The LLMCheck index estimates Raon-1 mini preview at ~99 tok/s on an M5 Max at Q4_K_M, a figure from its published bandwidth model, not a measured run. It needs about 18 GB of unified memory. It is KRAFTON's 28.8B mixture-of-experts model (4.3B active), released under the Apache 2.0 licence.
Needs KRAFTON's own llama.cpp branch (upstream support pending) or MLX with trust_remote_code; there is no Ollama or LM Studio support and no published Mac measurement.
This is an LLMCheck index estimate from its published two-term bandwidth model, not a measured run; the index labels it so everywhere it appears. Own this Mac? Submit a real run →
| Metric | Value |
|---|---|
| Tokens per second | estimated~99 tok/s |
| Provenance | estimate · how estimates are made |
| Quantization | Q4_K_M |
| Engine | llama.cpp |
| Figure dated | 2026-10 |
| Minimum RAM | 18 GB |
| Parameters | 28.8B MoE (4.3B active) |
| Chip bandwidth | 614 GB/s |
Each row as the index holds it, with its source. “Mac RAM” is the memory of the Mac a run used, not the model’s requirement (18 GB). The headline figure follows the reference rule: the lower-median measured plain-decode run at 5 bits or fewer (a run whose quant was not stated counts only when no stated-quant run qualifies), else the estimate; a run marked “not used to anchor estimates” is listed here but never becomes the headline.
| Speed | Quant | Engine | Mac RAM | Context | Source | Note |
|---|---|---|---|---|---|---|
| estimated99 tok/s | Q4_K_M | llama.cpp | 64 GB | — | LLMCheck estimator | — |
Ollama — the index has not verified an Ollama tag for Raon-1 mini preview, so it doesn’t print one (a guessed tag fails with “pull model manifest: file does not exist”). Search the Ollama library →
MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:
Downloads: Hugging Face repo → · model card →
Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.
KRAFTON's Apache 2.0 preview MoE trained from scratch (21 Oct 2026): 28.8B total, 4.3B active, 262K context, text only, Korean-first across seven languages, thinking mode by default. KRAFTON's card (preview, vendor-run, GPT judge) reports GPQA Diamond 84.3, LiveCodeBench v6 81.6 and SWE-bench Verified 70.8 on mini-SWE-agent, with MMLU-Pro 76.5 below its Qwen 3.6 and Gemma 4 comparators. Official GGUFs start at 16.1 GB (IQ4_XS), so it targets 24 GB Macs, but only through KRAFTON's llama.cpp branch or remote-code MLX; specs may change before the final release.
Apache 2.0 licence · 28.8B MoE · 262K context · LLMCheck capability 34/50 · see its leaderboard rank →
Raon-1 mini preview needs about 18 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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See how Raon-1 mini preview stacks up against other models on your specific Mac hardware.
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