whatmodel.sh · find the best AI models you can run

Best AI models for chat and writing to run locally on a 64GB Mac

A leaderboard of the best AI models for chat and writing you can run locally on a Mac with 64GB of memory. Gemma 4 31B is #1 right now, followed by Nemotron Cascade 2 30B-A3B and Qwen3.8 27B. Models are ranked on human votes from LMArena and on writing and instruction-following tests. Each model shows the download that fits and the command to run it.

237 models · scores combine 19 benchmarks · updated 2026-10-11 02:20 UTChow it works · find a leaderboard · benchmark your machine

task[all tasks][agent tasks][coding][chat & writing][math][vision & documents][web search]

Scores use reviewed chat & writing evaluations only. Compare scores within this task. Models without task measurements are excluded.

Models for 64GB RAM · Apple Silicon → ~48GB fast · local only · reset

+ more

chip[M1 Max][M1 Ultra][M2 Max][M2 Ultra][M3 Max (16-core CPU / 40-core GPU)][M4 Pro][M4 Max (16-core CPU / 40-core GPU)][M5 Pro][M5 Max (40-core GPU)]

set[all sets][LMArena (text) · 579][IFEval (aggregation unspecified) · 3][IFEval (aggregation unspecified) · 2][IFEval (aggregation unspecified) · 2][IFEval prompt-level strict · 2]

Filter the model list while keeping task scores. Models without a shared score scale are not yet calibrated; select a set to see its own scores.

Detect your exact chip or graphics card:

curl -G whatmodel.sh/ -d max=0 --data-urlencode "mac=$(sysctl -n hw.memsize machdep.cpu.brand_string)"Mac

curl -G whatmodel.sh/ -d max=0 --data-urlencode "ram=$(awk '/MemT/{print $2}' /proc/meminfo)" --data-urlencode "nv=$(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>/dev/null)"Linux

curl.exe -G whatmodel.sh/ -d max=0 --data-urlencode "ram=$((gcim Win32_ComputerSystem).TotalPhysicalMemory)" --data-urlencode "nv=$(nvidia-smi --query-gpu=name,memory.total --format=csv,noheader 2>$null)"Windows

$ terminal

ram[8][16][24][32][48][64][96][128][192][256]GB

gpu[apple silicon][graphics card][none]

price[local][$0.02][$0.1][$0.5][$2][$10][any]max per M

detecting your OS…

Score vs memory to run

     │                                      Gemma 4 12B ●────────Qwen3.8 27B─●─∘─●● Gemma 4 31B         ∘
  50 ┤ · ●────────────●────────●───────────∘────∘───∘───∘· ∘ · · · · ·∘· ·∘·∘∘ ∘ ∘∘·∘∘∘· ·∘·∘∘ · ∘∘∘∘· · ∘∘· ·
     │   ∘            ∘        ∘           ∘    ∘   ∘   ∘  ∘  ∘       ∘ ∘         ∘ ∘∘∘    ∘∘ ∘∘∘∘    ∘  ∘∘
  25 ┤ · ∘ · · · · · ·∘· · · · ∘ · · ·∘· · ∘ · ·∘· · · ·∘· ∘ · · · · · · ·∘· · · · ·∘· · ·∘∘ · · · · · · · · ·
     │                                          ∘       ∘
     └───┬────────────────────────────┬────────────────────┬─────────────────────┬────────────────────────────
        2GB                          5GB                 10GB                  20GB

