What's My AILanding page built from search-intent evidence, reference assumptions, and a benchmark-first path.
GPU cohort120B

GPU cohort

What local AI can I run on an Apple M4 Max GPU class machine?

People using the Apple chip tier itself as the buying shortcut for local AI headroom. This page gives the short local-AI answer for the search query, then routes uncertain cases into the benchmark before the recommendation turns into guesswork.

gpu cohortApple integrated GPU + 64 GB class memory
starter modelLlama 4 Scout
tier guide120B
publish waveWeek 1

benchmark first

Verify this class before you trust the reference answer.

It is a high ceiling cohort, but the benchmark still separates a good Apple spec line from a comfortable local AI experience. The benchmark is what turns this cohort answer into a machine-specific decision before you spend time downloading models that do not fit.

Benchmark this deviceCompare known machines

starter models

Best first models for this cohort

Llama 4 Scout

120B class • 67.0 GB minimum

Llama 4 Scout is the first serious American multimodal long-context step once a machine can already absorb 100B-class local packaging.

Open model page

Llama 3.3 70B

70B class • 40.0 GB minimum

Llama 3.3 70B remains the most established American large-model jump for a serious local machine that can already hold a 70B-class package.

Open model page

gpt-oss-20b

34B class • 15.5 GB minimum

gpt-oss-20b is the clearest midrange American local-model pick when you want a serious reasoning assistant without jumping straight into a 32B-class package.

Open model page

why this page ranks

Query evidence and benchmark path

  • Organic traffic signal: High demand for the query cluster around “apple m4 max gpu local ai”.
  • Search intent review: GPU cohort searches are high intent when the page explains model size, memory headroom, and when to benchmark anyway.
  • Benchmark completion potential: High. These searches are close enough to a hardware decision that a benchmark CTA consistently belongs above the fold.

runtime paths

Pick the runtime after you confirm the hardware band

The benchmark decides the size band first. The runtime pages then tell you which download path is the cleanest first move inside Ollama, LM Studio, or llama.cpp.

P0Static

Runtime page

Best local models for Ollama

Search intent: ollama best model

Best for the quickest path from benchmark result to a real local run.

Runtime guide + catalog coverage

Open page
P1Static

Runtime page

Best local models for llama.cpp

Search intent: llama.cpp best model

Best for people who care about low-level control, serving flags, and GGUF tuning.

Runtime guide + catalog coverage

Open page

nearby pages

Adjacent queries to open next