Model reference · open weights
GLM-5.3-Flash is an open-weight language model from RedHatAI. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Maker | RedHatAI |
|---|---|
| Type | Language models |
| Task | Vision + text |
| Parameters (lead) | 169.1B |
| Runs with | transformers |
| Based on | zai-org/GLM-5.3-Flash |
| Released | 2026-08-27 |
| Popularity | 10k downloads / month |
| Licence | Unknown |
About
This model is a quantized version of zai-org/GLM-5.3-Flash.
This model was obtained by quantizing the weights of zai-org/GLM-5.3-Flash to NVFP4, ready for inference with vLLM.
Weights are quantized to FP4 with a group size of 16, and activations are quantized to FP4 with local per-group scaling. Only the weights and activations of the linear operators within transformer blocks are quantized using LLM Compressor. Vision tower, embedding, and output head layers are kept in their original precision.
docker run --gpus all \
--privileged --ipc=host -p 8000:8000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
-e VLLM_ENGINE_READY_TIMEOUT_S=3600 \
vllm/vllm-openai:glm53-flash RedHatAI/GLM-5.3-Flash-NVFP4 \
--tensor-parallel-size 4 \
--no-enable-flashinfer-autotune \
--tool-call-parser glm47 \
--enable-auto-tool-choice \
--reasoning-parser glm45
docker run --gpus all \
--privileged --ipc=host -p 8000:8000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
-e VLLM_ENGINE_READY_TIMEOUT_S=3600 \
-e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
vllm/vllm-openai:glm53-flash RedHatAI/GLM-5.3-Flash-NVFP4 \
--tensor-parallel-size 4 \
--no-enable-flashinfer-autotune \
--tool-call-parser glm47 \
--enable-auto-tool-choice \
--reasoning-parser glm45 \
--gpu-memory-utilization 0.85 \
--disable-custom-all-reduce \
--speculative-config '{"method":"mtp","num_speculative_tokens":5}'
| Benchmark | Metric | Avg Score |
|---|---|---|
| GPQA Diamond | gpqa_pass@k:k=1 (3 seeds) | 90.57% |
| AIME25 | pass@k:k=1&n=1 (8 seeds) | 86.67% |
| GSM8K Platinum CoT | exact_match,strict-match (3 seeds) | 97.74% |
| MATH-500 | pass@k:k=1&n=1 (3 seeds) | 94.87% |
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys redhatai-glm-5-3-flash for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (redhatai-glm-5-3-flash below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"redhatai-glm-5-3-flash","messages":[{"role":"user","content":"Hello"}]}'
Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.