#	model	task score↓	where↓	speed↓	RAM↓	context↓	get it	sources

#	model	task score↓	where↓	RAM↓	context↓	get it	sources
57	Gemma 4 31B · 4-bit Google	69±1*	local	~37GB	262k	LM Studio ›
72	Nemotron Cascade 2 30B-A3B · 8-bit NVIDIA	68±4*†	local	~37GB	256k	llama.cpp ›
77	Qwen3.8 27B · 8-bit Alibaba	67±1*	local	~36GB	262k	Ollama ›
78	Gemma 4 26B-A4B · 4-bit Google	67±1*	local	~31GB	262k	LM Studio ›
83	Gemma 4 12B · 8-bit Google	67±6*	local	~15GB	262k	llama.cpp ›
90	Mistral Medium 3.5 (128B) · 2-bit Mistral	66±1*	local	~42GB	262k	llama.cpp ›
93	Muse Glimmer 30B · 8-bit Meta	66±1*	local	~40GB	131k	Ollama ›
111	Spark-X2.5 4B · 16-bit iFLYTEK (SparkLLM)	64±6*†	local	~10GB	1M	Ollama ›
113	Qwen3.5 27B · 8-bit Alibaba	64±1*	local	~37GB	262k	Ollama ›
124	Nemotron-Cascade-8B · 8-bit NVIDIA	63±7*†	local	~11GB		llama.cpp ›
128	Qwen3-Next 80B-A3B Instruct · 2-bit Alibaba	63±1	local	~27GB	131k	llama.cpp ›
131	LFM2.5 2.6B · 4-bit Liquid AI	62±7*	local	~4.5GB	131k	LM Studio ›
136	Qwen3.5 35B-A3B · 8-bit Alibaba	62±1	local	~47GB	262k	Ollama ›
146	LFM2.5 8B-A1B · 8-bit Liquid AI	60±5*	local	~13GB	128k	Ollama ›
148	Qwen3 30B-A3B Instruct 2507 · 8-bit Alibaba	60±1	local	~41GB	262k	Ollama ›
154	Spark-X2.5 1.7B · 16-bit iFLYTEK (SparkLLM)	60±5*†	local	~5.1GB	1M	Ollama ›
157	GLM-4.5-Air · 2-bit Z.ai	59±1*	local	~35GB	131k	llama.cpp ›
159	Gemma 2 9B IT DPO (Princeton) · 16-bit Princeton NLP	59±2*	local	~21GB		how to run ›
160	Qwen3-Next 80B-A3B Thinking · 2-bit Alibaba	59±1	local	~27GB	131k	llama.cpp ›
163	EXAONE 4.5 33B · 8-bit LG AI Research	59±4*†	local	~45GB	262k	llama.cpp ›
164	LFM2.5 1.2B Thinking · 8-bit Liquid AI	59±6*†	local	~3.5GB	33k	Ollama ›
166	GLM-4.7-Flash · 8-bit Z.ai	58±1*	local	~35GB	200k	llama.cpp ›
169	Qwen3.5 9B · 4-bit Alibaba	58±3	local	~12GB	262k	LM Studio ›
170	Gemma 3 27B · 8-bit Google	58±1	local	~37GB	131k	Ollama ›
171	Qwen3 30B-A3B Thinking 2507 · 8-bit Alibaba	58±2	local	~41GB	262k	Ollama ›
175	Granite 4.1 30B · 4-bit IBM	57±5*†	local	~19GB		Ollama ›
176	Phi-4-reasoning-plus 14B · 8-bit Microsoft	57±3†	local	~18GB		llama.cpp ›
177	Qwen3-VL 32B Thinking · 8-bit Alibaba	57±3*†	local	~39GB	256k	Ollama ›
178	Mistral Small 3.2 24B · 8-bit Mistral	57±1*	local	~32GB	128k	Ollama ›
180	Command A (03-2025) · 2-bit Cohere	57±1*	local	~37GB	256k	llama.cpp ›
186	Nemotron 3.5 Lightning 30B-A3B · 8-bit NVIDIA	56±1*	local	~42GB	262k	Ollama ›
187	Qwen3.5 4B · 4-bit Alibaba	56±3	local	~6.9GB	262k	LM Studio ›
188	Nemotron 3 Nano 4B · 8-bit NVIDIA	56±6*	local	~7GB	262k	Ollama ›
