GLM 4.5 vs GLM 4.6

GLM 4.6 leads llmrun Score 103.1 to 100.9 (ranges overlap); neither fits 24 GB.

Model A · Z.ai

GLM 4.5

100.9llmrun Score

358.3B · 35.6B active · 128K context · MIT · Jul 2025

ChatFunctions

Model B · Z.ai

GLM 4.6

103.1llmrun Score

356.8B · 34B active · 198K context · MIT · Sep 2025

ChatFunctions

Which should you choose?

Choose GLM 4.6 if you want…

Higher llmrun Score
103.1 vs 100.9, ranges overlap
Ahead on the benchmarks
3 of 3 shared boards
Longer context window
198K vs 128K tokens

GLM 4.5: no clear edge over GLM 4.6 in the data we have.

On your hardware

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

MemoryGLM 4.5GLM 4.6

8 GB

RTX 4060 · 8 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

12 GB

RTX 3060 12GB · 12 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

24 GBreference

RTX 4090 · 24 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

32 GB

RTX 5090 · 32 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

48 GB

RTX A6000 · 48 GB tier

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

Mac 32 GB

Mac Mini M4 · Macs

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

Mac 64 GB

Mac Studio M4 Max · Macs

GLM 4.5

Doesn't fit

smallest quant needs 101.4 GB

GLM 4.6

Doesn't fit

smallest quant needs 101 GB

Mac 128 GB

Mac Studio M4 Max · Macs

GLM 4.5

IQ2_M · ~20 tok/s

123.8 GB · up to 16K

GLM 4.6

IQ2_M · ~21 tok/s

123.3 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

GLM 4.5 GLM 4.6

Overall

GLM 4.5

100.997–105

GLM 4.6

103.198–108

Coding

GLM 4.5

98.789–108

GLM 4.6

96.081–111

Agents

GLM 4.5

105.499–112

GLM 4.6

104.399–109

Science

GLM 4.5

no data

GLM 4.6

99.878–121

GLM 4.5 · #44 of 92 open models · #31 of 77 that fit ≤256 GB

GLM 4.6 · #41 of 92 open models · #29 of 77 that fit ≤256 GB

Benchmarks

3 shared boards: GLM 4.5 leads 0, GLM 4.6 leads 3 · Benchmarks imported Oct 2026

BoardGLM 4.5GLM 4.6

SWE-bench Verified

GLM 4.5

64.2%#9/20 open

IndependentSWE-bench · Jul 2025

GLM 4.6

68.2%#7/20 open

IndependentSWE-bench · Sep 2025

LMArena Text

GLM 4.5

1411.0#42/186 open

ArenaLMArena · Oct 2026

GLM 4.6

1424.2#31/186 open

ArenaLMArena · Oct 2026

SWE-bench Bash Only

GLM 4.5

54.2%#6/9 open

IndependentSWE-bench · Aug 2025

GLM 4.6

55.4%#5/9 open

IndependentSWE-bench · Dec 2025

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

ALE-Bench

GLM 4.5

344.8#36/42 open

Lab-reportedEpoch AI · Aug 2025

GLM 4.6

340.8#37/42 open

Lab-reportedEpoch AI · Sep 2025

Only GLM 4.5 (4)

Only GLM 4.6 (4)

