Model Intelligence Sheet
zsjtiger/glm-4.7-flash-claude-opus-4.5-high-reasoning-distill-gguf overview
This model was trained on a small reasoning dataset of Claude Opus 4.5, with reasoning effort set to High. ---
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| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| glm-4.7-flash-claude-4.5-opus.bf16.gguf | GGUF | BF16 | 55.79 GB | Download |
| glm-4.7-flash-claude-4.5-opus.f16.gguf | GGUF | F16 | 55.79 GB | Download |
| glm-4.7-flash-claude-4.5-opus.iq2_m.gguf | GGUF | IQ2_M | 9.22 GB | Download |
| glm-4.7-flash-claude-4.5-opus.iq3_m.gguf | GGUF | IQ3_M | 12.30 GB | Download |
| glm-4.7-flash-claude-4.5-opus.iq3_xs.gguf | GGUF | IQ3_XS | 11.50 GB | Download |
| glm-4.7-flash-claude-4.5-opus.iq4_nl.gguf | GGUF | IQ4_NL | 15.79 GB | Download |
| glm-4.7-flash-claude-4.5-opus.iq4_xs.gguf | GGUF | IQ4_XS | 14.93 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q3_k_m.gguf | GGUF | Q3_K_M | 13.39 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q3_k_s.gguf | GGUF | Q3_K_S | 12.14 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q4_k_m.gguf | GGUF | Q4_K_M | 16.89 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q5_k_m.gguf | GGUF | Q5_K_M | 19.80 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q6_k.gguf | GGUF | Q6_K | 22.92 GB | Download |
| glm-4.7-flash-claude-4.5-opus.q8_0.gguf | GGUF | — | 29.66 GB | Download |
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{
"metadata": {},
"card_data": {
"base_model": "TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill",
"tags": [
"text-generation-inference",
"gguf",
"llama.cpp",
"unsloth",
"glm4_moe_lite"
],
"license": "apache-2.0",
"datasets": [
"TeichAI/claude-4.5-opus-high-reasoning-250x"
],
"frontmatter": {
"base_model": "TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill",
"tags": [
"text-generation-inference",
"gguf",
"llama.cpp",
"unsloth",
"glm4_moe_lite"
],
"license": "apache-2.0",
"datasets": [
"TeichAI/claude-4.5-opus-high-reasoning-250x"
]
},
"hero_image_url": "results_bar_chart.png",
"summary": "This model was trained on a small reasoning dataset of **Claude Opus 4.5**, with reasoning effort set to High. ---",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill\ntags:\n- text-generation-inference\n- gguf\n- llama.cpp\n- unsloth\n- glm4_moe_lite\nlicense: apache-2.0\ndatasets:\n- TeichAI/claude-4.5-opus-high-reasoning-250x\n---\n\n# GLM 4.7 Flash x Claude 4.5 Opus (High Reasoning)\n\nThis model was trained on a small reasoning dataset of **Claude Opus 4.5**, with reasoning effort set to High.\n\n- 🧬 Datasets:\n - `TeichAI/claude-4.5-opus-high-reasoning-250x`\n\n- 🏗 Base Model:\n - `unsloth/GLM-4.7-Flash`\n \n- ⚡ Use cases:\n - Coding\n - Science\n - Deep Research\n\n- ∑ Stats (Dataset)\n - Costs: $ 52.30 (USD)\n - Total tokens (input + output): 2.13 M\n\n---\n\n## How to run\n\nFor specific instructions/commands to serve this model locally using vLLM, SGLang, or transformers please see [the instructions from the original model's card](https://huggingface.co/unsloth/GLM-4.7-Flash#serve-glm-47-flash-locally)\n\nFor detailed instructions getting started with Llama.cpp please refer to [the unsloth guide](https://unsloth.ai/docs/models/glm-4.7-flash)\n\n### Sampling Parameters\n\nz-ai recommends the following sampling parameters for this model:\n\n| Default Settings (Most Tasks) | Terminal Bench, SWE Bench Verified |\n| ------------------------------------------------------------------ | ------------------------------------------------------------------ |\n| **temperature = 1.0** | **temperature = 0.7** |\n| **top_p = 0.95** | **top_p = 1.0** |\n| repeat penalty = disabled or 1.0 | repeat penalty = disabled or 1.0 |\n\n* For general use-case: `--temp 1.0 --top-p 0.95`\n* For tool-calling: `--temp 0.7 --top-p 1.0`\n* If using llama.cpp, set `--min-p 0.01` as llama.cpp's default is 0.05\n* Sometimes you'll need to experiment what numbers work best for your use-case.