189	LFM2.5 1.2B Instruct · 4-bit Liquid AI	56±6*†	local	~2.8GB	33k	LM Studio ›
190	Qwen3 32B · 8-bit Alibaba	56±1	local	~43GB	131k	Ollama ›
192	QwQ-32B · 8-bit Alibaba	56±1	local	~43GB	131k	Ollama ›
193	Mellum2.1 12B-A2.5B Thinking · 8-bit JetBrains	56±8*†	local	~15GB		llama.cpp ›
195	Llama 3.3 Nemotron Super 49B v1.5 · 4-bit NVIDIA	55±1*	local	~33GB	131k	llama.cpp ›
198	Gemma 3 12B · 8-bit Google	55±1*	local	~17GB	131k	Ollama ›
199	Granite 4.2 30B · 8-bit IBM	55±1*	local	~39GB	131k	Ollama ›
201	Qwen3-VL 30B-A3B Instruct · 8-bit Alibaba	55±3*†	local	~37GB	256k	Ollama ›
202	MiniCPM5 2B · 4-bit OpenBMB	55±6*†	local	~4.3GB	131k	LM Studio ›
205	Phi-4-reasoning 14B · 8-bit Microsoft	54±3†	local	~21GB	33k	Ollama ›
208	Qwen3 8B · 8-bit Alibaba	54±3*†	local	~12GB	33k	Ollama ›
209	Qwen3 4B Instruct 2507 · 8-bit Alibaba	54±2†	local	~7.1GB	262k	Ollama ›
210	Qwen3-VL 32B Instruct · 8-bit Alibaba	54±3*†	local	~39GB	256k	Ollama ›
211	Llama 3.3 Nemotron Super 49B v1 · 4-bit NVIDIA	54±1	local	~33GB		llama.cpp ›
212	Nemotron Nano 9B v2 · 8-bit NVIDIA	54±3	local	~13GB	131k	llama.cpp ›
214	Olmo 3.1 32B Instruct · 8-bit Ai2	54±1*	local	~43GB	66k	Ollama ›
215	Qwen3 4B Thinking 2507 · 8-bit Alibaba	53±3*†	local	~7.1GB	262k	Ollama ›
219	Nemotron-Cascade-14B-Thinking · 8-bit NVIDIA	53±6*†	local	~18GB		llama.cpp ›
220	Qwen3-VL 8B Instruct · 4-bit Alibaba	53±3*†	local	~12GB	256k	LM Studio ›
222	Qwen3 30B-A3B (Apr 2025, hybrid) · 8-bit Alibaba	53±1	local	~41GB	33k	Ollama ›
224	Seed-OSS 36B Instruct · 8-bit ByteDance Seed	53±5*†	local	~48GB	524k	llama.cpp ›
226	Llama 4 Scout (109B-A17B) · 2-bit Meta	53±1*	local	~36GB	328k	llama.cpp ›
227	EXAONE 4.0 32B · 8-bit LG AI Research	53±4*†	local	~42GB	131k	llama.cpp ›
228	Molmo 2 8B · 8-bit Ai2	53±1*	local	~11GB		llama.cpp ›
229	Qwen3-VL 8B Thinking · 4-bit Alibaba	53±3*†	local	~12GB	256k	LM Studio ›
230	Olmo 3 7B Think · 8-bit Ai2	53±3	local	~11GB	66k	Ollama ›
231	gpt-oss-20b · 4-bit OpenAI	52±1*	local	~25GB	131k	LM Studio ›
233	Athene-V2-Chat 72B · 4-bit Nexusflow	52±1	local	~48GB	33k	Ollama ›
234	Qwen3-VL 4B Thinking · 8-bit Alibaba	52±3*†	local	~6.9GB	256k	Ollama ›
235	Gemma 3n E4B · 8-bit Google	52±1*	local	~12GB	32k	Ollama ›
238	Qwen3-VL 4B Instruct · 8-bit Alibaba	52±3*†	local	~6.9GB	256k	Ollama ›
239	Mistral Large 2 (2407) · 2-bit Mistral	52±1	local	~45GB	128k	llama.cpp ›
240	Granite 4.0 H Micro 3B · 4-bit IBM	52±5*†	local	~5.1GB	131k	LM Studio ›
242	Llama 3.3 70B Instruct · 4-bit Meta	52±1	local	~46GB	128k	Ollama ›
243	Nemotron 3 Nano 30B-A3B · 8-bit NVIDIA	52±1*	local	~42GB	262k	Ollama ›
