Model Intelligence Sheet
teichai/qwen3-4b-thinking-2507-gemini-2.5-flash-distill-gguf overview
This model was trained on a large Gemini 2.5 Flash dataset. The goal of was to distill the behavior, reasoning traces, output style, and (most importantly) knowledge of Gemini-2.5 Flash. | Model | Effective parameters | Active parameters | | ------------- | ------------- | ------------- | | TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF | 30 B | 3 B | | TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill-GGUF | 8 B | 8 B | --- # Benchmark Results !alt="Results Bar Chart" !alt="MMLU Subject Breakdown"
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text-generation
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| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-bf16.gguf | GGUF | BF16 | 7.50 GB | Download |
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-f16.gguf | GGUF | F16 | 7.50 GB | Download |
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-q3_k_m.gguf | GGUF | Q3_K_M | 1.93 GB | Download |
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-q3_k_s.gguf | GGUF | Q3_K_S | 1.76 GB | Download |
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-q4_k_m.gguf | GGUF | Q4_K_M | 2.33 GB | Download |
| Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-q8_0.gguf | GGUF | — | 3.99 GB | Download |
| qwen3-4b-thinking-2507.F16.gguf | GGUF | F16 | 7.50 GB | Download |
| qwen3-4b-thinking-2507.Q8_0.gguf | GGUF | — | 3.99 GB | Download |
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{
"metadata": {},
"card_data": {
"base_model": "TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill",
"tags": [
"text-generation-inference",
"transformers",
"unsloth",
"qwen3"
],
"license": "apache-2.0",
"language": [
"en"
],
"datasets": [
"TeichAI/gemini-2.5-flash-11000x"
],
"pipeline_tag": "text-generation",
"frontmatter": {
"base_model": "TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill",
"tags": [
"text-generation-inference",
"transformers",
"unsloth",
"qwen3"
],
"license": "apache-2.0",
"language": [
"en"
],
"datasets": [
"TeichAI/gemini-2.5-flash-11000x"
],
"pipeline_tag": "text-generation"
},
"hero_image_url": "results_bar_chart.png",
"summary": "This model was trained on a large **Gemini 2.5 Flash** dataset. The goal of was to distill the behavior, reasoning traces, output style, and (most importantly) knowledge of Gemini-2.5 Flash. | Model | Effective parameters | Active parameters | | ------------- | ------------- | ------------- | | TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF | 30 B | 3 B | | TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill-GGUF | 8 B | 8 B | --- # Benchmark Results !alt=\"Results Bar Chart\" !alt=\"MMLU Subject Breakdown\"",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model: TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill\ntags:\n- text-generation-inference\n- transformers\n- unsloth\n- qwen3\nlicense: apache-2.0\nlanguage:\n- en\ndatasets:\n- TeichAI/gemini-2.5-flash-11000x\npipeline_tag: text-generation\n---\n\n# Qwen3 4B Thinking 2507 x Gemini 2.5 Flash \n\nThis model was trained on a large **Gemini 2.5 Flash** dataset.\n\nThe goal of was to distill the behavior, reasoning traces, output style, and (most importantly) knowledge of Gemini-2.5 Flash.\n\n- 🤖 Related Models:\n| Model | Effective parameters | Active parameters |\n| ------------- | ------------- | ------------- |\n| [`TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-30B-A3B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF) | 30 B | 3 B |\n| [`TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill-GGUF`](https://huggingface.co/TeichAI/Qwen3-8B-Gemini-2.5-Flash-Distill-GGUF) | 8 B | 8 B |\n\n\n- 🧬 Datasets:\n - `TeichAI/gemini-2.5-flash-11000x`\n\n- 🏗 Base Model:\n - `unsloth/Qwen3-30B-A3B-Thinking-2507`\n \n- ⚡ Use cases:\n - Coding\n - Science\n - Legal\n - History\n - Marketing\n - General Purpose\n\n- ∑ Stats (Dataset)\n - Costs: $ 134 (USD)\n - Total tokens (input + output): 54.4 M\n\n---\n\n# Benchmark Results\n\n\n\n\n\n## Model Comparison vs Base\n\n- Base model: unsloth/Qwen3-4B-Thinking-2507\n\n| Compare Model | Benchmark | Base Score | Model Score | Delta | Delta % |\n|:--------------------------------------------------------|:----------------------|-------------:|--------------:|------------:|------------:|\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | arc_challenge | 0.486348 | 0.511945 | 0.0255973 | 0.0526316 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | gpqa_diamond_zeroshot | 0.30303 | 0.353535 | 0.0505051 | 0.166667 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | hellaswag | 0.479785 | 0.504382 | 0.0245967 | 0.0512661 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | mmlu | 0.65532 | 0.661587 | 0.00626691 | 0.00956314 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | truthfulqa_mc2 | 0.555747 | 0.552899 | -0.00284708 | -0.00512299 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | winogrande | 0.64562 | 0.65588 | 0.0102605 | 0.0158924 |\n\n## Aggregate Comparison\n\n| Compare Model | Benchmarks Compared | Wins vs Base | Ties vs Base | Losses vs Base | Avg Delta |\n|:--------------------------------------------------------|----------------------:|---------------:|---------------:|-----------------:|------------:|\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | 6 | 5 | 0 | 1 | 0.0190632 |\n\n\n## Detailed Results\n\n| Model | Benchmark | Score | Total Questions | Total Correct |\n|:--------------------------------------------------------|:----------------------|---------:|------------------:|----------------:|\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | arc_challenge | 0.511945 | 1172 | 600 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | gpqa_diamond_zeroshot | 0.353535 | 198 | 70 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | hellaswag | 0.504382 | 10042 | 5065 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | mmlu | 0.661587 | 14042 | 9290 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | truthfulqa_mc2 | 0.552899 | 817 | 451 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | winogrande | 0.65588 | 1267 | 831 |\n| unsloth/Qwen3-4B-Thinking-2507 | arc_challenge | 0.486348 | 1172 | 570 |\n| unsloth/Qwen3-4B-Thinking-2507 | gpqa_diamond_zeroshot | 0.30303 | 198 | 60 |\n| unsloth/Qwen3-4B-Thinking-2507 | hellaswag | 0.479785 | 10042 | 4818 |\n| unsloth/Qwen3-4B-Thinking-2507 | mmlu | 0.65532 | 14042 | 9202 |\n| unsloth/Qwen3-4B-Thinking-2507 | truthfulqa_mc2 | 0.555747 | 817 | 454 |\n| unsloth/Qwen3-4B-Thinking-2507 | winogrande | 0.64562 | 1267 | 818 |\n\n\n### MMLU Subject Breakdown\n\n| Model | Subject | Benchmark | Score | Total Questions | Total Correct |\n|:--------------------------------------------------------|:------------------------------------|:-----------------------------------------|---------:|------------------:|----------------:|\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | formal_logic | mmlu_formal_logic | 0.603175 | 126 | 76 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_european_history | mmlu_high_school_european_history | 0.727273 | 165 | 120 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_us_history | mmlu_high_school_us_history | 0.833333 | 204 | 170 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_world_history | mmlu_high_school_world_history | 0.801688 | 237 | 190 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | international_law | mmlu_international_law | 0.752066 | 121 | 91 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | jurisprudence | mmlu_jurisprudence | 0.777778 | 108 | 84 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | logical_fallacies | mmlu_logical_fallacies | 0.797546 | 163 | 130 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | moral_disputes | mmlu_moral_disputes | 0.67341 | 346 | 233 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | moral_scenarios | mmlu_moral_scenarios | 0.340782 | 895 | 305 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | philosophy | mmlu_philosophy | 0.694534 | 311 | 216 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | prehistory | mmlu_prehistory | 0.719136 | 324 | 233 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | professional_law | mmlu_professional_law | 0.45176 | 1534 | 693 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | world_religions | mmlu_world_religions | 0.754386 | 171 | 129 