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+ +
+

+ 👋 Join our WeChat or Discord community. +
+ 📖 Check out the GLM-5 technical blog. +
+ 📍 Use GLM-5 API services on Z.ai API Platform. +
+ 👉 One click to GLM-5. +

+ +## Introduction + +We are launching GLM-5, targeting complex systems engineering and long-horizon agentic tasks. Scaling is still one of the most important ways to improve the intelligence efficiency of Artificial General Intelligence (AGI). Compared to GLM-4.5, GLM-5 scales from 355B parameters (32B active) to 744B parameters (40B active), and increases pre-training data from 23T to 28.5T tokens. GLM-5 also integrates DeepSeek Sparse Attention (DSA), largely reducing deployment cost while preserving long-context capacity. + +Reinforcement learning aims to bridge the gap between competence and excellence in pre-trained models. However, deploying it at scale for LLMs is a challenge due to the RL training inefficiency. To this end, we developed [slime](https://github.com/THUDM/slime), a novel **asynchronous RL infrastructure** that substantially improves training throughput and efficiency, enabling more fine-grained post-training iterations. With advances in both pre-training and post-training, GLM-5 delivers significant improvement compared to GLM-4.7 across a wide range of academic benchmarks and achieves best-in-class performance among all open-source models in the world on reasoning, coding, and agentic tasks, closing the gap with frontier models. + +## Benchmark + +| | GLM-5 | GLM-4.7 | DeepSeek-V3.2 | Kimi K2.5 | Claude Opus 4.5 | Gemini 3 Pro | GPT-5.2 (xhigh) | +| -------------------------------- | ---------------------- | --------- | ------------- |-----------| --------------- | ------------ | --------------- | +| HLE | 30.5 | 24.8 | 25.1 | 31.5 | 28.4 | 37.2 | 35.4 | +| HLE (w/ Tools) | 50.4 | 42.8 | 40.8 | 51.8 | 43.4* | 45.8* | 45.5* | +| AIME 2026 I | 92.7 | 92.9 | 92.7 | 92.5 | 93.3 | 90.6 | - | +| HMMT Nov. 2025 | 96.9 | 93.5 | 90.2 | 91.1 | 91.7 | 93.0 | 97.1 | +| IMOAnswerBench | 82.5 | 82.0 | 78.3 | 81.8 | 78.5 | 83.3 | 86.3 | +| GPQA-Diamond | 86.0 | 85.7 | 82.4 | 87.6 | 87.0 | 91.9 | 92.4 | +| SWE-bench Verified | 77.8 | 73.8 | 73.1 | 76.8 | 80.9 | 76.2 | 80.0 | +| SWE-bench Multilingual | 73.3 | 66.7 | 70.2 | 73.0 | 77.5 | 65.0 | 72.0 | +| Terminal-Bench 2.0 (Terminus 2) | 56.2 / 60.7 † | 41.0 | 39.3 | 50.8 | 59.3 | 54.2 | 54.0 | +| Terminal-Bench 2.0 (Claude Code) | 56.2 / 61.1 † | 32.8 | 46.4 | - | 57.9 | - | - | +| CyberGym | 43.2 | 23.5 | 17.3 | 41.3 | 50.6 | 39.9 | - | +| BrowseComp | 62.0 | 52.0 | 51.4 | 60.6 | 37.0 | 37.8 | - | +| BrowseComp (w/ Context Manage) | 75.9 | 67.5 | 67.6 | 74.9 | 67.8 | 59.2 | 65.8 | +| BrowseComp-Zh | 72.7 | 66.6 | 65.0 | 62.3 | 62.4 | 66.8 | 76.1 | +| τ²-Bench | 89.7 | 87.4 | 85.3 | 80.2 | 91.6 | 90.7 | 85.5 | +| MCP-Atlas (Public Set) | 67.8 | 52.0 | 62.2 | 63.8 | 65.2 | 66.6 | 68.0 | +| Tool-Decathlon | 38.0 | 23.8 | 35.2 | 27.8 | 43.5 | 36.4 | 46.3 | +| Vending Bench 2 | $4,432.12 | $2,376.82 | $1,034.00 | $1,198.46 | $4,967.06 | $5,478.16 | $3,591.33 | + +> *: refers to their scores of full set. +> +> †: A verified version of Terminal-Bench 2.0 that fixes some ambiguous instructions. +See footnote for more evaluation details. + +### Footnote + +* **Humanity’s Last Exam (HLE) & other reasoning tasks**: We evaluate with a maximum generation length of 131,072 tokens (`temperature=1.0, top_p=0.95, max_new_tokens=131072`). By default, we report the text-only subset; results marked with * are from the full set. We use GPT-5.2 (medium) as the judge model. For HLE-with-tools, we use a maximum context length of 202,752 tokens. +* **SWE-bench & SWE-bench Multilingual**: We run the SWE-bench suite with OpenHands using a tailored instruction prompt. Settings: `temperature=0.7, top_p=0.95, max_new_tokens=16384`, with a 200K context window. +* **BrowserComp**: Without context management, we retain details from the most recent 5 turns. With context management, we use the same discard-all strategy as DeepSeek-v3.2 and Kimi K2.5. +* **Terminal-Bench 2.0 (Terminus 2)**: We evaluate with the Terminus framework using `timeout=2h, temperature=0.7, top_p=1.0, max_new_tokens=8192`, with a 128K context window. Resource limits are capped at 16 CPUs and 32 GB RAM. +* **Terminal-Bench 2.0 (Claude Code)**: We evaluate in Claude Code 2.1.14 (think mode, default effort) with `temperature=1.0, top_p=0.95, max_new_tokens=65536`. We remove wall-clock time limits due to generation speed, while preserving per-task CPU and memory constraints. Scores are averaged over 5 runs. We fix environment issues introduced by Claude Code and also report results on a verified Terminal-Bench 2.0 dataset that resolves ambiguous instructions (see: [https://huggingface.co/datasets/zai-org/terminal-bench-2-verified](https://huggingface.co/datasets/zai-org/terminal-bench-2-verified)). +* **CyberGym**: