CanRun

Which local LLMs can the Apple M6 (Mac mini) run?

Unified memory — by default the GPU can use about 70% of it

Assumes 8k context and an f16 KV cache. Verdicts are shown for each memory size.

Specs

Memory options
16 GB · 24 GB · 32 GB
Memory bandwidth
153.6–170.6 GB/s
FP16 compute
5.3 TFLOPS
Launch year
2026
Macs with this chip
  • Mac mini: 16 GB · 24 GB · 32 GB
Also written as
M6

Verdicts at a glance

At Q4_K_M (or the closest available quant) with 8k context.

  • 16 GBRuns great13 modelsRuns well10 modelsRuns slowly5 modelsWon't run30 models5 more models run at a lower quant.
  • 24 GBRuns great17 modelsRuns well13 modelsRuns slowly10 modelsWon't run18 models7 more models run at a lower quant.
  • 32 GBRuns great20 modelsRuns well13 modelsRuns slowly15 modelsWon't run10 models1 more model runs at a lower quant.

How to read the verdicts

Runs great
Fully on the GPU at 20 tok/s or more
Runs well
Fully on the GPU at 8–20 tok/s; MoE experts in system RAM at 20 tok/s or more; or at least 90% on the GPU at 8 tok/s or more
Runs slowly
2–8 tok/s; CPU-only; less than 90% on the GPU; or MoE experts in system RAM below 20 tok/s
Won't run
Does not fit, or under 2 tok/s

Every model on the Apple M6

Scroll sideways to see every column.