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | business_ethics | mmlu_business_ethics | 0.71 | 100 | 71 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | clinical_knowledge | mmlu_clinical_knowledge | 0.70566 | 265 | 187 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_medicine | mmlu_college_medicine | 0.693642 | 173 | 120 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | global_facts | mmlu_global_facts | 0.44 | 100 | 44 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | human_aging | mmlu_human_aging | 0.695067 | 223 | 155 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | management | mmlu_management | 0.854369 | 103 | 88 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | marketing | mmlu_marketing | 0.846154 | 234 | 198 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | medical_genetics | mmlu_medical_genetics | 0.77 | 100 | 77 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | miscellaneous | mmlu_miscellaneous | 0.779055 | 783 | 610 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | nutrition | mmlu_nutrition | 0.718954 | 306 | 220 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | professional_accounting | mmlu_professional_accounting | 0.528369 | 282 | 149 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | professional_medicine | mmlu_professional_medicine | 0.672794 | 272 | 183 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | virology | mmlu_virology | 0.524096 | 166 | 87 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | econometrics | mmlu_econometrics | 0.605263 | 114 | 69 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_geography | mmlu_high_school_geography | 0.823232 | 198 | 163 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_government_and_politics | mmlu_high_school_government_and_politics | 0.865285 | 193 | 167 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_macroeconomics | mmlu_high_school_macroeconomics | 0.720513 | 390 | 281 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_microeconomics | mmlu_high_school_microeconomics | 0.802521 | 238 | 191 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_psychology | mmlu_high_school_psychology | 0.86789 | 545 | 473 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | human_sexuality | mmlu_human_sexuality | 0.717557 | 131 | 94 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | professional_psychology | mmlu_professional_psychology | 0.658497 | 612 | 403 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | public_relations | mmlu_public_relations | 0.690909 | 110 | 76 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | security_studies | mmlu_security_studies | 0.726531 | 245 | 178 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | sociology | mmlu_sociology | 0.80597 | 201 | 162 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | us_foreign_policy | mmlu_us_foreign_policy | 0.82 | 100 | 82 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | abstract_algebra | mmlu_abstract_algebra | 0.57 | 100 | 56 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | anatomy | mmlu_anatomy | 0.6 | 135 | 81 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | astronomy | mmlu_astronomy | 0.809211 | 152 | 123 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_biology | mmlu_college_biology | 0.8125 | 144 | 117 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_chemistry | mmlu_college_chemistry | 0.51 | 100 | 51 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_computer_science | mmlu_college_computer_science | 0.57 | 100 | 56 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_mathematics | mmlu_college_mathematics | 0.53 | 100 | 53 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | college_physics | mmlu_college_physics | 0.509804 | 102 | 52 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | computer_security | mmlu_computer_security | 0.78 | 100 | 78 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | conceptual_physics | mmlu_conceptual_physics | 0.753191 | 235 | 177 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | electrical_engineering | mmlu_electrical_engineering | 0.724138 | 145 | 105 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | elementary_mathematics | mmlu_elementary_mathematics | 