Text Generation
Transformers
Safetensors
English
Chinese
glm5_next
image-text-to-text
conversational
Eval Results
fp8
Instructions to use zai-org/GLM-5.3-Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/GLM-5.3-Flash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zai-org/GLM-5.3-Flash") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("zai-org/GLM-5.3-Flash") model = AutoModelForMultimodalLM.from_pretrained("zai-org/GLM-5.3-Flash", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zai-org/GLM-5.3-Flash with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zai-org/GLM-5.3-Flash" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/GLM-5.3-Flash", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zai-org/GLM-5.3-Flash
- SGLang
How to use zai-org/GLM-5.3-Flash with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "zai-org/GLM-5.3-Flash" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/GLM-5.3-Flash", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "zai-org/GLM-5.3-Flash" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/GLM-5.3-Flash", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use zai-org/GLM-5.3-Flash with Docker Model Runner:
docker model run hf.co/zai-org/GLM-5.3-Flash
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{%- set effective_reasoning_effort = reasoning_effort if reasoning_effort is defined and reasoning_effort in ['low', 'high'] else 'max' -%}
{%- if effective_reasoning_effort is not none -%}<|system|>Reasoning Effort: {{ effective_reasoning_effort | capitalize }}{%- endif -%}
{%- set clear_thinking = clear_thinking if clear_thinking is defined else false -%}
{%- if tools -%}
{%- macro tool_to_json(tool) -%}
{%- set ns_tool = namespace(first=true) -%}
{{ '{' -}}
{%- for k, v in tool.items() -%}
{%- if k != 'defer_loading' and k != 'strict' -%}
{%- if not ns_tool.first -%}{{- ', ' -}}{%- endif -%}
{%- set ns_tool.first = false -%}
"{{ k }}": {{ v | tojson(ensure_ascii=False) }}
{%- endif -%}
{%- endfor -%}
{{- '}' -}}
{%- endmacro -%}
{%- macro tool_references_to_response(refs) -%}
{{- '<tool_response><tools>\n' -}}
{%- for tr in refs -%}
{%- for tool in tools -%}
{%- if 'function' in tool -%}
{%- set tool = tool['function'] -%}
{%- endif -%}
{%- if tool.name == tr.name -%}
{{- tool_to_json(tool) + '\n' -}}
{%- endif -%}
{%- endfor -%}
{%- endfor -%}
{{- '</tools></tool_response>' -}}
{%- endmacro -%}
<|system|>
# Tools
You may call one or more functions to assist with the user query.
You are provided with function signatures within <tools></tools> XML tags:
<tools>
{% for tool in tools %}
{%- if 'function' in tool -%}
{%- set tool = tool['function'] -%}
{%- endif -%}
{% if tool.defer_loading is not defined or not tool.defer_loading %}
{{ tool_to_json(tool) }}
{% endif %}
{% endfor %}
</tools>
For each function call, output the function name and arguments within the following XML format:
<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
{%- macro emit_image() -%}<|begin_of_image|><|image|><|end_of_image|>{%- endmacro -%}
{%- macro emit_video() -%}<|begin_of_video|><|video|><|end_of_video|>{%- endmacro -%}
{%- macro emit_audio() -%}<|begin_of_audio|><|end_of_audio|>{%- endmacro -%}
{%- macro visible_text(content) -%}
{%- if content is string -%}
{{- content -}}
{%- elif content is iterable and content is not mapping -%}
{%- for item in content -%}
{%- if item is mapping and item.type == 'text' -%}
{{- item.text -}}
{%- elif item is string -%}
{{- item -}}
{%- elif item is mapping and item.type in ['image', 'image_url'] -%}
{{- emit_image() -}}
{%- elif item is mapping and item.type in ['video', 'video_url'] -%}
{{- emit_video() -}}
{%- elif item is mapping and item.type in ['audio', 'audio_url', 'input_audio'] -%}
{{- emit_audio() -}}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{{- content }}
{%- endif -%}
{%- endmacro -%}
{%- macro tool_response(text) -%}
{{- '<tool_response>' + text + '</tool_response>' -}}
{%- endmacro -%}
{%- macro render_tool_response(m) -%}
{%- if m.content is string -%}
{{- tool_response(m.content) -}}
{%- elif m.content and m.content is not mapping and m.content.0.type == "tool_reference" -%}
{{- tool_references_to_response(m.content) -}}
{%- elif is_list_of_outputs(m) -%}
{%- for tr in m.content -%}
{%- if tr.output is iterable and tr.output is not string and tr.output is not mapping and tr.output and tr.output.0.type == "tool_reference" -%}
{{- tool_references_to_response(tr.output) -}}
{%- else -%}
{{- tool_response(visible_text(tr.output)) -}}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{{- tool_response(visible_text(m.content)) -}}
{%- endif -%}
{%- endmacro -%}
{%- macro id_of(obj) -%}
{%- if obj.tool_call_id -%}
{{- obj.tool_call_id -}}
{%- elif obj.id -%}
{{- obj.id -}}
{%- endif -%}
{%- endmacro -%}
{%- macro is_list_of_outputs(m) -%}
{%- if m.content and m.content.0.output is defined -%}1{%- endif -%}