58 models sorted by verdict and speed, with 32 GB of memory
ModelVerdictSpeedQuantMemoryRuns asContextNotes
MiniCPM5 1B
Runs great
est. 145.5 tok/s116.4–174.6calibrated estimate ±20%
Q4_K_M1.5 / 22.4 GBUnified memoryup to 128k
  • thinking mode
Ling-3.0 Tiny
Runs great
est. 124.4 tok/s87.1–161.7theoretical estimate ±30%
Q4_K_M5.5 / 22.4 GBUnified memoryup to 128k
  • thinking mode
Llama 3.2 1B
Runs great
est. 120.2 tok/s96.2–144.3calibrated estimate ±20%
Q4_K_M1.7 / 22.4 GBUnified memoryup to 128k—
EXAONE 4.0 1.2B
Runs great
est. 98.7 tok/s79.0–118.5calibrated estimate ±20%
Q4_K_M1.9 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Gemma 4 E2B
Runs great
est. 73.0 tok/s51.1–94.8theoretical estimate ±30%
Q4_K_M3.7 / 22.4 GBUnified memoryup to 128k
  • thinking mode
LFM2.5 2.6B
Runs great
est. 71.9 tok/s50.3–93.4theoretical estimate ±30%
Q4_K_M2.4 / 22.4 GBUnified memoryup to 128k
  • thinking mode
HyperCLOVA X SEED 1.5B
Runs great
est. 71.4 tok/s57.1–85.7calibrated estimate ±20%
Q4_K_M2.4 / 22.4 GBUnified memoryup to 16k—
Mellum2.1 12B-A2.5B Thinking
Runs great
est. 69.4 tok/s55.6–83.3calibrated estimate ±20%
Q4_K_M8.8 / 22.4 GBUnified memoryup to 128k
  • thinking mode
MiniCPM5 2B
Runs great
est. 67.8 tok/s54.2–81.4calibrated estimate ±20%
Q4_K_M2.5 / 22.4 GBUnified memoryup to 32k
  • thinking mode
MiniCPM-V 4.7 35B-A3B
Runs great
est. 50.8 tok/s40.6–60.9calibrated estimate ±20%
Q4_K_M21.9 / 22.4 GBUnified memoryup to 16k
  • thinking mode
gpt-oss-20b
Runs great
est. 44.8 tok/s35.8–53.7calibrated estimate ±20%
MXFP412.9 / 22.4 GBUnified memoryup to 64k
  • thinking mode
Spark-X2.5 4B
Runs great
est. 44.7 tok/s35.7–53.6calibrated estimate ±20%
Q4_K_M3.5 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Llama 3.2 3B
Runs great
est. 43.8 tok/s35.0–52.6calibrated estimate ±20%
Q4_K_M3.5 / 22.4 GBUnified memoryup to 32k—
Qwen3.5 4B
Runs great
est. 41.8 tok/s33.5–50.2calibrated estimate ±20%
Q4_K_M3.7 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Qwen3 30B-A3B (2507)
Runs great
est. 40.4 tok/s32.3–48.5calibrated estimate ±20%
Q4_K_M19.9 / 22.4 GBUnified memoryup to 16k—
Kanana 1.5 15.7B-A3B
Runs great
est. 40.2 tok/s32.1–48.2calibrated estimate ±20%
Q4_K_M12.1 / 22.4 GBUnified memoryup to 32k—
Gemma 4 E4B
Runs great
est. 38.1 tok/s26.7–49.6theoretical estimate ±30%
Q4_K_M5.7 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Gemma 4 26B-A4B
Runs great
est. 32.8 tok/s26.3–39.4calibrated estimate ±20%
Q4_K_M17.7 / 22.4 GBUnified memoryup to 16k
  • thinking mode
Kanana 1.5 8B
Runs great
est. 21.6 tok/s17.3–26.0calibrated estimate ±20%
Q4_K_M6.6 / 22.4 GBUnified memoryup to 8k—
Llama 3.1 8B
Runs great
est. 21.6 tok/s17.3–26.0calibrated estimate ±20%
Q4_K_M6.6 / 22.4 GBUnified memoryup to 8k—
DeepSeek R1 Distill Llama 8B
Runs well
est. 21.6 tok/s17.3–26.0calibrated estimate ±20%
Q4_K_M6.6 / 22.4 GBUnified memoryup to 32k
  • Q2_K (heavy quality loss): Runs great
  • thinking mode
Nanbeige4.2 3B
Runs well
est. 21.2 tok/s14.8–27.5theoretical estimate ±30%
Q4_K_M4.7 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Qwen3.5 9B
Runs well
est. 21.1 tok/s16.9–25.3calibrated estimate ±20%
Q4_K_M6.7 / 22.4 GBUnified memoryup to 128k
  • thinking mode
DeepSeek R1 0528 Qwen3 8B
Runs well
est. 20.8 tok/s16.6–24.9calibrated estimate ±20%
Q4_K_M6.8 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Qwen3 8B
Runs well
est. 20.8 tok/s16.6–24.9calibrated estimate ±20%
Q4_K_M6.8 / 22.4 GBUnified memoryup to 32k
  • thinking mode
K2-Horizon 7B
Runs well
est. 19.1 tok/s15.3–22.9calibrated estimate ±20%
Q4_K_M7.4 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Gemma 4 12B
Runs well
est. 17.9 tok/s14.3–21.4calibrated estimate ±20%
Q4_K_M7.8 / 22.4 GBUnified memoryup to 128k
  • thinking mode
Gemma 3 12B
Runs well
est. 16.5 tok/s13.2–19.9calibrated estimate ±20%
Q4_K_M8.4 / 22.4 GBUnified memoryup to 128k
  • Q2_K (heavy quality loss): Runs great
HyperCLOVA X SEED Think 14B
Runs well
est. 12.7 tok/s8.9–16.5theoretical estimate ±30%
Q4_K_M10.8 / 22.4 GBUnified memoryup to 8k
  • thinking mode