\n\nIf you experience any issues with these parameters, some users have reported better results when lowering temperature to 0.5-0.6\n\n---\n\n## Benchmarks\n\n\n\n### Model Comparison vs Base\n\n\n\n- Base model: zai-org/GLM-4.7-Flash\n\n| Benchmark | Base Score | Distilled Score | Delta | Delta % |\n|:----------------------|-------------:|--------------:|-------------:|------------:|\n| arc_challenge | **0.224403** | 0.217577 | -0.00682594 | -0.0304183 |\n| gpqa_diamond_zeroshot | 0.262626 | **0.292929** | 0.030303 | 0.115385 |\n| hellaswag | **0.257817** | 0.256722 | -0.0010954 | -0.00424874 |\n| ifeval | 0.109057 | **0.112754** | 0.00369686 | 0.0338983 |\n| mmlu | 0.229454 | **0.240706** | 0.011252 | 0.0490379 |\n| truthfulqa_mc2 | **0.467552** | 0.466805 | -0.000747457 | -0.00159866 |\n| winogrande | 0.468824 | **0.504341** | 0.035517 | 0.0757576 |\n\n### Aggregate Comparison\n\n| Benchmarks Compared | Wins vs Base | Ties vs Base | Losses vs Base | Avg Delta |\n|----------------------:|---------------:|---------------:|-----------------:|------------:|\n| 7 | 4 | 0 | 3 | 0.0103 |\n\n### Detailed Results\n\n| Model | Benchmark | Score | Total Questions | Total Correct |\n|:-------------------------------------------------------------|:----------------------|---------:|------------------:|----------------:|\n| zai-org/GLM-4.7-Flash | winogrande | 0.468824 | 1267 | 594 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | winogrande | 0.504341 | 1267 | 639 |\n| zai-org/GLM-4.7-Flash | arc_challenge | 0.224403 | 1172 | 263 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | arc_challenge | 0.217577 | 1172 | 255 |\n| zai-org/GLM-4.7-Flash | hellaswag | 0.257817 | 10042 | 2589 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | hellaswag | 0.256722 | 10042 | 2578 |\n| zai-org/GLM-4.7-Flash | truthfulqa_mc2 | 0.467552 | 817 | 381 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | truthfulqa_mc2 | 0.466805 | 817 | 381 |\n| zai-org/GLM-4.7-Flash | mmlu | 0.229454 | 14042 | 3222 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | mmlu | 0.240706 | 14042 | 3380 |\n| zai-org/GLM-4.7-Flash | ifeval | 0.109057 | 541 | 59 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | ifeval | 0.112754 | 541 | 61 |\n| zai-org/GLM-4.7-Flash | gpqa_diamond_zeroshot | 0.262626 | 198 | 52 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | gpqa_diamond_zeroshot | 0.292929 | 198 | 58 |\n\n\n### MMLU Subject Breakdown\n\n\n\n#### MMLU Detailed Results\n\n| Model | Subject | Benchmark | Score | Total Questions | Total Correct |\n|:-------------------------------------------------------------|:------------------------------------|:-----------------------------------------|---------:|------------------:|----------------:|\n| zai-org/GLM-4.7-Flash | formal_logic | mmlu_formal_logic | 0.285714 | 126 | 36 |\n| zai-org/GLM-4.7-Flash | high_school_european_history | mmlu_high_school_european_history | 0.218182 | 165 | 36 |\n| zai-org/GLM-4.7-Flash | high_school_us_history | mmlu_high_school_us_history | 0.25 | 204 | 51 |\n| zai-org/GLM-4.7-Flash | high_school_world_history | mmlu_high_school_world_history | 0.270042 | 237 | 63 |\n| zai-org/GLM-4.7-Flash | international_law | mmlu_international_law | 0.239669 | 121 | 29 |\n| zai-org/GLM-4.7-Flash | jurisprudence | mmlu_jurisprudence | 0.259259 | 108 | 28 |\n| zai-org/GLM-4.7-Flash | logical_fallacies | mmlu_logical_fallacies | 0.220859 | 163 | 36 |\n| zai-org/GLM-4.7-Flash | moral_disputes | mmlu_moral_disputes | 0.248555 | 346 | 86 |\n| zai-org/GLM-4.7-Flash | moral_scenarios | mmlu_moral_scenarios | 0.237989 | 895 | 213 |\n| zai-org/GLM-4.7-Flash | philosophy | mmlu_philosophy | 0.186495 | 311 | 58 |\n| zai-org/GLM-4.7-Flash | prehistory | mmlu_prehistory | 0.216049 | 324 | 70 |\n| zai-org/GLM-4.7-Flash | professional_law | mmlu_professional_law | 0.245763 | 1534 | 377 |\n| zai-org/GLM-4.7-Flash | world_religions | mmlu_world_religions | 0.321637 | 171 | 55 |\n| zai-org/GLM-4.7-Flash | business_ethics | mmlu_business_ethics | 0.3 | 100 | 30 |\n| zai-org/GLM-4.7-Flash | clinical_knowledge | mmlu_clinical_knowledge | 0.215094 | 265 | 57 |\n| zai-org/GLM-4.7-Flash | college_medicine | mmlu_college_medicine | 0.208092 | 173 | 36 |\n| zai-org/GLM-4.7-Flash | global_facts | mmlu_global_facts | 0.18 | 100 | 18 |\n| zai-org/GLM-4.7-Flash | human_aging | mmlu_human_aging | 0.313901 | 223 | 70 |\n| zai-org/GLM-4.7-Flash | management | mmlu_management | 0.174757 | 103 | 18 |\n| zai-org/GLM-4.7-Flash | marketing | mmlu_marketing | 0.290598 | 234 | 68 |\n| zai-org/GLM-4.7-Flash | medical_genetics | mmlu_medical_genetics | 0.3 | 100 | 30 |\n| zai-org/GLM-4.7-Flash | miscellaneous | mmlu_miscellaneous | 0.237548 | 783 | 186 |\n| zai-org/GLM-4.7-Flash | nutrition | mmlu_nutrition | 0.22549 | 306 | 69 |\n| zai-org/GLM-4.7-Flash | professional_accounting | mmlu_professional_accounting | 0.234043 | 282 | 66 |\n| zai-org/GLM-4.7-Flash | professional_medicine | mmlu_professional_medicine | 0.183824 | 272 | 50 |\n| zai-org/GLM-4.7-Flash | virology | mmlu_virology | 0.283133 | 166 | 47 |\n| zai-org/GLM-4.7-Flash | econometrics | mmlu_econometrics | 0.236842 | 114 | 27 |\n| zai-org/GLM-4.7-Flash | high_school_geography | mmlu_high_school_geography | 0.176768 | 198 | 35 |\n| zai-org/GLM-4.7-Flash | high_school_government_and_politics | mmlu_high_school_government_and_politics | 0.196891 | 193 | 38 |\n| zai-org/GLM-4.7-Flash | high_school_macroeconomics | mmlu_high_school_macroeconomics | 0.202564 | 390 | 79 |\n| zai-org/GLM-4.7-Flash | high_school_microeconomics | mmlu_high_school_microeconomics | 0.214286 | 238 | 51 |\n| zai-org/GLM-4.7-Flash | high_school_psychology | mmlu_high_school_psychology | 0.192661 | 545 | 105 |\n| zai-org/GLM-4.7-Flash | human_sexuality | mmlu_human_sexuality | 0.259542 | 131 | 34 |\n| zai-org/GLM-4.7-Flash | professional_psychology | mmlu_professional_psychology | 0.25 | 612 | 153 |\n| zai-org/GLM-4.7-Flash | public_relations | mmlu_public_relations | 0.218182 | 110 | 24 |\n| zai-org/GLM-4.7-Flash | security_studies | mmlu_security_studies | 0.187755 | 245 | 46 |\n| zai-org/GLM-4.7-Flash | sociology | mmlu_sociology | 0.238806 | 201 | 48 |\n| zai-org/GLM-4.7-Flash | us_foreign_policy | mmlu_us_foreign_policy | 0.28 | 100 | 28 |\n| zai-org/GLM-4.7-Flash | abstract_algebra | mmlu_abstract_algebra | 0.22 | 100 | 22 |\n| zai-org/GLM-4.7-Flash | anatomy | mmlu_anatomy | 0.185185 | 135 | 25 |\n| zai-org/GLM-4.7-Flash | astronomy | mmlu_astronomy | 0.177632 | 152 | 27 |\n| zai-org/GLM-4.7-Flash | college_biology | mmlu_college_biology | 0.256944 | 144 | 37 |\n| zai-org/GLM-4.7-Flash | college_chemistry | mmlu_college_chemistry | 0.2 | 100 | 20 |\n| zai-org/GLM-4.7-Flash | college_computer_science | mmlu_college_computer_science | 0.26 | 100 | 26 |\n| zai-org/GLM-4.7-Flash | college_mathematics | mmlu_college_mathematics | 0.21 | 100 | 21 |\n| zai-org/GLM-4.7-Flash | college_physics | mmlu_college_physics | 0.215686 | 102 | 22 |\n| zai-org/GLM-4.7-Flash | computer_security | mmlu_computer_security | 0.28 | 100 | 28 |\n| zai-org/GLM-4.7-Flash | conceptual_physics | mmlu_conceptual_physics | 0.26383 | 235 | 62 |\n| zai-org/GLM-4.7-Flash | electrical_engineering | mmlu_electrical_engineering | 0.241379 | 145 | 35 |\n| zai-org/GLM-4.7-Flash | elementary_mathematics | mmlu_elementary_mathematics | 0.208995 | 378 | 79 |\n| zai-org/GLM-4.7-Flash | high_school_biology | mmlu_high_school_biology | 0.174194 | 310 | 54 |\n| zai-org/GLM-4.7-Flash | high_school_chemistry | mmlu_high_school_chemistry | 0.152709 | 203 | 31 |\n| zai-org/GLM-4.7-Flash | high_school_computer_science | mmlu_high_school_computer_science | 0.25 | 100 | 25 |\n| zai-org/GLM-4.7-Flash | high_school_mathematics | mmlu_high_school_mathematics | 0.211111 | 270 | 57 |\n| zai-org/GLM-4.7-Flash | high_school_physics | mmlu_high_school_physics | 0.198675 | 151 | 29 |\n| zai-org/GLM-4.7-Flash | high_school_statistics | mmlu_high_school_statistics | 0.152778 | 216 | 33 |\n| zai-org/GLM-4.7-Flash | machine_learning | mmlu_machine_learning | 0.321429 | 112 | 36 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | formal_logic | mmlu_formal_logic | 0.206349 | 126 | 26 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_european_history | mmlu_high_school_european_history | 0.206061 | 165 | 34 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_us_history | mmlu_high_school_us_history | 0.245098 | 204 | 50 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_world_history | mmlu_high_school_world_history | 0.270042 | 237 | 63 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | international_law | mmlu_international_law | 0.239669 | 121 | 29 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | jurisprudence | mmlu_jurisprudence | 0.305556 | 108 | 33 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | logical_fallacies | mmlu_logical_fallacies | 0.214724 | 163 | 35 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | moral_disputes | mmlu_moral_disputes | 0.271676 | 346 | 93 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | moral_scenarios | mmlu_moral_scenarios | 0.222346 | 895 | 199 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | philosophy | mmlu_philosophy | 0.228296 | 311 | 71 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | prehistory | mmlu_prehistory | 0.271605 | 324 | 88 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | professional_law | mmlu_professional_law | 0.252934 | 1534 | 388 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | world_religions | mmlu_world_religions | 0.280702 | 171 | 48 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | business_ethics | mmlu_business_ethics | 0.3 | 100 | 30 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | clinical_knowledge | mmlu_clinical_knowledge | 0.267925 | 265 | 71 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_medicine | mmlu_college_medicine | 0.213873 | 173 | 37 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | global_facts | mmlu_global_facts | 0.32 | 100 | 32 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | human_aging | mmlu_human_aging | 0.327354 | 223 | 73 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | management | mmlu_management | 0.213592 | 103 | 22 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | marketing | mmlu_marketing | 0.286325 | 234 | 67 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | medical_genetics | mmlu_medical_genetics | 0.35 | 100 | 35 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | miscellaneous | mmlu_miscellaneous | 0.254151 | 783 | 199 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | nutrition | mmlu_nutrition | 0.222222 | 306 | 68 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | professional_accounting | mmlu_professional_accounting | 0.244681 | 282 | 69 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | professional_medicine | mmlu_professional_medicine | 0.183824 | 272 | 50 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | virology | mmlu_virology | 0.325301 | 166 | 54 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | econometrics | mmlu_econometrics | 0.280702 | 114 | 32 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_geography | mmlu_high_school_geography | 0.207071 | 198 | 41 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_government_and_politics | mmlu_high_school_government_and_politics | 0.176166 | 193 | 34 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_macroeconomics | mmlu_high_school_macroeconomics | 0.217949 | 390 | 85 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_microeconomics | mmlu_high_school_microeconomics | 0.222689 | 238 | 53 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_psychology | mmlu_high_school_psychology | 0.209174 | 545 | 114 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | human_sexuality | mmlu_human_sexuality | 0.21374 | 131 | 28 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | professional_psychology | mmlu_professional_psychology | 0.259804 | 612 | 159 