LLM ipi ni bora kwa Mac yenye GB 128?

Miongoni mwa modeli zenye Intelligence Index iliyochapishwa, Qwen3.8 27B ina alama ya juu zaidi kati ya zile zinazoenda vizuri ndani ya GB 128 (8-bit). Kubwa zaidi inayoenda vizuri ni Qwen3.5 122B A10B. Kwa code: Qwen3 Coder Next.

Je, GB 128 zinatosha kwa AI ya ndani kwenye Mac?

Modeli huria 47 kati ya 73 zilizo hapa zinaenda vizuri ndani yake kwa biti 4 au zaidi. Kwa chaguo-msingi macOS huiruhusu GPU kutumia takriban GB 96 kati yake; modeli na context yake lazima zitoshe humo.

Je, Mac ya GB 128 inaweza kuendesha gpt-oss-20b?

Ndiyo, 4.25-bit asili, kwa takriban tokeni 95–168 kwa sekunde kwenye M3 Max na 189–337 kwenye M1 Ultra.

LLM bora za ndani kwa Mac ya GB 128 (M1 hadi M5)

Mac zenye GB 128

Chipu 5 kuanzia M1 hadi M5 huja na GB 128. Fungua yoyote kuona orodha na kasi zake.

Zinaenda vizuri 51

Inatosha na kubakiza nafasi ya context, kwa tokeni 10 au zaidi kwa sekunde kwenye M1 Ultra.

Modeli	Toleo	Kumbukumbu	M3 Max	M1 Ultra
Qwen3.8 27B27B · Akili 33.7	8-bit	28.7 GB	12–21	13–22
Nemotron 3.5 Bolt 74B A9B74B · 9B zinazotumika · Akili 21.4	8-bit	78.6 GB	19–33	38–67
Qwen3.6 35B A3B35B · 3B zinazotumika · Akili 18.2	8-bit	37.2 GB	56–100	113–200
Muse Glimmer 30B29.6B · Akili 17.5	8-bit	31.5 GB	11–19	11–20
Qwen3.5 122B A10B122B · 10B zinazotumika · Akili 15.6	4-bit	68.6 GB	32–57	64–114
Gemma 4 31B30.7B · Akili 14.7	8-bit	32.6 GB	10–18	11–20
Nemotron 3.5 Lightning 30B A3B30B · 3B zinazotumika · Akili 12.9	8-bit	31.9 GB	56–100	113–200
Granite 4.2 30B30B · Akili 12.7	8-bit	31.9 GB	11–19	11–20
MiniCPM5 2B2.52B · Akili 12.5	8-bit	2.7 GB	67–119	133–237
gpt-oss-120b117B · 5.1B zinazotumika · Akili 11.6	4.25-bit asili	65.3 GB	67–119	133–237
Mistral Small 4 (119B)119B · 6.5B zinazotumika · Akili 11.3	4-bit	66.9 GB	49–86	97–173
Qwen3.5 9B9B · Akili 11.2	8-bit	9.6 GB	19–33	38–67
Granite 4.2 8B8B · Akili 11.1	8-bit	8.5 GB	21–38	42–75
Qwen3 Coder Next80B · 3B zinazotumika · Akili 9.2	8-bit	85 GB	56–100	113–200
Granite 4.2 3B3B · Akili 9.1	8-bit	3.2 GB	56–100	113–200
gpt-oss-20b21B · 3.6B zinazotumika · Akili 9	4.25-bit asili	13.8 GB	95–168	189–337
Nemotron 3 Nano 30B A3B30B · 3.5B zinazotumika · Akili 8.9	8-bit	31.9 GB	49–86	97–173
Gemma 4 E4B8B · Akili 8.9	8-bit	8.5 GB	38–67	75–133
Llama 4 Scout 17B-16E Instruct109B · 17B zinazotumika · Akili 6.5	6-bit	88.6 GB	13–23	26–46
Ministral 3 8B8.9B · Akili 5.5	8-bit	9.5 GB	19–34	38–67
Nemotron 3 Nano 4B3.97B · Akili 4.8	8-bit	4.2 GB	43–76	86–152
Ornith 1.5 122B122B · 10B zinazotumika	4-bit	68.6 GB	32–57	64–114
Nemotron 3 Super 120B A12B120B · 12B zinazotumika	4-bit	67.5 GB	26–47	53–94
GLM-4.5 Air106B · 12B zinazotumika	6-bit	86.1 GB	18–33	37–65
Qwen3 Coder 30B A3B Instruct30.5B · 3.3B zinazotumika	8-bit	32.4 GB	51–91	103–183
GLM-4.7 Flash30B · 3B zinazotumika	8-bit	31.9 GB	56–100	113–200
Qwen3.6 27B27B	8-bit	28.7 GB	12–21	13–22
Gemma 4 26B A4B25.2B · 3.8B zinazotumika	8-bit	26.8 GB	45–80	90–160
Devstral Small 2 (24B)24B	8-bit	25.5 GB	13–24	14–25
Magistral Small 1.2 (2509)24B	8-bit	25.5 GB	13–24	14–25
Mistral Small 3.2 (24B)24B	8-bit	25.5 GB	13–24	14–25
LFM2.5 24B A2B24B · 2B zinazotumika	8-bit	25.5 GB	86–152	171–305
Phi-4 Reasoning Vision 15B15B	8-bit	15.9 GB	11–20	23–40
Phi-4 (14B)14B	8-bit	14.9 GB	12–21	24–43
Gemma 4 12B Unified12B	8-bit	12.7 GB	14–25	28–50
Qwen3 8B8.2B	8-bit	8.7 GB	21–37	41–74
Llama 3.1 8B Instruct8B	8-bit	8.5 GB	21–38	42–75
Gemma 4 E2B5.1B	8-bit	5.4 GB	75–133	150–267
Qwen3.5 4B4B	8-bit	4.3 GB	42–74	84–149
Phi-4 mini instruct3.8B	8-bit	4 GB	45–80	90–160
Llama 3.2 3B Instruct3.21B	8-bit	3.4 GB	53–94	106–188
SmolLM3 3B3B	8-bit	3.2 GB	56–100	113–200
LFM2.5 2.6B2.69B	8-bit	2.9 GB	62–110	124–221
Qwen3.5 2B2B	8-bit	2.1 GB	86–152	171–305
Llama 3.2 1B Instruct1.23B	8-bit	1.3 GB	138–246	277–492
Qwen3.5 0.8B0.8B	8-bit	0.9 GB	200–356	400–711
Qwen3 0.6B0.6B	8-bit	0.6 GB	300–533	600–1067
Qwen3.8 Flash Next180B · 6B zinazotumika · Akili 39.8	3-bit ubora wa chini	78.8 GB	69–123	138–246
Inkling Small276B · 12B zinazotumika · Akili 25.7	2-bit ubora wa chini	86.3 GB	47–84	95–168
DeepSeek V4 Flash 0731284B · 13B zinazotumika	2-bit ubora wa chini	88.8 GB	44–78	88–156
MiniMax M2.7230B · 10B zinazotumika	2-bit ubora wa chini	71.9 GB	58–103	116–206