0.642857 | 378 | 243 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_biology | mmlu_high_school_biology | 0.835484 | 310 | 259 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_chemistry | mmlu_high_school_chemistry | 0.669951 | 203 | 136 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_computer_science | mmlu_high_school_computer_science | 0.82 | 100 | 82 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_mathematics | mmlu_high_school_mathematics | 0.477778 | 270 | 129 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_physics | mmlu_high_school_physics | 0.589404 | 151 | 89 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | high_school_statistics | mmlu_high_school_statistics | 0.703704 | 216 | 152 |\n| TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill | machine_learning | mmlu_machine_learning | 0.455357 | 112 | 51 |\n| unsloth/Qwen3-4B-Thinking-2507 | formal_logic | mmlu_formal_logic | 0.595238 | 126 | 75 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_european_history | mmlu_high_school_european_history | 0.727273 | 165 | 120 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_us_history | mmlu_high_school_us_history | 0.818627 | 204 | 167 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_world_history | mmlu_high_school_world_history | 0.797468 | 237 | 189 |\n| unsloth/Qwen3-4B-Thinking-2507 | international_law | mmlu_international_law | 0.727273 | 121 | 88 |\n| unsloth/Qwen3-4B-Thinking-2507 | jurisprudence | mmlu_jurisprudence | 0.777778 | 108 | 84 |\n| unsloth/Qwen3-4B-Thinking-2507 | logical_fallacies | mmlu_logical_fallacies | 0.754601 | 163 | 123 |\n| unsloth/Qwen3-4B-Thinking-2507 | moral_disputes | mmlu_moral_disputes | 0.67341 | 346 | 233 |\n| unsloth/Qwen3-4B-Thinking-2507 | moral_scenarios | mmlu_moral_scenarios | 0.372067 | 895 | 333 |\n| unsloth/Qwen3-4B-Thinking-2507 | philosophy | mmlu_philosophy | 0.672026 | 311 | 208 |\n| unsloth/Qwen3-4B-Thinking-2507 | prehistory | mmlu_prehistory | 0.70679 | 324 | 229 |\n| unsloth/Qwen3-4B-Thinking-2507 | professional_law | mmlu_professional_law | 0.441982 | 1534 | 678 |\n| unsloth/Qwen3-4B-Thinking-2507 | world_religions | mmlu_world_religions | 0.777778 | 171 | 133 |\n| unsloth/Qwen3-4B-Thinking-2507 | business_ethics | mmlu_business_ethics | 0.63 | 100 | 63 |\n| unsloth/Qwen3-4B-Thinking-2507 | clinical_knowledge | mmlu_clinical_knowledge | 0.716981 | 265 | 190 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_medicine | mmlu_college_medicine | 0.693642 | 173 | 120 |\n| unsloth/Qwen3-4B-Thinking-2507 | global_facts | mmlu_global_facts | 0.36 | 100 | 36 |\n| unsloth/Qwen3-4B-Thinking-2507 | human_aging | mmlu_human_aging | 0.713004 | 223 | 159 |\n| unsloth/Qwen3-4B-Thinking-2507 | management | mmlu_management | 0.864078 | 103 | 89 |\n| unsloth/Qwen3-4B-Thinking-2507 | marketing | mmlu_marketing | 0.854701 | 234 | 200 |\n| unsloth/Qwen3-4B-Thinking-2507 | medical_genetics | mmlu_medical_genetics | 0.8 | 100 | 80 |\n| unsloth/Qwen3-4B-Thinking-2507 | miscellaneous | mmlu_miscellaneous | 0.776501 | 783 | 608 |\n| unsloth/Qwen3-4B-Thinking-2507 | nutrition | mmlu_nutrition | 0.712418 | 306 | 218 |\n| unsloth/Qwen3-4B-Thinking-2507 | professional_accounting | mmlu_professional_accounting | 0.549645 | 282 | 155 |\n| unsloth/Qwen3-4B-Thinking-2507 | professional_medicine | mmlu_professional_medicine | 0.669118 | 272 | 182 |\n| unsloth/Qwen3-4B-Thinking-2507 | virology | mmlu_virology | 0.518072 | 166 | 86 |\n| unsloth/Qwen3-4B-Thinking-2507 | econometrics | mmlu_econometrics | 0.614035 | 114 | 70 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_geography | mmlu_high_school_geography | 0.777778 | 198 | 154 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_government_and_politics | mmlu_high_school_government_and_politics | 0.829016 | 193 | 160 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_macroeconomics | mmlu_high_school_macroeconomics | 0.720513 | 390 | 281 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_microeconomics | mmlu_high_school_microeconomics | 0.802521 | 238 | 191 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_psychology | mmlu_high_school_psychology | 0.851376 | 545 | 464 |\n| unsloth/Qwen3-4B-Thinking-2507 | human_sexuality | mmlu_human_sexuality | 0.740458 | 131 | 97 |\n| unsloth/Qwen3-4B-Thinking-2507 | professional_psychology | mmlu_professional_psychology | 0.669935 | 612 | 409 |\n| unsloth/Qwen3-4B-Thinking-2507 | public_relations | mmlu_public_relations | 0.672727 | 110 | 74 |\n| unsloth/Qwen3-4B-Thinking-2507 | security_studies | mmlu_security_studies | 0.706122 | 245 | 173 |\n| unsloth/Qwen3-4B-Thinking-2507 | sociology | mmlu_sociology | 0.800995 | 201 | 161 |\n| unsloth/Qwen3-4B-Thinking-2507 | us_foreign_policy | mmlu_us_foreign_policy | 0.82 | 100 | 82 |\n| unsloth/Qwen3-4B-Thinking-2507 | abstract_algebra | mmlu_abstract_algebra | 0.55 | 100 | 55 |\n| unsloth/Qwen3-4B-Thinking-2507 | anatomy | mmlu_anatomy | 0.644444 | 135 | 87 |\n| unsloth/Qwen3-4B-Thinking-2507 | astronomy | mmlu_astronomy | 0.782895 | 152 | 119 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_biology | mmlu_college_biology | 0.763889 | 144 | 110 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_chemistry | mmlu_college_chemistry | 0.55 | 100 | 55 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_computer_science | mmlu_college_computer_science | 0.62 | 100 | 62 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_mathematics | mmlu_college_mathematics | 0.44 | 100 | 44 |\n| unsloth/Qwen3-4B-Thinking-2507 | college_physics | mmlu_college_physics | 0.480392 | 102 | 49 |\n| unsloth/Qwen3-4B-Thinking-2507 | computer_security | mmlu_computer_security | 0.73 | 100 | 73 |\n| unsloth/Qwen3-4B-Thinking-2507 | conceptual_physics | mmlu_conceptual_physics | 0.723404 | 235 | 170 |\n| unsloth/Qwen3-4B-Thinking-2507 | electrical_engineering | mmlu_electrical_engineering | 0.751724 | 145 | 108 |\n| unsloth/Qwen3-4B-Thinking-2507 | elementary_mathematics | mmlu_elementary_mathematics | 0.645503 | 378 | 244 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_biology | mmlu_high_school_biology | 0.812903 | 310 | 252 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_chemistry | mmlu_high_school_chemistry | 0.660099 | 203 | 134 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_computer_science | mmlu_high_school_computer_science | 0.81 | 100 | 81 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_mathematics | mmlu_high_school_mathematics | 0.440741 | 270 | 119 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_physics | mmlu_high_school_physics | 0.569536 | 151 | 86 |\n| unsloth/Qwen3-4B-Thinking-2507 | high_school_statistics | mmlu_high_school_statistics | 0.652778 | 216 | 141 |\n| unsloth/Qwen3-4B-Thinking-2507 | machine_learning | mmlu_machine_learning | 0.428571 | 112 | 48 |\n\n## Configuration\n- **Quantization:** 4bit\n- **Temperature:** 0.6\n- **Top P:** 0.95\n- **Top K:** 20\n- **Repetition Penalty:** 1.1\n---\n\nThis model was finetuned and converted to GGUF format using [Unsloth](https://github.com/unslothai/unsloth).\n\n**Example usage**:\n- For text only LLMs: **llama-cli** **--hf** repo_id/model_name **-p** \"why is the sky blue?\"\n- For multimodal models: **llama-mtmd-cli** **-m** model_name.gguf **--mmproj** mmproj_file.gguf\n\n## Ollama\nAn Ollama Modelfile is included for easy deployment.",
"related_quantizations": []
},
"tags": [
"transformers",
"gguf",
"qwen3",
"text-generation",
"text-generation-inference",
"unsloth",
"en",
"dataset:TeichAI/gemini-2.5-flash-11000x",
"base_model:TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill",
"base_model:quantized:TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"conversational"
],
"likes": 1,
"downloads": 278,
"gated": false,
"private": false,
"last_modified": "2025-12-01T07:54:50.000Z",
"created_at": "2025-11-18T01:50:08.000Z",
"pipeline_tag": "text-generation",
"library_name": "transformers"
}
Source payload excerpt (from Hugging Face API)
{
"_id": "691bd0d08f9860529d2ae90a",
"id": "TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF",
"modelId": "TeichAI/Qwen3-4B-Thinking-2507-Gemini-2.5-Flash-Distill-GGUF",
"sha": "17900053193c1ed071a47339e0049a1c32e847af",
"createdAt": "2025-11-18T01:50:08.000Z",
"lastModified": "2025-12-01T07:54:50.000Z",
"author": "TeichAI",
"downloads": 278,
"likes": 1,
"gated": false,
"private": false,
"pipeline_tag": "text-generation",
"library_name": "transformers",
"siblings_count": 14
}