llmrun

Apple · M6 · Desktop

Best AI Models for iMac 24" M6 (24 GB)

Runs 9B models well and fits 35B MoE; 14B and 27–31B fit but are slow (13 and 7 tok/s), and 70B doesn't fit in 20.5 GB.

24 GB unified20.5 GB for models170 GB/s16 TFLOPS FP162026
Buyabout $1,699

What LLMs can the iMac 24" M6 run?

#ModelSpeedllmrun ScoreQuant · Memory
1
Q4_K_M · 16.5 GB · 34.4 t/s
34.4 tok/sQ4_K_M · 16.5 GB
2
Qwen3.5 9BAlibaba
Q4_K_M · 6.6 GB · 18.7 t/s
18.7 tok/sQ4_K_M · 6.6 GB
3
Qwen3.5 4BAlibaba
Q4_K_M · 3.4 GB · 36.5 t/s
36.5 tok/sQ4_K_M · 3.4 GB
4
Q4_K_M · 13.1 GB · 37.6 t/s
37.6 tok/sQ4_K_M · 13.1 GB
5
Q4_K_M · 15.0 GB · 48.1 t/s
48.1 tok/sQ4_K_M · 15.0 GB
See all 322 models on the iMac 24" M6 →Bars = traction for models without a Score yet

About the iMac 24" M6 (24 GB)

The iMac 24" M6 is a mid-range 24 GB desktop: it runs 9B models well and fits 35B MoE. Among 24 GB machines, only the M5 Pro and M4 Pro write faster. macOS keeps about 3.5 GB, leaving 20.5 GB for models. With 16 TFLOPS it reads long prompts faster than most 24 GB machines: a 4K-token prompt takes 11 s. At its $1,699 MSRP it gives 11.0 tok/s per $1,000, 6th of the 8 machines compared here.

Speed in 24 GB#3170 GB/s
Prompt reading#216 TFLOPS
For models20.5 GBmacOS keeps 3.5 GB
ChipM6released 2026

iMac 24" M6 strengths and weaknesses

Strengths

  • Runs 35B MoE models: Qwen3.6 35B A3B at 33.5 tok/s in 19.8 GB

Weaknesses

  • 70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 20.5 GB usable here
  • Slow on large dense models: Qwen3.8 27B at 6.8 tok/s
  • Slow prompt reading: A 32K-token prompt on Gemma 4 26B A4B IT waits 1.5 min for the first token
  • No CUDA: vLLM, AWQ, GPTQ and FP8 builds don't run; use GGUF or MLX

Memory for models

20.5 GB of 24 GB
9B6.6 GB14B11.9 GB27–31B17.9 GB35B MoE19.8 GB
9B6.6 GB14B11.9 GB35B MoE19.8 GB
For models 20.5 GBmacOS keeps 3.5 GBModel size at Q4

70B models need 51.3 GB at Q4, more than the 20.5 GB available. The 32 GB config fits Qwen3.8 27B →Or rent an A100 (80 GB) from $1.07/hr →

Speed per dollar and per watt

On Qwen3.5 9B (9B params) at Q4_K_M. New means a shop price, either a street quote or the maker's own price; used is compared with used. The last two columns are the speed you get per $1,000 of price and per 100 W of power; higher is better. The iMac 24" M6 has no current new price, so it is shown at its MSRP.

MachineNew pricetok/stok/s per $1,000tok/s per 100 W
about $1,59930.0
18.8
21.4
about $1,09918.7
17.0
–
about $1,99930.0
15.0
–
about $2,49930.0
12.0
–
about $1,49916.9
11.3
–
about $1,69918.7
11.0
–
about $2,09918.7
8.9
–
about $2,19918.7
8.5
–
MachineUsed pricetok/stok/s per $1,000tok/s per 100 W
RTX 409024 GBBest used value
about $3,000103
34.3
22.9
about $7,000183
26.2
31.8
about $2,00045.1
22.6
31.1

Cost per token: the iMac 24" M6 against 16–36 GB machines and GPUs

On Qwen3.5 9B (9B params, Q4_K_M, 4K context). Speed, cost per token and power per token depend on the model.

≤16 GB24–36 GBthis desktopat MSRP
Cost per 1M output tokenson Qwen3.5 9B · card over 3 years + power
$5.76
Machine, MSRP
$5.76
Power
not published
3-year cost of ownership$1,699
Or rent an RTX 5090 in the cloud$0.50/hr

Renting costs as much as buying after ≈3,400 hours (≈2.3 years at 4 h a day).

Each dot is a machine or GPU; hover or tap it for its numbers, click to open it. Machines without a price for the chosen basis are left out. Machines without a published power figure are left out of Per watt and costed without power. How we calculate cost per token

Similar devices and alternatives

Other memory sizes of the same machine first, then machines and GPUs people weigh against it, each with the one reason it is worth a look. Speeds on Qwen3.5 9B.

iMac 24" M6 tokens per second by model size

Output speed depends on memory bandwidth (170 GB/s). Grey rows need more than the 20.5 GB available.