Qwen3 14B
Runs well
est. 12.5 tok/s10.0–15.0calibrated estimate ±20%
Q4_K_M10.9 / 22.4 GBUnified memoryup to 8k
  • thinking mode
DeepSeek R1 Distill Qwen 14B
Runs well
est. 12.2 tok/s9.8–14.7calibrated estimate ±20%
Q4_K_M11.2 / 22.4 GBUnified memoryup to 8k
  • thinking mode
Phi-4
Runs well
est. 12.1 tok/s9.7–14.5calibrated estimate ±20%
Q4_K_M11.3 / 22.4 GBUnified memoryup to 16k—
Mistral Small 3.2 24B
Runs well
est. 8.3 tok/s6.6–9.9calibrated estimate ±20%
Q4_K_M16.2 / 22.4 GBUnified memoryup to 8k—
Qwen3.6 35B-A3B
Runs slowly
est. 36.2 tok/s25.3–47.0theoretical estimate ±30%
Q4_K_M22.5 GB RAMCPU onlyup to 256k
  • CPU inference — capped at Runs slowly
  • Try IQ4_XS: Runs great
  • thinking mode
Qwen3.5 35B-A3B
Runs slowly
est. 35.7 tok/s25.0–46.4theoretical estimate ±30%
Q4_K_M22.8 GB RAMCPU onlyup to 256k
  • CPU inference — capped at Runs slowly
  • Try IQ4_XS: Runs great
  • thinking mode
Nemotron 3.5 Lightning 30B-A3B
Runs slowly
est. 29.7 tok/s20.8–38.6theoretical estimate ±30%
Q4_K_M25.5 GB RAMCPU onlyup to 256k
  • CPU inference — capped at Runs slowly
  • Try IQ4_XS: Runs great
  • thinking mode
K2-Horizon MoVA 36B-A4B
Runs slowly
est. 18.3 tok/s12.8–23.8theoretical estimate ±30%
Q4_K_M24.0 GB RAMCPU onlyup to 16k
  • CPU inference — capped at Runs slowly
  • thinking mode
Gemma 3 27B
Runs slowly
est. 7.5 tok/s6.0–9.0calibrated estimate ±20%
Q4_K_M17.8 / 22.4 GBUnified memoryup to 32k
  • Try IQ4_XS: Runs well
Qwen3.6 27B
Runs slowly
est. 7.5 tok/s6.0–9.0calibrated estimate ±20%
Q4_K_M17.9 / 22.4 GBUnified memoryup to 64k
  • thinking mode
Muse Glimmer 30B
Runs slowly
est. 7.4 tok/s6.0–8.9calibrated estimate ±20%
Q4_K_M18.0 / 22.4 GBUnified memoryup to 128k
  • thinking mode
Qwen3.5 27B
Runs slowly
est. 7.3 tok/s5.9–8.8calibrated estimate ±20%
Q4_K_M18.2 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Qwen3.8 27B
Runs slowly
est. 7.2 tok/s5.8–8.7calibrated estimate ±20%
Q4_K_M18.6 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Gemma 4 31B
Runs slowly
est. 6.8 tok/s5.5–8.2calibrated estimate ±20%
Q4_K_M19.6 / 22.4 GBUnified memoryup to 32k
  • thinking mode
Granite 4.2 30B
Runs slowly
est. 6.5 tok/s5.2–7.8calibrated estimate ±20%
Q4_K_M20.4 / 22.4 GBUnified memoryup to 8k
  • thinking mode
EXAONE 4.0 32B
Runs slowly
est. 6.5 tok/s5.2–7.8calibrated estimate ±20%
Q4_K_M20.5 / 22.4 GBUnified memoryup to 32k
  • thinking mode
EXAONE 4.5 33B
Runs slowly
est. 6.3 tok/s5.0–7.6calibrated estimate ±20%
Q4_K_M21.2 / 22.4 GBUnified memoryup to 16k
  • thinking mode
Qwen3 32B
Runs slowly
est. 3.9 tok/s2.7–5.1theoretical estimate ±30%
Q4_K_M21.9 GB RAMCPU onlyup to 16k
  • thinking mode
DeepSeek R1 Distill Qwen 32B
Runs slowly
est. 3.9 tok/s2.7–5.0theoretical estimate ±30%
Q4_K_M22.0 GB RAMCPU onlyup to 16k
  • thinking mode
Llama 3.3 70B
Won't runTry IQ2_M (heavy quality loss): Runs slowly
est. 3.2 tok/s2.2–4.1theoretical estimate ±30%
IQ2_M26.8 GB RAMCPU onlyup to 8k—
DeepSeek V4 Flash 0731
Won't run
—MXFP4needs 155.6 GB——
  • Needs about 155.6 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
GLM-5.3 Flash
Won't run
—Q4_K_Mneeds 182.1 GB——
  • Needs about 182.1 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
gpt-oss-120b
Won't run
—MXFP4needs 64.3 GB——
  • Needs about 64.3 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Kolibri 1
Won't run
—Q4_K_Mneeds 50.5 GB——
  • Needs about 50.5 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Laguna S 2.1
Won't run
—Q4_K_Mneeds 68.6 GB——
  • Needs about 68.6 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Ling-3.0 Flash
Won't run
—Q4_K_Mneeds 77.7 GB——
  • Needs about 77.7 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Qwen3.5 122B-A10B
Won't run
—Q4_K_Mneeds 79.0 GB——
  • Needs about 79.0 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Solar Open 100B
Won't run
—Q4_K_Mneeds 64.4 GB——
  • Needs about 64.4 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode
Solar Open 2 250B
Won't run
—IQ4_XSneeds 137.2 GB——
  • Needs about 137.2 GB; 28.0 GB of memory is free (22.4 GB usable by the GPU)
  • thinking mode

