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

Best AI models for web search to run locally on a 64GB Mac

A leaderboard of the best AI models for web search you can run locally on a Mac with 64GB of memory. Mistral Small 3.1 24B (2503) is #1 right now, followed by Llama 4 Scout (109B-A17B) and Command A (03-2025). Models are ranked on web research tests like BrowseComp, with search turned on. Each model shows the download that fits and the command to run it.

31 models · scores combine 12 benchmarks · updated how it works · find a leaderboard · benchmark your machine
task[all tasks][agent tasks][coding][chat & writing][math][vision & documents][web search]

Scores use reviewed web search 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][Arena search systems (style controlled) · 96][BrowseComp-ZH · 13][BrowseComp-ZH · 5][BrowseComp-ZH · 3][Humanity's Last Exam with tools · 3][BrowseComp with context management · 3][BrowseComp with context management · 2][Humanity's Last Exam with tools · 2][Humanity's Last Exam with tools · 2][BrowseComp · 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

detecting your OS…

Run curl "whatmodel.sh/?ram=64&gpu=apple&max=0"to get this list in your terminal (add &format=json for agents).

ram[8][16][24][32][48][64][96][128][192][256]GB
gpu[apple silicon][graphics card][none]
price[local][$0.05][$0.25][$1][$5][$20][any]max per M

detecting your OS…

Score vs memory to run

#modeltask score↓where↓speed↓RAM↓context↓get itsources
#modeltask score↓where↓speed↓RAM↓context↓get itsources
16Mistral Small 3.1 24B (2503) · 8-bit Mistral62±3*local~32GB128kOllama › Finance Agent Benchmark (Vals AI, arXiv:2508.00828v1)
39Llama 4 Scout (109B-A17B) · 2-bit Meta52±4*local~36GB328kllama.cpp › Finance Agent Benchmark (Vals AI, arXiv:2508.00828v1)
50Command A (03-2025) · 2-bit Cohere49±5*local~37GB256kllama.cpp › Finance Agent Benchmark (Vals AI, arXiv:2508.00828v1)
52Muse Glimmer 30B · 8-bit Meta48±6*†local~40GB131kOllama › meta-models/Muse-Glimmer-30B model card (speed and benchmark tables)
56Qwen3.6 27B · 8-bit Alibaba46±6*local~37GB262kOllama › meta-models/Muse-Glimmer-30B model card (speed and benchmark tables)
64Llama 3.3 70B Instruct · 4-bit Meta42±6*local~46GB128kOllama › Finance Agent Benchmark (Vals AI, arXiv:2508.00828v1)
71Qwen3.5 27B · 8-bit Alibaba41±3†local~37GB262kOllama › Qwen/Qwen3.5-122B-A10B model cardQwen/Qwen3.6-35B-A3B model card
74Qwen3.5 35B-A3B · 8-bit Alibaba39±3†local~47GB262kOllama › Qwen/Qwen3.5-122B-A10B model cardQwen/Qwen3.6-35B-A3B model card
76Gemma 4 31B · 4-bit Google38±3local~37GB262kLM Studio › K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts (arXiv:2606.02404v1)meta-models/Muse-Glimmer-30B model card (speed and benchmark tables)google/gemma-4-31B-it model card
83Qwen3.6 35B-A3B · 4-bit Alibaba34±4*local~41GB262kLM Studio › K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts (arXiv:2606.02404v1)Qwen/Qwen3.6-35B-A3B model card
88Gemma 4 26B-A4B · 4-bit Google23±8*†local~31GB262kLM Studio › google/gemma-4-31B-it model card
91GLM-4.5-Air · 2-bit Z.ai19±6*†local~35GB131kllama.cpp › GLM-4.5 Team (Zhipu AI & Tsinghua) — GLM-4.5 technical report
—Gemma 4 12B · Q8_0 Googlenot yet calibratedlocal~15GB262kllama.cpp › XHToken/Spark-X2.5-4B model card
—Gemma 4 E2B · mlx-8bit Googlenot yet calibratedlocal~7.7GB131kLM Studio › openbmb/MiniCPM5-2B model cardXHToken/Spark-X2.5-4B model card
—Gemma 4 E4B · mlx-8bit Googlenot yet calibratedlocal~11GB131kLM Studio › openbmb/MiniCPM5-2B model cardXHToken/Spark-X2.5-4B model card
—GLM-4.7-Flash · Q8_0 Z.ainot scored yetlocal~35GB200kllama.cpp ›
—gpt-oss-20b · mlx-8bit OpenAInot yet calibratedlocal~25GB131kLM Studio › OpenAI — gpt-oss-120b & gpt-oss-20b Model Card
—Granite 4.2 3B · Q8_0 IBMnot yet calibratedlocal~5.6GB131kllama.cpp › openbmb/MiniCPM5-2B model card
—K2 Horizon 7B · gguf-q8_0 Institute of Foundation Models (MBZUAI)not scored yetlocal~13GB524kllama.cpp ›
—LFM2.5 2.6B · mlx-8bit Liquid AInot yet calibratedlocal~4.5GB131kLM Studio › openbmb/MiniCPM5-2B model card
—LFM2.5 8B-A1B · q8_0 Liquid AInot yet calibratedlocal~13GB128kOllama › openbmb/MiniCPM5-2B model card
—MiniCPM5 2B · mlx-8bit OpenBMBnot yet calibratedlocal~4.3GB131kLM Studio › openbmb/MiniCPM5-2B model card
—Nemotron 3 Nano 30B-A3B · q8_0 NVIDIAnot scored yetlocal~42GB262kOllama ›
—Nemotron 3 Nano 4B · q8_0 NVIDIAnot yet calibratedlocal~7GB262kOllama › openbmb/MiniCPM5-2B model card
—Ornith 1.0 35B (35B-A3B) · mlx-8bit DeepReinforcenot yet calibratedlocal~41GB262kLM Studio › ornith-ai/Ornith-1.5-35B-A3B model card
—Ornith 1.5 35B-A3B · Q8_0 DeepReinforcenot yet calibratedlocal~41GB262kllama.cpp › ornith-ai/Ornith-1.5-35B-A3B model card
—Qwen3.5 2B · q8_0 Alibabanot yet calibratedlocal~4.9GB262kOllama › openbmb/MiniCPM5-2B model cardXHToken/Spark-X2.5-4B model card
—Qwen3.5 4B · mlx-8bit Alibabanot yet calibratedlocal~6.9GB262kLM Studio › openbmb/MiniCPM5-2B model cardXHToken/Spark-X2.5-4B model card
—Qwen3.5 9B · mlx-8bit Alibabanot yet calibratedlocal~12GB262kLM Studio › XHToken/Spark-X2.5-4B model card
—Spark-X2.5 1.7B · bf16 iFLYTEK (SparkLLM)not yet calibratedlocal~5.1GB1MOllama › XHToken/Spark-X2.5-4B model card
—Spark-X2.5 4B · bf16 iFLYTEK (SparkLLM)not yet calibratedlocal~10GB1MOllama › XHToken/Spark-X2.5-4B model card

+ 100 more don't fit your machine or budget · show them

131 of 135 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