  1. 9BQwen3.5 9B · Q4_K_M · 6.6 GB
    18.7tok/s
  2. 14BQwen3 14B · Q4_K_M · 11.9 GB
    12.5tok/s
  3. 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB slow
    6.8tok/s
  4. 35B MoEQwen3.6 35B A3B · IQ4_XS · 19.8 GB tight · IQ4_XS
    33.5tok/s
  5. 70BLlama 3.3 70B Instruct · not at 4-bit
    needs 51.3 GB
  6. 120B MoEGPT OSS 120B · not at 4-bit
    needs 70.8 GB

Estimated speeds: Q4_K_M, 4K context, one user. How we estimate

Chip generations: writing vs compute

M1 → M5
Writing speed (tok/s)Compute (TFLOPS FP16)
1×2×3×4×M12021M22023M32023M42024M52026M1 · 5.2 TFLOPS FP16M1 · 7.5 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 11.0 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 11.3 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 13.2 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 16.9 tok/s · 153.6 GB/sCompute 3.1×Writing +125%
1×2×3×4×M12021M22023M32023M42024M52026M1 · 5.2 TFLOPS FP16M1 · 7.5 tok/s · 68.3 GB/sM2 · 7.2 TFLOPS FP16M2 · 11.0 tok/s · 100 GB/sM3 · 7 TFLOPS FP16M3 · 11.3 tok/s · 102.4 GB/sM4 · 8.6 TFLOPS FP16M4 · 13.2 tok/s · 120 GB/sM5 · 16 TFLOPS FP16M5 · 16.9 tok/s · 153.6 GB/sCompute 3.1×Writing +125%

Writing speed follows memory bandwidth and barely moved: 7.5 to 16.9 tok/s since the M1. Compute, which sets how fast prompts are read, grew 3.1×. Indexed to the M1; speeds on Qwen3.5 9B, same 16 GB.

All 1142 models on the iMac 24" M6

Featured only

Best quant that fits in 20.5 GB, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works

LLM models compatible with iMac 24" M6 (24 GB) — ranked by Score, recency and Fit
ModelVRAMScoreFit
Q4_K_M·49.7 t/s
14.2 GBA79, Runs well
Q4_K_M·21.3 t/s
5.6 GBB62, Decent
Qwen2.5 Coder 1.5B Instruct
Q4_K_M·93.0 t/s
1.7 GBS90, Runs great
Q4_K_M·36.7 t/s
3.6 GBA73, Runs well
Q4_K_M·12.5 t/s
11.8 GBB51, Decent
Q4_K_M·7.0 t/s
17.3 GBC37, Usable
Opt 6.7B
FP16·8.1 t/s
14.7 GBB45, Decent
Mistral Nemo Instruct 2407
Q4_K_M·14.7 t/s
11.0 GBB54, Decent
Q4_K_M·24.2 t/s
6.8 GBB64, Decent
Q4_K_M·12.5 t/s
11.8 GBB51, Decent
Gemma 3 27B IT
IQ4_XS·7.3 t/s
19.8 GBD19, Barely runs
Hermes 4.3 36B
Q3_K_M·6.5 t/s
20.1 GBD15, Barely runs
Q4_K_M·22.2 t/s
7.9 GBB62, Decent
Q3_K_M·7.2 t/s
19.0 GBD27, Barely runs
Clef Omni
Q2_K·44.3 t/s
20.4 GBC44, Usable

iMac 24" M6 specs

Specs

Chip
M6
CPU cores
10
GPU cores
10
Unified memory
24 GB
For models
20.5 GB (macOS keeps 3.5 GB)
Memory bandwidth
170 GB/s
FP16 (dense)
16 TFLOPS
Neural Engine
76 TOPS
Released
2026-11-06
MSRP
$1,699

iMac 24" M6 FAQ

Is the iMac 24" M6 (24 GB) worth it for local LLMs in 2026?

At its $1,699 MSRP it gives 11.0 tok/s per $1,000 on Qwen3.5 9B, 6th of the 8 machines compared here. It runs 9B models well and fits 35B MoE; 14B and 27–31B fit but are slow (13 and 7 tok/s), and 70B doesn't fit in 20.5 GB.

How much memory is available for AI on the iMac 24" M6 (24 GB)?

About 20.5 GB of the 24 GB. macOS keeps roughly 3.5 GB for itself and other apps.

What is the largest model the iMac 24" M6 (24 GB) can run?

Qwen3.6 35B A3B (36.0B) is the largest at 4-bit or better: at IQ4_XS it uses 19.8 GB, 97% of the available memory, and runs at about 33.5 tok/s.

Can the iMac 24" M6 (24 GB) run Gemma 4 26B A4B IT?

Yes. Gemma 4 26B A4B IT fits at Q4_K_M, using 16.5 GB of the 20.5 GB available, and it is the best model that runs well on this machine.

Can the iMac 24" M6 (24 GB) run 70B models?

No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 20.5 GB available.

How long does the iMac 24" M6 (24 GB) take to read a long prompt?

On Gemma 4 26B A4B IT, about 11 s for a 4K-token prompt and 1.5 min for a 32K-token document before the first word appears.

Is renting a GPU cheaper than buying the iMac 24" M6?

An RTX 5090 (32 GB) rents from $0.50/hr. Renting costs as much as buying after ≈3,400 hours (≈2.3 years at 4 h a day).