GLM-5.3-Flash @ DGX Station GB300: ~206 tok/s (single stream), 1M context
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
Hey all!
I'm finally doing some cool stuff with my "thinking heater" (h/t u/-TV-Stand-). I'm still experimenting with GLM-5.2 (in anticipation of 5.3 coming tomorrow, I hope!) and things are very cool so far. With the release of GLM-5.3-flash, I decided to play with it on the 'tation.
I decided to go with NVFP4 because Blackwell and that it would fit amazingly inside the HBM3e. And it most definitely flies.... 206 tok/s single stream (I didn't bother to check several streams yet).
If you ever want to run it inside your 'tation, this is how I got it done:
docker run -d --name vllm-glm-5.3-flash \ --gpus all \ -p 8001:8001 \ -v /models:/models \ -e VLLM_KV_CACHE_LAYOUT=HND \ -e VLLM_WEIGHT_OFFLOADING_DISABLE_PIN_MEMORY=1 \ -e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \ vllm/vllm-openai:glm53-flash-arm64-cu130 \ serve \ --model /models/huggingface-cache/hub/models--LibertAIDAI--GLM-5.3-Flash-NVFP4 \ --tensor-parallel-size 1 \ --gpu-memory-utilization 0.92 \ --max-model-len 1048576 \ --dtype auto \ --compilation-config '{"mode":3}' \ --enable-prefix-caching \ --max-num-seqs 4 \ --max-num-batched-tokens 16384 \ --trust-remote-code \ --tool-call-parser glm47 \ --enable-auto-tool-choice \ --reasoning-parser glm45 \ --moe-backend marlin \ --speculative-config '{"method":"mtp","num_speculative_tokens":3}' \ --override-generation-config '{"temperature":1.0,"top_p":0.95}' \ --attention-config '{"use_fp4_indexer_cache": true}' \ --safetensors-load-strategy prefetch \ --served-model-name glm-5.3-flash \ --host 0.0.0.0 \ --port 8001 Gotcha: this image has a bug and won't download the model on its own. Auto-download fails, so you have to point --model at a pre-downloaded local folder (as above) rather than a bare HF repo id. You need the weights on disk first.
Soon: more benchmarks!
[link] [comments]
More from r/LocalLLaMA
-
NVIDIA shipped OpenShell, an open source sandbox that gives local and open agents real runtime limits instead of prompt rules. Over 100 firms joined the safety stack. OpenAI did not.
Sep 28
-
3090 for $1500???
Sep 28
-
modified qwen 3.8 27b modifies windows credential dumper to bypass EDR detection
Sep 28
-
Minisforum MS-S1 MAX-P495 @ €7.799,00
Sep 28
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.