Canonical Rankings

Best Macs for this model

GLM-4.7-Flash ranked across the Mac lineup at the best practical quantization, using the best available runtime evidence.

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28 ranked MacsUse the strongest current runtime evidence for each row.Static paths cover only canonical model pages; sort and quantization stay as query state.

Rank	Mac	Score	Quant	Tok/s	Runtime	Fits	Evidence	Price	Why it ranks here
1	Mac Studio M3 Ultra 256GB	433	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$7,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 220.2 GB headroom remains at this quantization.
2	Mac Pro M2 Ultra 192GB	369	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$6,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 156.2 GB headroom remains at this quantization.
3	Mac Studio M4 Max 128GB	305	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$4,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 92.2 GB headroom remains at this quantization.
4	MacBook Pro M4 Max 128GB 16-inch	305	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$5,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 92.2 GB headroom remains at this quantization.
5	Mac Studio M3 Ultra 96GB	273	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$3,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 60.2 GB headroom remains at this quantization.
6	Mac Studio M4 Max 64GB	241	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$2,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 28.2 GB headroom remains at this quantization.
7	MacBook Pro M4 Max 64GB 16-inch	241	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$4,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 28.2 GB headroom remains at this quantization.
8	Mac Mini M4 Pro 48GB	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$1,599	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
9	MacBook Pro M4 Pro 48GB 14-inch	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$2,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
10	Mac Studio M4 Max 48GB	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$2,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
11	MacBook Pro M4 Pro 48GB 16-inch	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$2,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
12	MacBook Pro M4 Max 48GB 14-inch	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$3,499	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
13	MacBook Pro M4 Max 48GB 16-inch	225	8bit	36.8 tok/s	llama.cpp	Fits	Estimated	$3,999	8bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 12.2 GB headroom remains at this quantization.
14	Mac Studio M4 Max 36GB	214	6bit	36.8 tok/s	llama.cpp	Fits	Estimated	$1,999	6bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.2 GB headroom remains at this quantization.
15	MacBook Pro M4 Max 36GB 14-inch	214	6bit	36.8 tok/s	llama.cpp	Fits	Estimated	$2,999	6bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.2 GB headroom remains at this quantization.
16	MacBook Pro M4 Max 36GB 16-inch	214	6bit	36.8 tok/s	llama.cpp	Fits	Estimated	$3,499	6bit is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.2 GB headroom remains at this quantization.
17	Mac Mini M4 32GB	208	Q5	36.8 tok/s	llama.cpp	Fits	Estimated	$799	Q5 is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 6.7 GB headroom remains at this quantization.
18	MacBook Air M4 32GB 13-inch	208	Q5	36.8 tok/s	llama.cpp	Fits	Estimated	$1,499	Q5 is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 6.7 GB headroom remains at this quantization.
19	MacBook Air M4 32GB 15-inch	208	Q5	36.8 tok/s	llama.cpp	Fits	Estimated	$1,699	Q5 is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 6.7 GB headroom remains at this quantization.
20	Mac Mini M4 24GB	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$599	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
21	MacBook Air M4 24GB 13-inch	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$1,299	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
22	Mac Mini M4 Pro 24GB	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$1,399	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
23	MacBook Air M4 24GB 15-inch	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$1,499	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
24	MacBook Pro M4 Pro 24GB 14-inch	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$1,999	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
25	MacBook Pro M4 Pro 24GB 16-inch	178	Q2_K	36.8 tok/s	llama.cpp	Fits	Estimated	$2,499	Q2_K is the current best practical quantization. 36.8 tok/s is estimated from nearby benchmark coverage. 7.0 GB headroom remains at this quantization.
26	Mac Mini M4 16GB	0	F32	—	llama.cpp	No	Estimated	$499	GLM-4.7-Flash does not fit on Mac Mini M4 16GB at the current practical quantization.
27	MacBook Air M4 16GB 13-inch	0	F32	—	llama.cpp	No	Estimated	$1,099	GLM-4.7-Flash does not fit on MacBook Air M4 16GB 13-inch at the current practical quantization.
28	MacBook Air M4 16GB 15-inch	0	F32	—	llama.cpp	No	Estimated	$1,299	GLM-4.7-Flash does not fit on MacBook Air M4 16GB 15-inch at the current practical quantization.

