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3940 chat models and 46,081 sizes from Hugging Face, each judged for the Mac you pick: whether it fits, the memory it takes, how fast it writes and how it scores. Chart any two numbers, compare up to four, or paste a link to any GGUF model.
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Arena rating against words a second
The chart needs JavaScript. The table below is for M4, 16 GB.
Best trade-offs: nothing beats these on both axes · Better than the typical model on both · Under 4 bits a weight: its score overstates it
| Model | Size | Fit | Memory | Writes | Reads | Longest chat | Arena | Arena coding |
|---|---|---|---|---|---|---|---|---|
| Gemma 3 12BGoogle · 12B | Q4_K_S4.71 bits · unsloth | Runs great | 7.5 GB | 7.2 | 83 | 8K | 1342 | 1316 |
| Gemma 3n E4BGoogle · 6.9B | Q8_08.56 bits · unsloth | Runs great | 7.6 GB | 9.7 | 142 | 16K | 1318 | 1307 |
| Granite 4.1 8BIBM · 8.8B | Q5_16.03 bits · ibm-granite | Runs great | 7.5 GB | 6.4 | 111 | 8K | 1304 | 1353 |
| Gemma 3 4BGoogle · 3.9B | Q6_K_L6.91 bits · bartowski | Runs great | 5.1 GB | 16 | 251 | 128K | 1303 | 1273 |
| Granite 4.2 8BIBM · 8.8B | Q5_16.03 bits · ibm-granite | Runs great | 7.5 GB | 6.4 | 111 | 8K | 1290 | 1370 |
| Granite 4.2 3BIBM · 3.7B | Q8_08.51 bits · ibm-granite | Runs great | 7.1 GB | 11 | 266 | 64K | 1290 | 1378 |
| Gemma 2 9BGoogle · 9.2B | Q4_K_L5.18 bits · bartowski | Runs great | 7.7 GB | 4 | 106 | 8K | 1267 | 1270 |
| Phi 4Microsoft · 15B | Q4_15.06 bits · microsoft | Runs well | 10 GB | 4.9 | 67 | 8K | 1256 | 1306 |
| Aya Expanse 8BCohere · 8B | Q6_K_L6.83 bits · bartowski | Runs great | 7.6 GB | 6.2 | 121 | 8K | 1223 | 1255 |
| Llama 3.1 Tulu 3 8BAi2 · 8B | Q6_K6.57 bits · lmstudio-community | Runs great | 7.3 GB | 6.3 | 121 | 8K | 1221 | |
| Llama 3.1 8BMeta · 8B | Q6_K6.57 bits · unsloth | Runs great | 7.3 GB | 6.3 | 121 | 8K | 1211 | 1259 |
| Granite 3.1 8BIBM · 8.2B | Q6_K_L6.61 bits · bartowski | Runs great | 7.6 GB | 5.6 | 119 | 8K | 1209 | |
| Gemma 2 2BGoogle · 2.6B | Q8_08.53 bits · bartowski | Runs great | 3.3 GB | 16 | 374 | 8K | 1200 | 1191 |
| Phi 3 Medium 4KMicrosoft · 14B | Q3_K_M3.97 bits · bartowski | Runs great | 7.5 GB | 5 | 70 | 4K | 1198 | 1231 |
| Granite 3.1 2BIBM · 2.5B | Q8_08.52 bits · bartowski | Runs great | 5.9 GB | 14 | 385 | 64K | 1179 | 1249 |
| Llama 3.2 3BMeta · 3.2B | Q8_08.53 bits · unsloth | Runs great | 5.7 GB | 11 | 304 | 32K | 1167 | 1176 |
| SOLAR 10.7B V1.0Upstage · 11B | Q4_K_M4.82 bits · TheBloke | Runs great | 7 GB | 5.3 | 91 | 4K | 1152 | |
| Mistral 7B V0.2Mistral AI · 7.2B | Q6_K6.57 bits · TheBloke | Runs great | 7.3 GB | 6.7 | 135 | 16K | 1149 | 1186 |
| Phi 3 Mini 128KMicrosoft · 3.8B | Q8_08.51 bits · QuantFactory | Runs great | 6 GB | 4.7 | 255 | 8K | 1130 | 1155 |
| Phi 3 Mini 4KMicrosoft · 3.8B | Q8_08.51 bits · bartowski | Runs great | 5.1 GB | 4.7 | 255 | 4K | 1128 | 1187 |
| SmolLM2 1.7BHugging Face · 1.7B | Q8_08.52 bits · bartowski | Runs great | 2.9 GB | 9.5 | 570 | 8K | 1115 | |
| Llama 3.2 1BMeta · 1.2B | Q8_08.52 bits · unsloth | Runs great | 3.9 GB | 31 | 786 | 128K | 1111 | 1149 |
| Chatglm3 6BZ.ai · 6.2B | Q8_08.51 bits · mradermacher | Runs great | 6.9 GB | 10 | 156 | 8K | 1057 | 1090 |
