FitMyLLM
APPLE· M2 MAX

Apple M2 Max (64GB)

Running LLMs on the Apple M2 Max (64GB) — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $2,299 buys

USABLE MEMORY
48 GB
FLAGSHIP
BANDWIDTH
400
GB/S
MODELS Q4
345/449
77%
7B Q4 SPEED
~51
BLAZING
▸ MODEL COVERAGE @ Q477% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

Average speeds at Q4 quantization. Actual performance varies by model architecture and context length.

3B
~119
TOK/S
7B
~51
TOK/S
14B
~25
TOK/S
32B
~11
TOK/S
70B
~5
TOK/S
▸ MEASURED RIG REPORTS

We rent the machine and time every model on it: decode, VRAM peak, concurrency, watts and cost per million tokens. Yours may already be one of them — and two are free to read in full.

SEE THE REPORTS
▸ SPECIFICATIONS
USABLE MEMORY
48 GB of 64
BANDWIDTH
400 GB/s
FP16 COMPUTE
13.6 TFLOPS
TDP
60W
MEMORY
LPDDR5
ARCHITECTURE
M2 Max
MSRP
$2,299
252
FAST MODELS · >30 TOK/S
Real-time chat speed
341
USABLE · >10 TOK/S
Comfortable for all tasks
345
TOTAL COMPATIBLE
Fit in usable memory at Q4
▸ DON’T WANT TO BUY?

Test M2 Max (64GB) (or anything bigger) without committing. Pay by the second, cancel anytime.

Spin up in ~60s. Pay by the second. Cancel anytime.

Some links are affiliate links — we may earn a small commission at no extra cost to you. This helps keep FitMyLLM free and independent.

▸ COMPATIBLE MODELS· 345
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
3951
TOK/S · 1% MEM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
2634
TOK/S · 1% MEM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
2540
TOK/S · 1% MEM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
2540
TOK/S · 1% MEM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
1389
TOK/S · 1% MEM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
1317
TOK/S · 1% MEM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
1166
TOK/S · 1% MEM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
1061
TOK/S · 1% MEM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
1061
TOK/S · 1% MEM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
1061
TOK/S · 1% MEM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
1016
TOK/S · 1% MEM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
988
TOK/S · 1% MEM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
936
TOK/S · 2% MEM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
711
TOK/S · 2% MEM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
711
TOK/S · 2% MEM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
684
TOK/S · 2% MEM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
626
TOK/S · 2% MEM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
626
TOK/S · 2% MEM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
593
TOK/S · 2% MEM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
593
TOK/S · 2% MEM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
593
TOK/S · 2% MEM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
573
TOK/S · 2% MEM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
480
TOK/S · 2% MEM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
474
TOK/S · 2% MEM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
439
TOK/S · 2% MEM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
409
TOK/S · 2% MEM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
378
TOK/S · 2% MEM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
329
TOK/S · 2% MEM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
323
TOK/S · 2% MEM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
296
TOK/S · 3% MEM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
296
TOK/S · 3% MEM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
296
TOK/S · 3% MEM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
296
TOK/S · 3% MEM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
274
TOK/S · 3% MEM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
274
TOK/S · 3% MEM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
274
TOK/S · 3% MEM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
263
TOK/S · 3% MEM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
250
TOK/S · 3% MEM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
250
TOK/S · 3% MEM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
237
TOK/S · 12% MEM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your Apple M2 Max (64GB).

WHAT THIS CARD IS WORTH

M2 Max (64GB) holds 345 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is DeepSeek R1 Distill Llama 70B at IQ4_XS.

TOKENS/SEC PER $100
2.0
8B at Q4_K_M, so cards compare like for like
USABLE MEMORY PER $100
2.09 GB
what memory costs on this card
THE BIGGEST IT TAKES
DeepSeek R1 Distill Llama 70B70.6B · IQ4_XS43.1 GB5 tok/sEST
Llama 3.3 70B70.6B · IQ4_XS43.1 GB5 tok/sEST
Llama 3.1 70B70.6B · IQ4_XS43.1 GB5 tok/sEST
Llama 3 70B70.6B · IQ4_XS43.1 GB5 tok/sEST
Llama-3.1-Nemotron-70B70.6B · IQ4_XS43.1 GB5 tok/sEST
Cogito 70B70B · IQ4_XS42.8 GB5 tok/sEST
Llama 2 70B70B · IQ4_XS42.8 GB5 tok/sEST
CodeLlama 70B70B · IQ4_XS42.8 GB5 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
H100 SXM5 64 GB64 GB$25,0000.2 tok/s per $100
Radeon Instinct MI20064 GB$10,0001.8 tok/s per $100
Radeon Instinct MI21064 GB$8,0002.2 tok/s per $100
M1 Ultra (64GB)48 GB$2,4992.9 tok/s per $100
M2 Max (64GB)48 GB$2,2992.0 tok/s per $100

Neighbours in memory rather than in price: memory decides whether a card can do the job at all, so two cards of the same size at different prices is the comparison you are making. Ordered by memory, then bandwidth — not by the value column, which is worked out from bandwidth and price alone and therefore rewards a cheap card whatever its software stack does to that bandwidth in practice. Read it as one input, not as a ranking.

▸ DEVICE UNDER TEST

Apple M2 Max (64GB) — 64 GB unified, 48 GB usable.

APPLE M2 MAX (64GB) SPEC
BRAND
Apple
UNIFIED MEMORY
64 GB
USABLE BY A MODEL
48 GB
BANDWIDTH
400 GB/s
FP16 COMPUTE
13.6 TFLOPS
FP32 COMPUTE
13.6 TFLOPS
TDP
60 W
ARCHITECTURE
M2 Max
MSRP
$2299
▸ AI CAPABILITY
345/ 449 models @ Q4

With 48 GB of its 64 GB reaching a model and 400 GB/s bandwidth, this machine handles models up to 65.2B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~46 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR APPLE M2 MAX (64GB)
345 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
LLaMA 1 65B65.2B40.3 GB542.6
Jamba 2 Mini52B32.3 GB309.2
Jamba 1.5 Mini 52B51.6B32.0 GB3024.2
Kimi-Linear-48B-A3B48B29.8 GB11926.6
Nemotron-H 47B47B29.2 GB884.6
Mixtral-8x7B46.7B29.0 GB2718.8
Nous-Hermes-2-Mixtral-8x7B-DPO46.7B29.0 GB2727.4
Dolphin 2.6 Mixtral 8x7B46.7B29.0 GB2723.8
Phi-3.5 MoE 42B41.9B26.1 GB5456.7
Falcon 40B40B24.9 GB920.9
InternVL3 38B38B23.7 GB978.9
Seed-OSS 36B Instruct36B22.5 GB1054.4
c4ai-command-r-v01 35B35B21.9 GB1027.5
Qwen 3.5 35B A3B35B21.9 GB11953.3
Qwen 3.6 35B A3B35B21.9 GB11953.9
Nous Capybara 34B34.4B21.5 GB1042.0
Yi-1.5 34B34.4B21.5 GB1045.3
Falcon-H1 34B34B21.3 GB1066.1
CodeLlama 34B34B21.3 GB1025.4
Nous Hermes 2 34B34B21.3 GB1047.0