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ModelTape / Models / GLM 5.3 BF16
Z.ai · open-weights

GLM 5.3 BF16

GLM 5.3 BF16 is an open-weights language model from Z.ai, released August 25, 2026. It has 753B parameters (mixture-of-experts, 51B active). The context window is 1M tokens.

Check it against your own PC →

Lab
Z.ai
Released
August 25, 2026
Weights
Open glm-5.3
Parameters
753B MoE · 51B active
Context
1M
Price / M tokens
–
Epoch ECI
not yet rated

Can you run GLM 5.3 BF16 locally?

Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMToo large––––
8 GB VRAMToo large––––
12 GB VRAMToo large––––
16 GB VRAMToo large––––
24 GB VRAMToo large––––
32 GB VRAMToo large––––

Ready-made quantizations on Hugging Face: AesSedai/GLM-5.3-GGUF · 0ppxnhximxr/GLM-5.3-GGUF · Inferact/GLM-5.3-NVFP4 · RadixArk/GLM-5.3-NVFP4 · modal-labs/GLM-5.3-NVFP4 · mlx-community/GLM-5.3-4bit

Benchmark results

Epoch AI has not published results for GLM 5.3 BF16 yet. New models are usually evaluated within days to weeks.

Links

Hugging Face: zai-org/GLM-5.3-BF16

More from Z.ai

GLM-5.3-FlashX · GLM 5.3 Flash BF16 · GLM-5.3-Flash · GLM-5.3 · GLM-5.2 · GLM-5.1 · GLM-5V-Turbo · GLM-5-Turbo

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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