What's My AIModel fit page built from catalog review, runtime coverage, and benchmark-oriented hardware guidance.
Model fit34B

can i run it

Can I run Granite 4.0 H-Small locally?

Granite 4.0 H-Small is a credible American midrange choice for RAG-heavy work, but it is more specialized than the general-purpose winners above it. This page answers the practical parts of the question: what class of computer is enough, which runtime gives the lowest-friction first run, and which nearby models may fit better.

minimum tier34B
minimum memory19.5 GB
comfortable memory24.0 GB
runtime coverageOllama, LM Studio, and llama.cpp paths tracked

why this model

Granite 4.0 H-Small is worth checking when you want RAG and enterprise-style agents.

This shortlist stays inside verified American model releases. Granite 4.0 H-Small gets the nod because it is particularly good when the local workload is RAG, extraction, or enterprise agent flow; for a general first local model, gpt-oss-20b is easier to justify on the same class of hardware. Verified 2026-03-12 · review by 2026-04-11.

Benchmark this deviceCompare known machines

hardware fit

What kind of computer should handle Granite 4.0 H-Small?

These reference hardware classes show the minimum benchmark band where this model starts to make sense.

reference band

Creator laptop

34B class • 24 GB reference memory

Balanced CPU/GPU throughput, suitable for heavier local inference workflows.

Open hardware page

reference band

Workstation desktop

70B class • 48 GB reference memory

High-end desktop class hardware with room for large quantized models.

Open hardware page

reference band

Ultra workstation

120B class • 128 GB reference memory

Extreme desktop class hardware with enough headroom for gpt-oss-120b-class local inference.

runtime paths

Where should you start?

LM StudioCommunity path

Community GGUF import path for LM Studio.

Download path. unsloth/granite-4.0-h-small-GGUF

lms get https://huggingface.co/unsloth/granite-4.0-h-small-GGUF
Read LM Studio guideOpen runtime evidence
llama.cppCommunity path

Community GGUF import path for llama.cpp.

Download path. unsloth/granite-4.0-h-small-GGUF

llama-server -hf unsloth/granite-4.0-h-small-GGUF -c 131072 --port 8080
Read llama.cpp guideOpen runtime evidence

related pages

Nearby models and runtimes

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

evidence sources

Evidence sources

  • Model provenance review: Verified 2026-03-12 · review by 2026-04-11 for Granite 4.0 H-Small and the surrounding reviewed catalog. Open page
  • Benchmark methodology: How the benchmark confirms whether Granite 4.0 H-Small fits a real machine before download time. Open page
  • Ollama tracked path: Official Ollama package for Granite 4.0 H-Small. Open source
  • LM Studio tracked path: Community GGUF import path for LM Studio. Open source
  • llama.cpp tracked path: Community GGUF import path for llama.cpp. Open source