244	Qwen3-VL 30B-A3B Thinking · 8-bit Alibaba	51±3*†	local	~37GB	256k	Ollama ›
245	Athene-70B · 4-bit Nexusflow	51±1*	local	~46GB		llama.cpp ›
246	Olmo 3 32B Think · 8-bit Ai2	51±1	local	~43GB	66k	Ollama ›
250	Qwen2.5 72B Instruct · 4-bit Alibaba	51±1	local	~48GB	33k	llama.cpp ›
251	Llama 3.1 Nemotron 70B Instruct · 4-bit NVIDIA	51±1	local	~47GB	128k	Ollama ›
253	Granite 4.1 8B · 4-bit IBM	51±1*	local	~11GB	131k	LM Studio ›
254	Gemma 2 9B IT SimPO · 16-bit Princeton NLP	51±1*	local	~21GB		how to run ›
256	Olmo 3 7B Instruct · 8-bit Ai2	50±3	local	~11GB	66k	Ollama ›
258	Gemma 3 4B · 8-bit Google	50±1	local	~7.4GB	131k	Ollama ›
259	Granite 4.1 3B · 4-bit IBM	50±5*†	local	~3.7GB		Ollama ›
260	Mistral Small 3.1 24B (2503) · 8-bit Mistral	50±1*	local	~32GB	128k	Ollama ›
261	Granite 4.0 Micro 3B · 8-bit IBM	50±5*†	local	~5.3GB	131k	llama.cpp ›
262	Command R7B (12-2024) · 8-bit Cohere	49±3*	local	~12GB	128k	Ollama ›
265	Qwen2.5 32B Instruct · 8-bit Alibaba	49±2	local	~43GB	131k	Ollama ›
266	Llama-3-Instruct-8B-SimPO-ExPO · 16-bit Chujie Zheng (ExPO)	49±2*	local	~18GB		how to run ›
267	Granite 4.2 3B · 8-bit IBM	49±1	local	~5.6GB	131k	llama.cpp ›
268	Granite 4.2 8B · 8-bit IBM	49±1*	local	~11GB	131k	llama.cpp ›
269	Olmo 3.1 32B Think · 8-bit Ai2	49±1	local	~43GB	66k	Ollama ›
270	Llama 3.1 Tulu 3 70B DPO · 4-bit Ai2	49±4*†	local	~46GB	131k	llama.cpp ›
271	Granite 4.0 H Small (32B-A9B) · 8-bit IBM	49±1	local	~38GB	131k	llama.cpp ›
274	Llama-3-Instruct-8B-SimPO · 16-bit Princeton NLP	49±2*	local	~18GB		how to run ›
275	Granite 4.0 H Tiny (7B-A1B) · 4-bit IBM	49±4*†	local	~9.3GB	131k	LM Studio ›
276	Gemma 2 27B IT · 8-bit Google	48±1	local	~36GB	8k	Ollama ›
277	Granite 4.0 H 1B · 8-bit IBM	48±4	local	~3.2GB	131k	Ollama ›
278	Llama 3.1 70B Instruct · 4-bit Meta	48±1	local	~46GB	128k	Ollama ›
280	Llama 3.1 Tulu 3 70B · 4-bit Ai2	48±1	local	~47GB	131k	Ollama ›
281	Llama 3.1 Nemotron 51B Instruct · 4-bit NVIDIA	48±1*	local	~34GB		llama.cpp ›
282	s1.1 32B · 8-bit Simple Scaling	48±4*	local	~38GB	33k	llama.cpp ›
283	Mellum2 12B-A2.5B Instruct · 8-bit JetBrains	48±4*†	local	~15GB	131k	llama.cpp ›
285	LFM2 2.6B · 4-bit Liquid AI	48±6*†	local	~4.3GB	33k	LM Studio ›
286	Qwen3 4B · 8-bit Alibaba	47±2	local	~7.1GB	33k	Ollama ›
288	Granite 4.0 1B · 16-bit IBM	47±3	local	~6.1GB	128k	Ollama ›
289	OLMo 2 13B Instruct (1124) · 8-bit Allen Institute for AI	47±3*†	local	~19GB	4k	Ollama ›
290	Qwen3.5 2B · 8-bit Alibaba	47±3	local	~4.9GB	262k	Ollama ›
291	Qwen2.5 14B Instruct · 8-bit Alibaba	47±3	local	~21GB	131k	Ollama ›