| Ornith 1.5 9Bornith-ai · 9.2B | Q5_K_M6.04 bits · Mungert | Runs great | 7.7 GB | 8.3 | 106 | 32K | ||
| Gemma 4 12BGoogle · 12B | Q4_K_M4.78 bits · unsloth | Runs great | 7.6 GB | 8.3 | 82 | 16K | ||
| Ornith 1.0 9Bornith-ai · 8.9B | Q6_K6.58 bits · ornith-ai | Runs great | 7.6 GB | 7.9 | 109 | 8K | ||
| Gemma 4 E4BGoogle · 7.5B | Q6_K_L7.63 bits · bartowski | Runs great | 7.6 GB | 8 | 130 | 16K | ||
| Qwen3.5 9BAlibaba Qwen · 9.2B | Q5_K_M6.18 bits · gguf | Runs great | 7.6 GB | 8 | 106 | 16K | ||
| Qwen3.5 9B The Defiant Fable Uncensored Heretic NEO IMATRIX MAX MTPDavidAU · 9.2B | Q4_K_M5.94 bits · DavidAU | Runs great | 7.6 GB | 8.4 | 106 | 32K | ||
| Qwen3.5 4BAlibaba Qwen · 4.3B | Q8_08.52 bits · gguf | Runs great | 7.3 GB | 13 | 225 | 128K | ||
| Qwen3 VL 8BAlibaba Qwen · 8.2B | Q6_K6.57 bits · unsloth | Runs great | 7.5 GB | 5.9 | 119 | 8K | ||
| Ornith 1.5 9B Uncensoredjunafinity · 8.9B | Q6_K6.58 bits · dealignai | Runs great | 7.6 GB | 7.9 | 109 | 8K | ||
| Qwen3 4BAlibaba Qwen · 4B | Q8_08.52 bits · Qwen | Runs great | 7.2 GB | 8.4 | 243 | 32K | ||
| Gemma 4 E2BGoogle · 4.7B | Q8_08.69 bits · unsloth | Runs great | 6.4 GB | 13 | 210 | 128K | ||
| HyperCLOVAX SEED Text 1.5Bnaver-hyperclovax · 1.8B | Q4_K_M5.01 bits · rippertnt | Runs great | 5 GB | 15 | 539 | 64K | ||
| Qwen3 VL 4BAlibaba Qwen · 4B | Q8_08.52 bits · Qwen | Runs great | 7.2 GB | 8.4 | 243 | 32K | ||
| Hy MT2 7BTencent · 7.5B | Q6_K6.58 bits · tencent | Runs great | 7.5 GB | 6.5 | 130 | 16K | ||
| Qwen3 8BAlibaba Qwen · 8.2B | Q6_K6.57 bits · Qwen | Runs great | 7.5 GB | 5.9 | 119 | 8K | ||
| Qwen2.5 7BAlibaba Qwen · 7.6B | Q6_K_L6.84 bits · bartowski | Runs great | 7.7 GB | 8.1 | 128 | 32K | ||
| MiMo V2.6 Distill Qwen 9BXiaomi · 8.9B | Q5_K_M6.15 bits · bartowski | Runs great | 7.6 GB | 8.3 | 109 | 32K | ||
| Cyber Ornith 1.5 9B OBLITERATEDDuoNeural · 8.9B | Q6_K6.58 bits · DuoNeural | Runs great | 7.6 GB | 7.9 | 109 | 8K | ||
| Qwen3 4B 2507Alibaba Qwen · 4B | Q8_08.52 bits · a-ivanovitch | Runs great | 7.2 GB | 8.4 | 243 | 32K | ||
| Sharp Spark X2.5 4Bpeculiar-ragdoll · 4.1B | Q6_K_XL7.03 bits · peculiar-ragdoll | Runs great | 6.5 GB | 13 | 237 | 128K | ||
| Gemma 4 E4B Uncensored HauhauCS Aggressive (HauhauCS)HauhauCS · 7.5B | Q6_K_P6.65 bits · HauhauCS | Runs great | 7.6 GB | 9 | 130 | 64K | ||
| AdaVaR 3BZejunLi · 3.1B | Q8_08.51 bits · mradermacher | Runs great | 4.8 GB | 16 | 316 | 64K | ||
| Gemma4 12B QAT Uncensored HauhauCS BalancedHauhauCS · 12B | Q4_K_M4.96 bits · HauhauCS | Runs well | 10 GB | 8.1 | 82 | 256K | ||
| Qwen3 1.7BAlibaba Qwen · 2B | UD-Q8_K_XL9.19 bits · unsloth | Runs great | 4.6 GB | 11 | 480 | 32K | ||
| Spark X2.5 4BXHToken · 4.1B | Q8_08.52 bits · XHToken | Runs great | 7.3 GB | 13 | 237 | 128K | ||
| Qwen3 VL 8B Abliteratedmradermacher · 8.2B | Q6_K6.57 bits · mradermacher | Runs great | 7.5 GB | 5.9 | 119 | 8K | ||
| Qwen3.5 9B Uncensored HauhauCS Aggressive (HauhauCS)HauhauCS · 8.9B | Q6_K6.58 bits · HauhauCS | Runs great | 7.6 GB | 7.9 | 109 | 8K | ||
| Qwen3 0.6BAlibaba Qwen · 0.8B | UD-Q8_K_XL9.01 bits · unsloth | Runs great | 3.1 GB | 14 | 1300 | 32K | ||