Zinaenda, lakini polepole 3

Inatosha, lakini chini ya tokeni 10 kwa sekunde: sawa kwa kazi za kundi, polepole kwa mazungumzo.

Modeli	Toleo	Kumbukumbu	M3 Max	M1 Ultra
Mistral Medium 3.5 (128B)128B · Akili 14.2	4-bit	72 GB	3–4	5–9
Devstral 2 (123B)123B	4-bit	69.2 GB	3–5	5–9
Llama 3.3 70B Instruct70B	8-bit	74.4 GB	2–4	5–9

Zinatosha kwa shida 3

Inahitaji karibu kumbukumbu yote: ongeza kikomo cha kumbukumbu ya GPU na weka context fupi.

Modeli	Toleo	Kumbukumbu	M3 Max	M1 Ultra
GLM-5.3 Flash320B · 18B zinazotumika · Akili 41.8	2-bit ubora wa chini	100 GB	32–57	64–114
MiMo V2.6 Flash309B · 15B zinazotumika · Akili 37.9	2-bit ubora wa chini	96.6 GB	38–68	77–136
Hy3295B · 21B zinazotumika · Akili 25.3	2-bit ubora wa chini	92.2 GB	27–48	55–97

Kubwa mno 16

Inahitaji kumbukumbu zaidi ya GB 128, hata kwa biti 2.

Maswali

LLM ipi ni bora kwa Mac yenye GB 128?: Miongoni mwa modeli zenye Intelligence Index iliyochapishwa, Qwen3.8 27B ina alama ya juu zaidi kati ya zile zinazoenda vizuri ndani ya GB 128 (8-bit). Kubwa zaidi inayoenda vizuri ni Qwen3.5 122B A10B. Kwa code: Qwen3 Coder Next.
Je, GB 128 zinatosha kwa AI ya ndani kwenye Mac?: Modeli huria 47 kati ya 73 zilizo hapa zinaenda vizuri ndani yake kwa biti 4 au zaidi. Kwa chaguo-msingi macOS huiruhusu GPU kutumia takriban GB 96 kati yake; modeli na context yake lazima zitoshe humo.
Je, Mac ya GB 128 inaweza kuendesha gpt-oss-20b?: Ndiyo, 4.25-bit asili, kwa takriban tokeni 95–168 kwa sekunde kwenye M3 Max na 189–337 kwenye M1 Ultra.

Ukubwa mwingine: 8 GB · 16 GB · 18 GB · 24 GB · 32 GB · 36 GB · 48 GB · 64 GB · 96 GB · 128 GB · 192 GB · 256 GB · 512 GB

Ziendeshe kwa MLX Harness (bure, open source) au mlx-lm ya Apple ndani ya Terminal: hatua kwa hatua.

Jinsi inavyokokotolewa

Kumbukumbu: vigezo vya modeli kwa biti 8, 6, 4, 3 au 2 kwa kila weight pamoja na group scales za MLX (nusu biti kwa kila weight), au muundo wake asili, pamoja na nafasi ya context juu yake. Kwa chaguo-msingi macOS huiruhusu GPU kutumia takriban 75% ya unified memory. Kasi: bandwidth ya kumbukumbu ikigawanywa kwa baiti zinazosomwa kwa kila tokeni ndiyo kikomo cha juu kwa mazungumzo moja; katika benchmarks za umma za llama.cpp kwenye Apple Silicon uendeshaji halisi hufikia takriban 45% hadi 80% yake, na huo ndio upana unaoonyeshwa. Haya ni makadirio, si vipimo: pima Mac yako mwenyewe kwenye MLX Bench. Takwimu za modeli ni kutoka kwa kadi rasmi ya kila modeli, takwimu za chipu ni kutoka Tech Specs za Apple. Imekaguliwa 2026-10-19. Data ileile ya mlx.app/compare.