296	Mellum2 12B-A2.5B Thinking · 8-bit JetBrains	47±3*†	local	~15GB	131k	llama.cpp ›
298	Mistral Small 3 24B (2501) · 8-bit Mistral	47±1*	local	~32GB	32k	Ollama ›
299	Qwen3-VL 2B Thinking · 8-bit Alibaba	47±3*†	local	~4.2GB	256k	Ollama ›
302	Qwen2.5 Coder 32B Instruct · 8-bit Alibaba	46±1*	local	~43GB	131k	Ollama ›
303	Aya Expanse 32B · 8-bit Cohere	46±1*	local	~43GB	128k	Ollama ›
304	North Micro Vision Instruct (2.4B) · 4-bit Cohere	46±8*†	local	~3.8GB	128k	how to run ›
305	Mistral Small 4 (119B-A6.5B) · 2-bit Mistral	46±7*†	local	~40GB	262k	llama.cpp ›
306	Gemma 2 9B IT · 8-bit Google	46±1	local	~14GB	8k	Ollama ›
307	Llama 3 70B Instruct · 4-bit Meta	46±1	local	~47GB	8k	Ollama ›
309	Qwen2.5 7B Instruct · 8-bit Alibaba	45±2	local	~12GB	131k	Ollama ›
311	OpenThinker2 32B · 8-bit Open Thoughts	45±5*	local	~38GB	33k	llama.cpp ›
313	Qwen2 72B Instruct · 4-bit Alibaba	45±1	local	~48GB	131k	Ollama ›
315	Granite 3.3 8B Instruct · 8-bit IBM	45±4*†	local	~11GB	128k	llama.cpp ›
316	LFM2 1.2B · 4-bit Liquid AI	45±4*†	local	~2.8GB	33k	LM Studio ›
318	Command R Plus (04-2024) · 2-bit Cohere	44±1	local	~43GB	128k	llama.cpp ›
319	Phi-4 14B · 8-bit Microsoft	44±1	local	~21GB	16k	Ollama ›
320	OLMo 2 32B Instruct (0325) · 8-bit Ai2	44±1	local	~38GB		llama.cpp ›
321	Granite 3.2 8B Instruct · 8-bit IBM	44±4*†	local	~12GB	131k	Ollama ›
322	EXAONE 3.5 2.4B Instruct · 8-bit LG AI Research	44±3*†	local	~5.1GB	33k	Ollama ›
323	Qwen3 1.7B · 8-bit Alibaba	44±2	local	~4.6GB	33k	Ollama ›
324	Qwen2.5 3B Instruct · 8-bit Alibaba	44±3*	local	~5.9GB	33k	Ollama ›
325	Qwen2 7B Instruct · 8-bit Alibaba	44±3*	local	~12GB	131k	Ollama ›
326	Command R (08-2024) · 8-bit Cohere	44±1*	local	~43GB	128k	Ollama ›
327	Ministral 3 14B · 8-bit Mistral	43±3*	local	~20GB	262k	Ollama ›
328	LFM2 700M · 4-bit Liquid AI	43±4*†	local	~2.3GB	33k	LM Studio ›
329	Qwen1.5 110B Chat · 2-bit Alibaba	43±1	local	~45GB	32k	llama.cpp ›
330	Qwen3-VL 2B Instruct · 8-bit Alibaba	43±2*	local	~4.2GB	256k	Ollama ›
333	Jamba 1.5 Mini · 4-bit AI21 Labs	42±1	local	~34GB		llama.cpp ›
334	SmolLM3 3B · 8-bit Hugging Face	42±4*	local	~5.9GB	66k	llama.cpp ›
335	EXAONE 4.0 1.2B · 8-bit LG AI Research	42±3*†	local	~3.6GB	66k	llama.cpp ›
337	Ministral 8B (2410) · 8-bit Mistral	42±1	local	~10GB	128k	llama.cpp ›
338	Ministral 3 8B · 8-bit Mistral	42±6*†	local	~13GB	262k	Ollama ›
339	OLMo 2 7B Instruct (1124) · 8-bit Allen Institute for AI	42±4*†	local	~11GB	4k	Ollama ›
340	Qwen1.5 72B Chat · 4-bit Alibaba	41±1	local	~48GB	32k	llama.cpp ›
342	Aya Expanse 8B · 8-bit Cohere	41±1*	local	~12GB	8k	Ollama ›