| Qwen3.5 9B Kimi K3 Distilledkhazarai · 9.2B | Q5_K_M5.78 bits · mradermacher | Runs great | 7.4 GB | 8.6 | 106 | 32K | ||
| Gemma 3 1BGoogle · 1B | Q5_K_S6.69 bits · unsloth | Runs great | 1 GB | 51 | 975 | 32K | ||
| Qwen3 14BAlibaba Qwen · 15B | Q4_K_M4.88 bits · Qwen | Runs well | 9.9 GB | 4.8 | 66 | 8K | ||
| B1 9Bschneewolflabs · 9.2B | Q5_K_M5.78 bits · mradermacher | Runs great | 7.4 GB | 8.6 | 106 | 32K | ||
| Qwen3.8 4B Distillempero-ai · 4.3B | Q8_08.52 bits · empero-ai | Runs great | 7.3 GB | 13 | 225 | 128K | ||
| Qwen3.5 2BAlibaba Qwen · 1.9B | Q8_08.56 bits · gguf | Runs great | 3.9 GB | 29 | 503 | 256K | ||
| Qwen2.5 1.5B InstructAlibaba Qwen · 1.8B | Q8_08.51 bits · Qwen | Runs great | 2.5 GB | 25 | 548 | 32K | ||
| Jinen V1 Small.togatogah · 0.1B | F1632.24 bits · togatogah | Runs great | 0.6 GB | 45 | 1950 | 1K | ||
| Qwen3.8 9B Distillempero-ai · 9.2B | Q5_K_M5.78 bits · empero-ai | Runs great | 7.4 GB | 8.6 | 106 | 32K |
How the numbers are made
The models. The chat models people download as GGUF on Hugging Face this month (the most downloaded, trending and most liked), refreshed every morning. A compressed copy of a model, such as ISTA-DASLab's GSQ-RCO builds of Qwen3.8, is listed as one of that model's sizes. A fine-tune or a retrained model, such as PrismML's Bonsai, is a model of its own and never borrows another model's score. Updated November 5, 2026; the full list as JSON.
Fit and memory. The size's file, a key-value cache at 8 bits per value for the chat length shown, and a fixed allowance fitted to the memory the app measures on its own models. The verdicts are the app's: runs great leaves room for everything else, runs well leaves enough, a tight fit closes other apps. Every row picks the most bits that runs great, else runs well, from sizes of 4 bits a weight or more first; past about 8 bits a copy only writes slower, so the smaller file wins. Longest chat is the longest conversation that keeps the verdict the model has at 8,000 tokens.
Speed. Predicted, a few exchanges into a chat (4,096 tokens), from the same model the app uses, fitted to measured llama.cpp tables on every Apple silicon chip (constants of October 11, 2026). Rows marked rough are outside those tables: a mixture of experts, a publisher's own size format, or a chip newer than M5. It leans low: two independent reports checked on 11 October 2026 ran 14% and 18% faster than this estimate at an empty chat (Gemma 3 12B on an M1 Max, Gemma 4 26B A4B on an M4). How speed is measured.
Ratings. LM Arena's ratings with style control, overall and for coding, from its leaderboard dataset (October 28, 2026, CC BY 4.0). 104 of the 3,940 models have one; a rating goes only to the maker's own model, never to a fine-tune or a copy under another maker's name. A rating describes the full model, so a size under 4 bits a weight does worse than its rating says; that is why rows lead with 4 bits or more.
Your own model. Paste a Hugging Face link in the search box. Your browser reads the repo's file list and the first few megabytes of one file's header from Hugging Face, and judges it with the same arithmetic. The link is not added to the page's address, and Outmake's servers receive no request for it.