What's My AILanding page built from search-intent evidence, reference assumptions, and a benchmark-first path.
GPU cohort70B

GPU cohort

What local AI can I run on an RTX 4070 Super desktop GPU?

Desktop builders who want a practical large-model answer before choosing the rest of the machine. 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 cohort12 GB desktop VRAM class
starter modelLlama 3.3 70B
tier guide70B
publish waveWeek 1

benchmark first

Verify this class before you trust the reference answer.

It is an attractive local-AI card, but the benchmark still turns the parts-list assumption into a browser-tested answer. 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 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

OLMo 3.1 Instruct 32B

34B class • 19.5 GB minimum

OLMo 3.1 32B is the strongest Apache-licensed American 32B-class option, but it asks for more memory than gpt-oss-20b to reach a clean first run.

Open model page

why this page ranks

Query evidence and benchmark path

  • Organic traffic signal: High demand for the query cluster around “rtx 4070 super 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