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GLM-5.2 vs Kimi K2.6

Comparing VRAM requirements, performance, and capabilities for running these models locally with Ollama.

Parameters

753B

Context

977K

VRAM Range

274–821 GB

Recommended

Q2_K (274 GB)

ByZhipu AI·LicenseMIT
Parameters

1000B

Context

256K

VRAM Range

360–604 GB

Recommended

Q2_K (360 GB)

ByMoonshot AI·LicenseModified MIT

VRAM Requirements by Quantization

Side-by-side memory needs at each quality level.

QuantizationGLM-5.2Kimi K2.6Difference
Q4_K_M486 GB604 GB-118.0 GB
Q8_0821 GB

Capabilities

Feature support comparison.

CapabilityGLM-5.2Kimi K2.6
text generationYesYes
code generationYesYes
reasoningYesYes
multilingualYesYes
tool useYesYes
mathYes
visionYes

Benchmark Scores

Higher is better. Scores from published evaluations.

BenchmarkGLM-5.2Kimi K2.6
swe-bench-pro62.158.6
gpqa-diamond91.2
swe-bench-verified80.2

Hardware Compatibility

Can each model run at recommended quantization on common VRAM tiers?

VRAMGLM-5.2Kimi K2.6
8 GBNoNo
12 GBNoNo
16 GBNoNo
24 GBNoNo
32 GBNoNo
48 GBNoNo
64 GBNoNo
96 GBNoNo

Run GLM-5.2

ollama run glm-5.2:cloud

Run Kimi K2.6

ollama run kimi-k2.6:cloud

Check your exact hardware

Use the compatibility checker to see how each model performs on your specific GPU or Mac.

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