLM 4.7 →

Specifications

Specifications of Qwen3 235B A22B Thinking 2507 and GLM 4.7
Spec	Qwen3 235B A22B Thinking 2507	GLM 4.7
Publisher	Alibaba	Z.ai
Parameters	235.1B	358.3B
Active parameters	22B per token	36B per token
Architecture	Qwen3MoeForCausalLM	Glm4MoeForCausalLM
Context	256K tokens	198K tokens
Modalities	Chat, Function-calling	Chat, Function-calling
License	Apache 2.0	MIT
Released	Jul 2025	Dec 2025

Frequently Asked Questions

Which is better, Qwen3 235B A22B Thinking 2507 or GLM 4.7?

Qwen3 235B A22B Thinking 2507 and GLM 4.7 match in llmrun Score, with values of 108.1 versus 108.3; neither fits 24 GB. Choose Qwen3 235B A22B Thinking 2507 for fits a Mac 128 GB and lighter on memory; choose GLM 4.7 for newer release.

Which needs less VRAM, Qwen3 235B A22B Thinking 2507 or GLM 4.7?

At Q4_K_M, Qwen3 235B A22B Thinking 2507 requires 141.6 GB while GLM 4.7 needs 215.6 GB, making Qwen3 235B A22B Thinking 2507 the easier model to run on your local setup.

Can I run Qwen3 235B A22B Thinking 2507 or GLM 4.7 on a 16 GB GPU?

Qwen3 235B A22B Thinking 2507 does not fit (smallest quant needs 72.4 GB); GLM 4.7 does not fit (smallest quant needs 101.4 GB).

Which has a longer context window, Qwen3 235B A22B Thinking 2507 or GLM 4.7?

Qwen3 235B A22B Thinking 2507 supports 262,144 tokens and GLM 4.7 supports 202,752 tokens.