We evaluate in Claude Code 2.1.18 (think mode, no web tools) with (`temperature=1.0, top_p=1.0, max_new_tokens=32000`) and a 250-minute timeout per task. Results are single-run Pass@1 over 1,507 tasks. +* **MCP-Atlas**: All models are evaluated in think mode on the 500-task public subset with a 10-minute timeout per task. We use Gemini 3 Pro as the judge model. +* **τ²-bench**: We add a small prompt adjustment in Retail and Telecom to avoid failures caused by premature user termination. For Airline, we apply the domain fixes proposed in the Claude Opus 4.5 system card. +* **Vending Bench 2**: Runs are conducted independently by [Andon Labs](https://andonlabs.com/evals/vending-bench-2). + + +## Serve GLM-5 Locally + +### Prepare environment + +vLLM, SGLang, and xLLM all support local deployment of GLM-5. A simple deployment guide is provided here. + ++ vLLM + + Using Docker as: + + ```shell + docker pull vllm/vllm-openai:nightly + ``` + + or using pip: + + ```shell + pip install -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly + ``` + + then upgrade transformers: + + ``` + pip install git+https://github.com/huggingface/transformers.git + ``` + ++ SGLang + + Using Docker as: + ```bash + docker pull lmsysorg/sglang:glm5-hopper # For Hopper GPU + docker pull lmsysorg/sglang:glm5-blackwell # For Blackwell GPU + ``` + +### Deploy + ++ vLLM + + ```shell + vllm serve zai-org/GLM-5-FP8 \ + --tensor-parallel-size 8 \ + --gpu-memory-utilization 0.85 \ + --speculative-config.method mtp \ + --speculative-config.num_speculative_tokens 1 \ + --tool-call-parser glm47 \ + --reasoning-parser glm45 \ + --enable-auto-tool-choice \ + --served-model-name glm-5-fp8 + ``` + + Check the [recipes](https://github.com/vllm-project/recipes/blob/main/GLM/GLM5.md) for more details. + ++ SGLang + + ```shell + python3 -m sglang.launch_server \ + --model-path zai-org/GLM-5-FP8 \ + --tp-size 8 \ + --tool-call-parser glm47 \ + --reasoning-parser glm45 \ + --speculative-algorithm EAGLE \ + --speculative-num-steps 3 \ + --speculative-eagle-topk 1 \ + --speculative-num-draft-tokens 4 \ + --mem-fraction-static 0.85 \ + --served-model-name glm-5-fp8 + ``` + + Check the [sglang cookbook](https://cookbook.sglang.io/autoregressive/GLM/GLM-5) for more details. + ++ xLLM and other Ascend NPU + + Please check the deployment guide [here](https://github.com/zai-org/GLM-5/blob/main/example/ascend.md). + + +## Citation + +Our technical report is coming soon. \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000000000000000000000000000000000000..2ab98ef068d62829d17c5ade1827b9f013fa2bbf --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,86 @@ +[gMASK] +{%- if tools -%} +<|system|> +# Tools + +You may call one or more functions to assist with the user query. + +You are provided with function signatures within XML tags: + +{% for tool in tools %} +{{ tool | tojson(ensure_ascii=False) }} +{% endfor %} + + +For each function call, output the function name and arguments within the following XML format: +{function-name}{arg-key-1}{arg-value-1}{arg-key-2}{arg-value-2}...{%- endif -%} +{%- 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 }} + {%- endif -%} + {%- endfor -%} + {%- else -%} + {{- content }} + {%- 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 reasoning_content = '' %} +{%- set content = visible_text(m.content) %} +{%- if m.reasoning_content is string %} + {%- set reasoning_content = m.reasoning_content %} +{%- else %} + {%- if '' in content %} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') %} + {%- set content = content.split('')[-1].lstrip('\n') %} + {%- endif %} +{%- endif %} +{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content -%} +{{ '' + reasoning_content.strip() + ''}} +{%- else -%} +{{ '' }} +{%- 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 %} +{{- '' + tc.name -}} +{% set _args = tc.arguments %}{% for k, v in _args.items() %}{{ k }}{{ v | tojson(ensure_ascii=False) if v is not string else v }}{% endfor %}{% endfor %} +{% endif %} +{%- elif m.role == 'tool' -%} +{%- if m.content is string -%} +{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|observation|>' }} +{%- endif %} +{{- '' }} +{{- m.content }} +{{- '' }} +{%- else -%} +<|observation|>{% for tr in m.content %} +{{ tr.output if tr.output is defined else tr }}{% endfor -%} +{% endif -%} +{%- elif m.role == 'system' -%} +<|system|>{{ visible_text(m.content) }} +{%- endif -%} +{%- endfor -%} +{%- if add_generation_prompt -%} + <|assistant|>{{- '' if (enable_thinking is defined and not enable_thinking) else '' -}} +{%- endif -%} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000000000000000000000000000000000000..a34ad26ab36785f99d45866c1e9fe145003638ef --- /dev/null +++ b/config.json @@ -0,0 +1,59 @@ +{ + "architectures": [ + "GlmMoeDsaForCausalLM" + ], + "attention_bias": false, + 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