{%- endmacro -%}
{%- macro has_dup_tool_result_id(lo, hi, target) -%}
{%- set ns_cnt = namespace(n=0) -%}
{%- for k in range(lo, hi + 1) -%}
{%- set m = messages[k] -%}
{%- if is_list_of_outputs(m) -%}
{%- for entry in m.content -%}
{%- if id_of(entry) == target -%}
{%- set ns_cnt.n = ns_cnt.n + 1 -%}
{%- endif -%}
{%- endfor -%}
{%- elif id_of(m) == target -%}
{%- set ns_cnt.n = ns_cnt.n + 1 -%}
{%- endif -%}
{%- if ns_cnt.n > 1 -%}{%- break -%}{%- endif -%}
{%- endfor -%}
{%- if ns_cnt.n > 1 -%}1{%- endif -%}
{%- endmacro -%}
{%- macro tc_id_exists(tcs, target) -%}
{%- set ns_f = namespace(found=false) -%}
{%- for tc in tcs -%}
{%- if id_of(tc) == target -%}
{%- set ns_f.found = true -%}
{%- break -%}
{%- endif -%}
{%- endfor -%}
{%- if ns_f.found -%}1{%- endif -%}
{%- endmacro -%}
{%- set ns = namespace(last_user_index=-1) -%}
{%- for m in messages %}
{%- if m.role == 'user' %}
{%- set ns.last_user_index = loop.index0 -%}
{%- endif %}
{%- endfor %}
{%- for m in messages -%}
{%- if m.role == 'user' -%}<|user|>{{ visible_text(m.content) }}
{%- elif m.role == 'assistant' -%}
<|assistant|>
{%- set content = visible_text(m.content) %}
{%- if m.reasoning_content is string %}
{%- set reasoning_content = m.reasoning_content %}
{%- elif '</think>' in content %}
{%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] %}
{%- set content = content.split('</think>')[-1] %}
{%- endif %}
{%- if (not clear_thinking or loop.index0 > ns.last_user_index) and reasoning_content is defined -%}
{{ '<think>' + reasoning_content + '</think>'}}
{%- else -%}
{{ '<think></think>' }}
{%- endif -%}
{%- if content.strip() -%}
{{ content.strip() }}
{%- endif -%}
{% if m.tool_calls %}
{% for tc in m.tool_calls %}
{%- if tc.function %}
{%- set tc = tc.function %}
{%- endif %}
{{- '<tool_call>' + tc.name -}}
{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
{% endif %}
{%- elif m.role == 'tool' -%}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|observation|>' -}}
{%- set block_start = loop.index0 -%}
{%- set ns_blk = namespace(end=block_start) -%}
{%- for j in range(block_start, messages|length) -%}
{%- if messages[j].role == 'tool' -%}
{%- set ns_blk.end = j -%}
{%- else -%}
{%- break -%}
{%- endif -%}
{%- endfor -%}
{%- set ns_a = namespace(tool_calls=none) -%}
{%- if block_start > 0 and messages[block_start - 1].role == 'assistant' and messages[block_start - 1].tool_calls -%}
{%- set ns_a.tool_calls = messages[block_start - 1].tool_calls -%}
{%- endif -%}
{%- set ns_chk = namespace(can_sort=true) -%}
{%- if not ns_a.tool_calls -%}
{%- set ns_chk.can_sort = false -%}
{%- else -%}
{%- for k in range(block_start, ns_blk.end + 1) -%}
{%- set m = messages[k] -%}
{%- if is_list_of_outputs(m) -%}
{%- for entry in m.content -%}
{%- set eid = id_of(entry) -%}
{%- if not eid -%}
{%- set ns_chk.can_sort = false -%}
{%- elif has_dup_tool_result_id(block_start, ns_blk.end, eid) -%}
{%- set ns_chk.can_sort = false -%}
{%- elif not tc_id_exists(ns_a.tool_calls, eid) -%}
{%- set ns_chk.can_sort = false -%}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{%- set tk_id = id_of(m) -%}
{%- if not tk_id -%}
{%- set ns_chk.can_sort = false -%}
{%- elif has_dup_tool_result_id(block_start, ns_blk.end, tk_id) -%}
{%- set ns_chk.can_sort = false -%}
{%- elif not tc_id_exists(ns_a.tool_calls, tk_id) -%}
{%- set ns_chk.can_sort = false -%}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- for i in range(ns_a.tool_calls | length) -%}
{%- set tc_id = id_of(ns_a.tool_calls[i]) -%}
{%- if not tc_id -%}
{%- set ns_chk.can_sort = false -%}
{%- endif -%}
{%- for j in range(i + 1, ns_a.tool_calls | length) -%}
{%- if id_of(ns_a.tool_calls[j]) == tc_id -%}
{%- set ns_chk.can_sort = false -%}
{%- endif -%}
{%- endfor -%}
{%- endfor -%}
{%- endif -%}
{%- if ns_chk.can_sort -%}
{%- for tc in ns_a.tool_calls -%}
{%- set tc_id = id_of(tc) -%}
{%- for k in range(block_start, ns_blk.end + 1) -%}
{%- set m = messages[k] -%}
{%- if is_list_of_outputs(m) -%}
{%- for entry in m.content -%}
{%- set eid = id_of(entry) -%}
{%- if eid == tc_id -%}
{%- if entry.output is iterable and entry.output is not string and entry.output is not mapping and entry.output and entry.output.0.type == "tool_reference" -%}
{{- tool_references_to_response(entry.output) -}}
{%- else -%}
{{- tool_response(visible_text(entry.output)) -}}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- else -%}
{%- set tk_id = id_of(m) -%}
{%- if tk_id == tc_id -%}
{{- render_tool_response(m) -}}
{%- endif -%}
{%- endif -%}
{%- endfor -%}
{%- endfor -%}
{%- else -%}
{%- for k in range(block_start, ns_blk.end + 1) -%}
{{- render_tool_response(messages[k]) -}}
{%- endfor -%}
{%- endif -%}
{% endif -%}
{%- elif m.role == 'system' -%}
<|system|>{{ visible_text(m.content) }}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
<|assistant|>{{- '<think>' -}}
{%- endif -%}
|