345	Llama 3.1 Tulu 3 8B · 8-bit Ai2	40±1	local	~12GB	131k	Ollama ›
347	Command R (03-2024) · 8-bit Cohere	40±1	local	~46GB	128k	Ollama ›
350	Xwin-LM 70B v0.1 · 4-bit Xwin-LM	39±2*	local	~45GB		llama.cpp ›
351	Llama 3 8B Instruct · 8-bit Meta	39±1	local	~12GB	8k	Ollama ›
353	LFM2 350M · 4-bit Liquid AI	39±4*†	local	~1.9GB	33k	LM Studio ›
355	Llama 3.1 8B Instruct · 8-bit Meta	39±1	local	~12GB	128k	Ollama ›
356	Granite 3.1 8B Instruct · 8-bit IBM	39±1	local	~12GB	128k	Ollama ›
357	Yi 1.5 34B Chat · 8-bit 01.AI	39±1*	local	~45GB	4k	Ollama ›
359	Gemma 3 1B · 4-bit Google	38±2	local	~3GB	32k	LM Studio ›
360	Qwen3 0.6B · 8-bit Alibaba	38±3*	local	~3GB	33k	Ollama ›
361	Ministral 3 14B Reasoning 2512 · 4-bit Mistral	38±3*	local	~10GB	262k	LM Studio ›
362	Qwen1.5 32B Chat · 8-bit Alibaba	38±1*	local	~43GB	32k	Ollama ›
363	Phi-3-medium-4k-instruct · 8-bit Microsoft	38±1	local	~20GB	4k	Ollama ›
364	Gemma 2 2B IT · 8-bit Google	37±1*	local	~5.3GB	8k	Ollama ›
366	Mixtral 8x7B Instruct v0.1 · 4-bit Mistral	37±1	local	~31GB	32k	Ollama ›
369	InternLM2.5 20B Chat · 8-bit Shanghai AI Laboratory (InternLM)	37±1*	local	~27GB	33k	Ollama ›
370	InternLM2 Chat 20B · 16-bit Shanghai AI Laboratory (InternLM)	36±2*	local	~43GB		how to run ›
371	Mistral 7B Instruct v0.3 · 8-bit Mistral	36±2*	local	~11GB	32k	Ollama ›
372	Yi 34B Chat · 8-bit 01.AI	36±1	local	~45GB	4k	Ollama ›
373	Qwen1.5 14B Chat · 8-bit Alibaba	36±1	local	~20GB	32k	Ollama ›
374	Granite 3.3 2B Instruct · 8-bit IBM	36±3*†	local	~4.3GB	128k	llama.cpp ›
375	WizardLM 70B V1.0 · 4-bit Microsoft	35±1	local	~45GB		Ollama ›
376	OpenChat 3.5 0106 · 8-bit OpenChat	35±1*	local	~11GB	8k	Ollama ›
377	Tulu 2 DPO 70B · 4-bit Ai2	35±1	local	~45GB		llama.cpp ›
378	Granite 3.1 3B-A800M Instruct · 8-bit IBM	35±5*†	local	~5.2GB	131k	llama.cpp ›
380	Granite 3.0 8B Instruct · 8-bit IBM	35±1*	local	~12GB	4k	Ollama ›
381	OpenChat 3.5 · 8-bit OpenChat	35±1*	local	~11GB	8k	Ollama ›
382	DeepSeek LLM 67B Chat · 4-bit DeepSeek	35±1	local	~44GB	4k	Ollama ›
384	Gemma 4 E4B · 4-bit Google	35±2	local	~11GB	131k	LM Studio ›
385	Gemma 1.1 7B IT · 8-bit Google	35±1	local	~13GB	8k	Ollama ›
386	Granite 3.1 2B Instruct · 8-bit IBM	35±1	local	~5.2GB	128k	Ollama ›
388	Starling-LM 7B beta · 8-bit Nexusflow	34±1	local	~11GB	8k	Ollama ›
389	Ministral 3 3B · 8-bit Mistral	34±5*	local	~6.9GB	262k	Ollama ›
390	Deita 7B v1.0 · 4-bit HKUST NLP	34±2*	local	~32GB		how to run ›
391	Granite 4.0 H 350M · 4-bit IBM	34±4*†	local	~1.9GB	33k	LM Studio ›
392	Vicuna 33B v1.3 · 8-bit LMSYS	34±1	local	~44GB	2k	Ollama ›