VRAM by quantization

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

QuantGLM 4.5GLM 4.6

Q2_K

GLM 4.5

153 GB131.2 GB file

32K 158 GB · 128K 173 GB

GLM 4.6

152 GB130.7 GB file

32K 157 GB · 128K 173 GB

Q3_K_S

GLM 4.5

157 GB155.0 GB file

32K 162 GB · 128K 178 GB

GLM 4.6

157 GB154.4 GB file

32K 162 GB · 128K 177 GB

Q3_K_M

GLM 4.5

175 GB171.3 GB file

32K 180 GB · 128K 196 GB

GLM 4.6

175 GB170.6 GB file

32K 179 GB · 128K 195 GB

Q4_0

GLM 4.5

180 GB203.0 GB file

32K 185 GB · 128K 200 GB

GLM 4.6

179 GB202.2 GB file

32K 184 GB · 128K 199 GB

Q4_K_M

GLM 4.5

216 GB216.5 GB file

32K 220 GB · 128K 236 GB

GLM 4.6

215 GB215.6 GB file

32K 220 GB · 128K 235 GB

Q5_K_M

GLM 4.5

256 GB254.2 GB file

32K 261 GB · 128K 276 GB

GLM 4.6

255 GB253.2 GB file

32K 260 GB · 128K 275 GB

Q6_K

GLM 4.5

296 GB294.4 GB file

32K 301 GB · 128K 317 GB

GLM 4.6

295 GB293.1 GB file

32K 300 GB · 128K 315 GB

Q8_0

GLM 4.5

359 GB381.0 GB file

32K 364 GB · 128K 379 GB

GLM 4.6

357 GB379.3 GB file

32K 362 GB · 128K 378 GB

14 more quants

IQ2_XXS

GLM 4.5

99.2 GB115.9 GB file

32K 104 GB · 128K 119 GB

GLM 4.6

98.7 GB115.4 GB file

32K 104 GB · 128K 119 GB

IQ2_XS

GLM 4.5

108 GB101.8 GB file

32K 113 GB · 128K 128 GB

GLM 4.6

108 GB101.0 GB file

32K 112 GB · 128K 128 GB

IQ2_S

GLM 4.5

113 GB102.7 GB file

32K 117 GB · 128K 133 GB

GLM 4.6

112 GB101.9 GB file

32K 117 GB · 128K 132 GB

IQ2_M

GLM 4.5

122 GB122.4 GB file

32K 126 GB · 128K 142 GB

GLM 4.6

121 GB121.9 GB file

32K 126 GB · 128K 141 GB

IQ3_XXS

GLM 4.5

139 GB145.2 GB file

32K 144 GB · 128K 160 GB

GLM 4.6

139 GB144.7 GB file

32K 144 GB · 128K 159 GB

IQ3_XS

GLM 4.5

148 GB148.9 GB file

32K 153 GB · 128K 169 GB

GLM 4.6

148 GB148.2 GB file

32K 153 GB · 128K 168 GB

IQ3_M

GLM 4.5

162 GB164.9 GB file

32K 167 GB · 128K 182 GB

GLM 4.6

161 GB164.3 GB file

32K 166 GB · 128K 181 GB

Q3_K_L

GLM 4.5

184 GB170.6 GB file

32K 189 GB · 128K 205 GB

GLM 4.6

183 GB169.9 GB file

32K 188 GB · 128K 204 GB

IQ4_XS

GLM 4.5

193 GB191.6 GB file

32K 198 GB · 128K 213 GB

GLM 4.6

192 GB190.7 GB file

32K 197 GB · 128K 213 GB

IQ4_NL

GLM 4.5

202 GB202.5 GB file

32K 207 GB · 128K 222 GB

GLM 4.6

201 GB201.6 GB file

32K 206 GB · 128K 222 GB

Q4_1

GLM 4.5

202 GB224.6 GB file

32K 207 GB · 128K 222 GB

GLM 4.6

201 GB223.6 GB file

32K 206 GB · 128K 222 GB

Q4_K_S

GLM 4.5

202 GB203.7 GB file

32K 207 GB · 128K 222 GB

GLM 4.6

201 GB202.8 GB file

32K 206 GB · 128K 222 GB

Q5_K_S

GLM 4.5

247 GB247.0 GB file

32K 252 GB · 128K 267 GB

GLM 4.6

246 GB245.9 GB file

32K 251 GB · 128K 266 GB

BF16

GLM 4.5

717 GB716.8 GB file

32K 722 GB · 128K 738 GB

GLM 4.6

714 GB713.7 GB file

32K 719 GB · 128K 734 GB

How to run each

GLM 4.5

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-4.5-GGUF:Q4_K_M

All ways to run GLM 4.5 →

GLM 4.6

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-4.6-GGUF:Q4_K_M

All ways to run GLM 4.6 →

Specifications

Specifications of GLM 4.5 and GLM 4.6
Spec	GLM 4.5	GLM 4.6
Publisher	Z.ai	Z.ai
Parameters	358.3B	356.8B
Active parameters	36B per token	34B per token
Architecture	Glm4MoeForCausalLM	Glm4MoeForCausalLM
Context	128K tokens	198K tokens
Modalities	Chat, Function-calling	Chat, Function-calling
License	MIT	MIT
Released	Jul 2025	Sep 2025

Frequently Asked Questions

Which is better, GLM 4.5 or GLM 4.6?

GLM 4.6 leads llmrun Score 103.1 to 100.9 (ranges overlap); neither fits 24 GB. Choose GLM 4.6 for higher llmrun Score and ahead on the benchmarks.

Which needs less VRAM, GLM 4.5 or GLM 4.6?

At Q4_K_M, GLM 4.5 requires 215.6 GB while GLM 4.6 needs 214.7 GB, making GLM 4.6 the easier model to run on your local setup.

Can I run GLM 4.5 or GLM 4.6 on a 16 GB GPU?

GLM 4.5 does not fit (smallest quant needs 101.4 GB); GLM 4.6 does not fit (smallest quant needs 101 GB).

Which has a longer context window, GLM 4.5 or GLM 4.6?

GLM 4.5 supports 131,072 tokens and GLM 4.6 supports 202,752 tokens.