Head to head

Kimi K3 vs GLM 5.3

Kimi K3 scores higher on 3 of the 4 benchmarks both models publish. The widest gap is on Humanity's Last Exam (with tools), where GLM 5.3 leads by 6.5 points. Both have open weights; GLM 5.3 is far lighter to host, needing about 520 GB at 4-bit against 1.9 TB for Kimi K3.

Kimi K3Moonshot AI · OpenLLM Buddy catalog90.6compositeGLM 5.3Z.ai (Zhipu) · Open weights82.7composite

Shared benchmarks

Raw published scores; the higher score on each row is highlighted. LMArena Elo is a human-preference vote and is not counted as a win.

Should you pick Kimi K3 or GLM 5.3?

Pick Kimi K3 if…

  • You want it running in minutes on a dedicated GPU through OpenLLM Buddy, in an uncensored build.

Pick GLM 5.3 if…

  • You care most about Humanity's Last Exam (with tools), where it scores at least 2 points higher.
  • You want the lighter model to host: about 520 GB at 4-bit against 1.9 TB.
  • You need fast responses: about 88 tokens per second through APIs, against 66.
  • Cost matters: $4.40 per million output tokens against $15.00.
  • You need a permissive license: it ships under GLM-5.3 License (custom; arena.ai lists MIT).

Hardware and cost to run

Kimi K3

Even at 4-bit it needs about 1.9 TB (Multiple nodes (over 1.1 TB)), well beyond a home workstation, so most people run it on rented multi-GPU servers. Full BF16 precision needs about 6.4 TB (Multiple nodes (over 1.1 TB)).

On OpenLLM Buddy: Kimi-K3-Uncensored-GGUF runs on 8× H100 80GB as a GGUF quantized build, with an OpenAI-compatible API and no per-token fees. Prices start at $422 USD for 11 hours.

Deploy Kimi K3
Full GPU memory table for Kimi K3

GLM 5.3

Even at 4-bit it needs about 520 GB (4× H200 (564 GB)), well beyond a home workstation, so most people run it on rented multi-GPU servers. Full BF16 precision needs about 1.7 TB (Multiple nodes (over 1.1 TB)).

Full GPU memory table for GLM 5.3

Category profile

Category index uses every test each model reports, not only the shared ones.

ReasoningCodingAgenticKnowledge
Kimi K3GLM 5.3
Reasoning82.480.6
Coding97.578.3
Agentic89.589.3
Knowledge93.1—

Specs side by side

Kimi K3GLM 5.3
LabMoonshot AIZ.ai (Zhipu)
WeightsOpenOpen
Released2026-07-272026-08-14
Parameters2.8T total, 104B active (MoE)753B total, 40B active (MoE)
Context1M1M
LicenseKimi K3 License (custom)GLM-5.3 License (custom; arena.ai lists MIT)
4-bit memory1.9 TB · Multiple nodes (over 1.1 TB)520 GB · 4× H200 (564 GB)
API price$3.00 in / $15.00 out per 1M tokens$1.40 in / $4.40 out per 1M tokens
API speed66 tok/s88 tok/s

Related comparisons

Sources

ModelTestScoreSettingSource
Kimi K3GPQA Diamond93.5max reasoning effortKimi K3 model card (Hugging Face)
GLM 5.3GPQA Diamond91.7GLM 5.3 (max); competitor comparison columnMeta Muse Spark Open model card (comparison column)
Kimi K3Humanity's Last Exam43.5HLE-Full, no tools, max effortKimi K3 model card (Hugging Face)
GLM 5.3Humanity's Last Exam42.3no tools, text-only subset (2,158 q); competitor comparison columnMiniMax M3.1 Flash model card (comparison column)
Kimi K3Humanity's Last Exam (with tools)56.0HLE-Full, with tools, max effortKimi K3 model card (Hugging Face)
GLM 5.3Humanity's Last Exam (with tools)62.5with toolsHugging Face model card (GLM-5.3)
Kimi K3Terminal-Bench88.3Terminal-Bench 2.1, max effortKimi K3 model card (Hugging Face)
GLM 5.3Terminal-Bench88.2Terminal-Bench 2.1Hugging Face model card (GLM-5.3)
Kimi K3LMArena Text Elo1488LMArena text overall, 'Kimi K3 (Max)', ±4, as of 2026-10-27Arena (LMArena) text leaderboard
GLM 5.3LMArena Text Elo1481GLM-5.3 (Max), ±5, board dated 2026-10-27LMArena (arena.ai) text leaderboard

Scores are published results from model cards, lab reports, and public leaderboards, each linked to its source. Settings such as thinking mode or test version differ between sources and are shown next to each score. OpenLLM Buddy catalog models are uncensored fine-tunes; their scores are those of the official base model. Data collected 2026-10-30. How the index works