393	OpenHermes 2.5 Mistral 7B · 16-bit Nous Research	34±1	local	~17GB		LM Studio ›
394	Granite 3.2 2B Instruct · 8-bit IBM	34±3*†	local	~5.2GB	131k	Ollama ›
395	Llama 3.2 3B Instruct · 8-bit Meta	33±1	local	~6.1GB	131k	Ollama ›
396	Llama 2 70B Chat · 4-bit Meta	33±1	local	~46GB	4k	Ollama ›
397	OLMo 2 1B Instruct (0425) · 8-bit Allen Institute for AI	33±4*†	local	~3.2GB	4k	llama.cpp ›
398	Starling-LM 7B alpha · 8-bit UC Berkeley (NEST)	33±1	local	~11GB	8k	Ollama ›
399	OpenThinker3 7B · 8-bit Open Thoughts	33±3*	local	~10GB	33k	llama.cpp ›
400	Nous Hermes 2 Mixtral 8x7B DPO · 4-bit Nous Research	33±1*	local	~31GB	33k	Ollama ›
401	Gemma 3 270M IT · 8-bit Google	32±5*†	local	~2.4GB	32k	Ollama ›
402	Granite 3.0 2B Instruct · 8-bit IBM	32±1*	local	~5.3GB	4k	Ollama ›
403	SmolLM2 360M Instruct · 4-bit Hugging Face	32±5*†	local	~2.3GB	8k	Ollama ›
404	QwQ-32B-Preview · 8-bit Alibaba	31±1*	local	~43GB	33k	Ollama ›
405	WizardLM 13B V1.2 · 4-bit Microsoft	31±1	local	~29GB		how to run ›
406	Mistral 7B Instruct v0.2 · 8-bit Mistral	31±1	local	~11GB	32k	Ollama ›
407	Tulu 2 DPO 13B · 16-bit Allen Institute for AI	31±2*	local	~29GB		how to run ›
408	Granite 3.1 1B-A400M Instruct · 8-bit IBM	31±5*†	local	~3GB	131k	Ollama ›
409	Granite 3.0 3B-A800M Instruct · 8-bit IBM	31±4*†	local	~5.3GB	4k	llama.cpp ›
410	SOLAR 10.7B Instruct v1.0 · 8-bit Upstage	31±1*	local	~16GB	4k	Ollama ›
411	Qwen3.5 0.8B · 8-bit Alibaba	31±4*†	local	~3.1GB	262k	Ollama ›
412	Dolphin 2.2.1 Mistral 7B · 8-bit Cognitive Computations	31±1	local	~11GB		Ollama ›
413	Qwen1.5 7B Chat · 8-bit Alibaba	31±1	local	~12GB	32k	Ollama ›
415	Qwen2.5 0.5B Instruct · 8-bit Alibaba	30±3*	local	~2.6GB	33k	Ollama ›
417	Qwen-14B-Chat · 16-bit Alibaba	30±1	local	~31GB		how to run ›
418	Phi-3-mini-4k-instruct (June 2024 update) · 4-bit Microsoft	30±1*	local	~5.8GB		LM Studio ›
419	Vicuna 13B v1.5 · 8-bit LMSYS	30±1	local	~18GB	4k	Ollama ›
420	Granite 4.0 350M · 16-bit IBM	30±4*†	local	~2.9GB	32k	Ollama ›
421	Llama 2 13B Chat · 8-bit Meta	29±1	local	~18GB	4k	Ollama ›
422	Code Llama 34B Instruct · 8-bit Meta	29±1*	local	~45GB	16k	Ollama ›
423	Zephyr 7B beta · 8-bit Hugging Face	29±1	local	~11GB		Ollama ›
424	Tulu 2 DPO 7B · 16-bit Allen Institute for AI	29±2*	local	~16GB		how to run ›
425	Phi-3-mini-128k-instruct (Apr 2024) · 16-bit Microsoft	29±1	local	~9.5GB		how to run ›
426	Gemma 7B IT · 8-bit Google	29±1	local	~13GB	8k	Ollama ›
427	Phi-3-mini-4k-instruct (Apr 2024) · 4-bit Microsoft	29±1*	local	~9.5GB		llama.cpp ›
428	Zephyr 7B alpha · 8-bit Hugging Face	28±1	local	~11GB		Ollama ›