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | public_relations | mmlu_public_relations | 0.309091 | 110 | 34 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | security_studies | mmlu_security_studies | 0.159184 | 245 | 39 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | sociology | mmlu_sociology | 0.253731 | 201 | 51 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | us_foreign_policy | mmlu_us_foreign_policy | 0.25 | 100 | 25 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | abstract_algebra | mmlu_abstract_algebra | 0.23 | 100 | 23 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | anatomy | mmlu_anatomy | 0.251852 | 135 | 34 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | astronomy | mmlu_astronomy | 0.164474 | 152 | 25 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_biology | mmlu_college_biology | 0.263889 | 144 | 38 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_chemistry | mmlu_college_chemistry | 0.22 | 100 | 22 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_computer_science | mmlu_college_computer_science | 0.22 | 100 | 22 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_mathematics | mmlu_college_mathematics | 0.25 | 100 | 25 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | college_physics | mmlu_college_physics | 0.245098 | 102 | 25 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | computer_security | mmlu_computer_security | 0.24 | 100 | 24 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | conceptual_physics | mmlu_conceptual_physics | 0.340426 | 235 | 80 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | electrical_engineering | mmlu_electrical_engineering | 0.193103 | 145 | 28 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | elementary_mathematics | mmlu_elementary_mathematics | 0.240741 | 378 | 91 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_biology | mmlu_high_school_biology | 0.190323 | 310 | 58 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_chemistry | mmlu_high_school_chemistry | 0.216749 | 203 | 44 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_computer_science | mmlu_high_school_computer_science | 0.19 | 100 | 19 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_mathematics | mmlu_high_school_mathematics | 0.240741 | 270 | 65 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_physics | mmlu_high_school_physics | 0.172185 | 151 | 26 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | high_school_statistics | mmlu_high_school_statistics | 0.194444 | 216 | 42 |\n| TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill | machine_learning | mmlu_machine_learning | 0.241071 | 112 | 27 |\n\n### Benchmark Config\n\n- **Quantization:** 4bit\n- **Temperature:** 0.0\n- **Top P:** 1.0\n- **Top K:** 0\n- **Repetition Penalty:** 1.0\n\nAll results were obtained through the official lm evaluation harness\n\n---\nThis qwen3 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.",
"related_quantizations": []
},
"tags": [
"gguf",
"text-generation-inference",
"llama.cpp",
"unsloth",
"glm4_moe_lite",
"dataset:TeichAI/claude-4.5-opus-high-reasoning-250x",
"base_model:TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill",
"base_model:quantized:TeichAI/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 2,
"downloads": 108,
"gated": false,
"private": false,
"last_modified": "2026-03-05T01:12:27.000Z",
"created_at": "2026-03-05T01:12:27.000Z",
"pipeline_tag": "",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
"_id": "69a8d87b978251be88b9ec09",
"id": "zsjTiger/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF",
"modelId": "zsjTiger/GLM-4.7-Flash-Claude-Opus-4.5-High-Reasoning-Distill-GGUF",
"sha": "dca27dd493fc0f7f4d7a8187beb9b8a82713255d",
"createdAt": "2026-03-05T01:12:27.000Z",
"lastModified": "2026-03-05T01:12:27.000Z",
"author": "zsjTiger",
"downloads": 108,
"likes": 2,
"gated": false,
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"pipeline_tag": "",
"library_name": "",
"siblings_count": 19
}