GLM-4.7-Flash — ranking first, raw rows below

Start with the ranked Mac table above. Use the rest of this page to inspect raw Apple Silicon coverage and model metadata.

Quantizations observed: Q4_K_XL

1Benchmark rows

1Chip tiers covered

36.8Fastest avg tok/s (M1 Max (64 GB))

17 GBMinimum RAM observed

What this page answers best

Fastest published result is 36.8 tok/s on M1 Max (64 GB) at Q4_K_XL. Smallest published fit is 17.0 GB on M1 Max (64 GB). Longest published context on this page is 4k. Published runtimes include llama.cpp. Start with Rankings for the decision, then use the raw rows below to audit the evidence.

Evidence state: 1 linked reference row and no Silicon Score Lab rows yet.

Published runtimes here: llama.cpp.

Need the best Mac for this model? Use Buy Need a setup-first answer? Use Run Checking whether it fits? Use Fit Browse Macs by exact hardware Need the full audit trail? Use Bench Comparing against rented GPUs? Use AI Datacenter Index

Catalog record

30BTotal params

3BActive params

202,752Context window

2026-01-19Release date

What this model is, and what Apple Silicon users are actually seeing

Official model cards tell you what the model is for and which software stacks it targets. Field reality below shows how much Apple Silicon evidence we have so far.

Official brief

For multi-turn agentic tasks (τ²-Bench and Terminal Bench 2), please turn on Preserved Thinking mode.

Official source · Raw model card

agentscodingreasoning

Runtime support mentioned

vLLMSGLangTransformers

Official takeaways

For local deployment, GLM-4.7-Flash supports inference frameworks including vLLM and SGLang.
For multi-turn agentic tasks (τ²-Bench and Terminal Bench 2), please turn on Preserved Thinking mode.
Install the supported versions of SGLang and Transformers (using uv is recommended): For Blackwell GPUs, include --attention-backend triton --speculative-draft-attention-backend triton in your SGLang launch command.
vLLM and SGLang only support GLM-4.7-Flash on their main branches.

Deployment notes

For local deployment, GLM-4.7-Flash supports inference frameworks including vLLM and SGLang. Comprehensive deployment instructions are available in the official Github repository.
vLLM and SGLang only support GLM-4.7-Flash on their main branches.

Official model cards describe intent, capabilities, and supported stacks. They do not prove Apple Silicon speed by themselves.

Field reality on Apple Silicon

GLM-4.7-Flash: 1 Apple Silicon field report; best reported generation ~36.8 tok/s; best reported prompt processing ~99.4 tok/s; seen on MacBook Pro M1 MAX 64GB; via llama.cpp.

1Benchmark rows

1Field reports

2Practitioner signals

Sparse BenchmarksEvidence status

What practitioners keep saying

The thread treats GLM-4.7-Flash as one of the current MoE models worth directly comparing on Apple Silicon.
This is a signal that GLM-4.7-Flash should be benchmarked and caveated, not ignored.
The thread ties looping and poor behavior to an implementation bug rather than pure model quality.

Runtime mentions in the field

ClineContinuellama.cpp

Hardware mentioned in reports

16GB32GB64GB128GBM1 MaxMacBookMacBook Pro

What would improve confidence

Capture Practitioner Runtime Notes
Expand Cross Chip Benchmark Coverage
Queue Lab Verification If Hardware Available
Reproduce Field Performance Signal

Current published coverage

Published chip coverage includes M1 Max (64 GB). Fastest published row is 36.8 tok/s on M1 Max (64 GB) at Q4_K_XL. Lowest published RAM requirement is 17.0 GB on M1 Max (64 GB). Catalog context window is 4k.

M1 Max (64 GB)

Raw benchmark rows for GLM-4.7-Flash

Rows stay below the ranking because this page is answer-first. Use them to inspect exact chips, quantizations, runtimes, and sources.

Chip	Quant	RAM req.	Context	Avg tok/s	Prompt tok/s	Runtime	Source
M1 Max (64 GB)	Q4_K_XL	17.0 GB	4k	36.8 tok/s	99.4 tok/s	llama.cpp	ref

Chips with published results for GLM-4.7-Flash

M1 Max (64 GB)

Data

benchmarks.json — full dataset · models.json — model summaries · benchmarks.csv — CSV export

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