430	Gemma 4 E2B · 4-bit Google	28±3	local	~7.7GB	131k	LM Studio ›
431	Llama 3.2 1B Instruct · 4-bit Meta	27±1	local	~5.2GB	131k	Ollama ›	+1
432	Code Llama 70B Instruct · 4-bit Meta	27±1*	local	~46GB	16k	Ollama ›
434	Vicuna 7B v1.5 · 8-bit LMSYS	27±1	local	~11GB	4k	Ollama ›
435	Gemma 1.1 2B IT · 8-bit Google	27±1	local	~5.2GB	8k	Ollama ›
436	SmolLM2 1.7B Instruct · 8-bit Hugging Face	27±1	local	~4.2GB	8k	Ollama ›
437	Granite 3.0 1B-A400M Instruct · 8-bit IBM	26±4*†	local	~3GB	4k	llama.cpp ›
438	Qwen2.5 1.5B Instruct · 8-bit Alibaba	26±3	local	~4GB	33k	Ollama ›
439	Mistral 7B Instruct v0.1 · 8-bit Mistral	26±1*	local	~9.6GB	8k	llama.cpp ›
440	Llama 2 7B Chat · 8-bit Meta	25±1	local	~11GB	4k	Ollama ›
441	Ghost 7B Alpha · 16-bit Ghost X	25±2*	local	~17GB		how to run ›
442	Nous-Hermes-13b · 16-bit Nous Research	25±2*	local	~29GB	2k	how to run ›
443	Qwen1.5 4B Chat · 8-bit Alibaba	24±1*	local	~7GB	32k	Ollama ›
444	Gemma 2B IT · 8-bit Google	23±1	local	~5.2GB	8k	Ollama ›
445	OLMo 7B Instruct · 16-bit Ai2	21±1*	local	~16GB		how to run ›
450	Falcon 40B Instruct · 4-bit TII	19±1	local	~29GB		llama.cpp ›
451	ChatGLM3-6B · 8-bit Zhipu AI (THUDM)	19±1*	local	~8.4GB		llama.cpp ›
452	Falcon 7B Instruct · 8-bit TII	18±2*	local	~9.3GB		llama.cpp ›
455	Qwen1.5 1.8B Chat · 4-bit Alibaba	16±5*	local	~3.1GB	33k	LM Studio ›
456	Phi-2 (2.7B) · 4-bit Microsoft	14±2*	local	~7.3GB	2k	how to run ›
457	OpenAssistant SFT-4 Pythia 12B · 4-bit LAION (OpenAssistant)	14±1	local	~27GB		how to run ›
460	FastChat-T5 3B · 4-bit LMSYS	10±1	local	~8.5GB		how to run ›
463	StableLM-Tuned-Alpha 7B · 4-bit Stability AI	6±1	local	~35GB		how to run ›
—	Hermes 3 Llama 3.1 70B · q4_k_m Nous Research	not yet calibrated	local	~46GB	131k	llama.cpp ›
—	Hermes 3 Llama 3.1 8B · q8_0 Nous Research	not yet calibrated	local	~12GB	128k	Ollama ›
—	Phi-3.5-mini-instruct · q8_0 Microsoft	not yet calibrated	local	~6.8GB	128k	Ollama ›
—	Phi-4-mini 3.8B · q8_0 Microsoft	not yet calibrated	local	~6.9GB	128k	Ollama ›
—	Qwen2 0.5B Instruct · q8_0 Alibaba	not yet calibrated	local	~2.6GB	32k	Ollama ›
—	Qwen2 1.5B Instruct · q8_0 Alibaba	not yet calibrated	local	~4GB	32k	Ollama ›

+ 235 more don't fit your machine or budget · show them

+ 66 models with fewer than 3 results left off, since one or two tests say little about overall ability · show them

472 of 588 catalogue models listed here · sources and licences

* new or thinly tested: ranked on too few benchmark results · † only the maker’s own numbers so far · ~RAM is estimated; full context may need more memory