Models with a thinking mode spend extra tokens thinking, so their speed thresholds are 1.5× stricter (30 / 12 / 3 tok/s). With thinking turned off, a model may do one grade better.

Verdict by memory size

Q4_K_M verdict for each memory configuration — open the model page for speeds
Model16 GB24 GB32 GB
MiniCPM5 1BRuns greatRuns greatRuns great
Ling-3.0 TinyRuns greatRuns greatRuns great
Llama 3.2 1BRuns greatRuns greatRuns great
EXAONE 4.0 1.2BRuns greatRuns greatRuns great
Gemma 4 E2BRuns greatRuns greatRuns great
LFM2.5 2.6BRuns greatRuns greatRuns great
HyperCLOVA X SEED 1.5BRuns greatRuns greatRuns great
Mellum2.1 12B-A2.5B ThinkingRuns greatRuns greatRuns great
MiniCPM5 2BRuns greatRuns greatRuns great
MiniCPM-V 4.7 35B-A3BWon't runWon't runRuns great
gpt-oss-20bWon't runRuns greatRuns great
Spark-X2.5 4BRuns greatRuns greatRuns great
Llama 3.2 3BRuns greatRuns greatRuns great
Qwen3.5 4BRuns greatRuns greatRuns great
Qwen3 30B-A3B (2507)Won't runRuns slowlyRuns great
Kanana 1.5 15.7B-A3BRuns slowlyRuns greatRuns great
Gemma 4 E4BRuns greatRuns greatRuns great
Gemma 4 26B-A4BWon't runRuns slowlyRuns great
Kanana 1.5 8BRuns wellRuns greatRuns great
Llama 3.1 8BRuns wellRuns greatRuns great
DeepSeek R1 Distill Llama 8BRuns wellRuns wellRuns well
Nanbeige4.2 3BRuns wellRuns wellRuns well
Qwen3.5 9BRuns wellRuns wellRuns well
DeepSeek R1 0528 Qwen3 8BRuns wellRuns wellRuns well
Qwen3 8BRuns wellRuns wellRuns well
K2-Horizon 7BRuns wellRuns wellRuns well
Gemma 4 12BRuns wellRuns wellRuns well
Gemma 3 12BRuns wellRuns wellRuns well
HyperCLOVA X SEED Think 14BRuns slowlyRuns wellRuns well
Qwen3 14BRuns slowlyRuns wellRuns well
DeepSeek R1 Distill Qwen 14BRuns slowlyRuns wellRuns well
Phi-4Runs slowlyRuns wellRuns well
Mistral Small 3.2 24BWon't runRuns wellRuns well
Qwen3.6 35B-A3BWon't runWon't runRuns slowly
Qwen3.5 35B-A3BWon't runWon't runRuns slowly
Nemotron 3.5 Lightning 30B-A3BWon't runWon't runRuns slowly
K2-Horizon MoVA 36B-A4BWon't runWon't runRuns slowly
Gemma 3 27BWon't runRuns slowlyRuns slowly
Qwen3.6 27BWon't runRuns slowlyRuns slowly
Muse Glimmer 30BWon't runRuns slowlyRuns slowly
Qwen3.5 27BWon't runRuns slowlyRuns slowly
Qwen3.8 27BWon't runRuns slowlyRuns slowly
Gemma 4 31BWon't runRuns slowlyRuns slowly
Granite 4.2 30BWon't runRuns slowlyRuns slowly
EXAONE 4.0 32BWon't runRuns slowlyRuns slowly
EXAONE 4.5 33BWon't runWon't runRuns slowly
Qwen3 32BWon't runWon't runRuns slowly
DeepSeek R1 Distill Qwen 32BWon't runWon't runRuns slowly
Llama 3.3 70BWon't runWon't runWon't run
DeepSeek V4 Flash 0731Won't runWon't runWon't run
GLM-5.3 FlashWon't runWon't runWon't run
gpt-oss-120bWon't runWon't runWon't run
Kolibri 1Won't runWon't runWon't run
Laguna S 2.1Won't runWon't runWon't run
Ling-3.0 FlashWon't runWon't runWon't run
Qwen3.5 122B-A10BWon't runWon't runWon't run
Solar Open 100BWon't runWon't runWon't run
Solar Open 2 250BWon't runWon't runWon't run

Measured results on the Apple M6

Public benchmarks we calibrate against. Their conditions (context, backend, flags) can differ from the estimates above.

Measured results on the Apple M6
ModelQuantBackendContextPrompt (tok/s)Generation (tok/s)FlagsSourceMeasured
llama-2-7bQ4_0llama.cpp512989.035.7Metal, FAgithub.com2026-10-01

Frequently asked questions

What is the largest model that runs entirely on the Apple M6?

Qwen3.5 35B-A3B at IQ4_XS (a 18.17 GB file) fits entirely in 32 GB of unified memory with 8k context, at est. 42.4 tok/s (33.9–50.9, calibrated estimate ±20%).

How many local LLMs run well on the Apple M6?

At Q4_K_M with 8k context, with 32 GB of memory, out of 58 tracked models: 20 run great, 13 run well, 15 run slowly and 10 won't run.

Can the Apple M6 run a 70B model like Llama 3.3 70B?

Runs slowly — CPU only, IQ2_M (heavy quality loss): est. 3.2 tok/s (2.2–4.1, theoretical estimate ±30%).

Speeds are estimates from memory bandwidth, calibrated against public benchmarks, and each one comes with an error band and a confidence label. Real results vary with drivers, backend, context length and thermals.

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