kingjones777/Mellum2-12B-A2.5B-Thinking-ROCmFP4-GGUF overview
⚠️ STOCK llama.cpp WILL NOT LOAD THIS MODEL The Mellum architecture is not merged upstream PR 23966 https://github.com/ggml org/llama.cpp/pull/23966 — the patc…
Runs locally from ~6.49 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | kingjones777/Mellum2-12B-A2.5B-Thinking-ROCmFP4-GGUF |
|---|---|
| Author | kingjones777 |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | JetBrains/Mellum2-12B-A2.5B-Thinking |
| Last modified | 2026-08-16T22:43:35.000Z |
Model README
---
license: apache-2.0
base_model: JetBrains/Mellum2-12B-A2.5B-Thinking
base_model_relation: quantized
tags: [gguf, llama.cpp, rocm, gfx1151, strix-halo, amd, ryzen-ai-max-395, ai-max-395, rocmfpx, mellum, moe, code, code-completion]
language: [en]
pipeline_tag: text-generation
---
> ### ⚠️ STOCK llama.cpp WILL NOT LOAD THIS MODEL
> The Mellum architecture is not merged upstream (PR #23966) — the patch is in patches/ in this repo.
>
> 🚀 104.99 tok/s — +6.9% faster than Q4_K_M, ranges disjoint.
Mellum2-12B-A2.5B-Thinking — ROCmFP4 (tier 102 COHERENT) GGUF
A 4-bit ROCmFP4 quantization for AMD gfx1151 (Ryzen AI MAX+ 395 / Strix Halo), quantized
from BF16 GGUF (22.6 GiB) — a lossless source, not a requantization of a lower-bit build.
| | |
|---|---|
| File | Mellum2-12B-A2.5B-Thinking-Q4_0_ROCMFP4_COHERENT.gguf |
| Size | 6.4907 GiB |
| BPW | 4.59 |
| ftype | Q4_0_ROCMFP4_COHERENT (102) |
⛔ Requires a llama.cpp with the ROCmFP4 quant types
Q4_0_ROCMFP4_COHERENT (ftype 102) exists only in
charlie12345/ROCmFPX, not upstream llama.cpp.
Ignore the auto-generated "Use this model" commands above.
---
All quant variants
All measured on one box, one binary (Ryzen AI MAX+ 395, gfx1151, ROCm 7.2.4), median of 3,
warm-up discarded — so these rows are directly comparable.
| variant | ftype | size | bpw | decode (median) | range |
|---|---|---|---|---|---|
| 4-bit COHERENT | 102 | 6.49 GiB | 4.59 | 104.99 | 104.96 – 105.73 |
| 8-bit AGENT | 115 | 11.88 GiB | 8.39 | 74.41 | 74.36 – 74.42 |
| 8-bit plain | 111 | 11.70 GiB | 8.27 | 75.72 | 75.72 – 75.73 |
Repos: 4-bit ·
⚠️ AGENT is SLIGHTLY SLOWER here — 74.41 vs 75.72. The opposite of the Instruct variant, which tells you the difference is model-specific and small. Neither 8-bit build approaches the 4-bit build's 104.99 tok/s.
> On AGENT generally: it keeps more tensors at true Q8_0 instead of the packed 8-bit type.
> That raises MTP draft acceptance on models which have an MTP head (measured +6.2% on
> Qwen3.8-27B). Mellum2 has no MTP head, so there is nothing for the extra precision to feed
> and the two 8-bit builds differ only marginally — in either direction.
Measured
Ryzen AI MAX+ 395 (gfx1151, 128 GB unified, ROCm 7.2.4). **Median of 3+, warm-up discarded,
otherwise-idle box.** Correctness at the model's official sampling.
| build | size | decode (median) | range |
|---|---|---|---|
| this build | 6.4907 GiB | 104.99 | [104.96 – 105.73] |
| Q4_K_M | — | 98.17 | [98.16 – 98.87] |
+6.9%, ranges disjoint — a real difference, not noise.
Correctness: 17×23 ⇒ ✅ 391 · capital of Japan ⇒ ✅ Tokyo · days in 2024 ⇒ ✅ 366
Per-tensor types (audited in the finished file)
output.weight Q6_K · token_embd Q6_K · router ffn_gate_inp F32 · norms F32 · 339 tensors
tie_word_embeddings is false, so both --output-tensor-type and --token-embedding-type apply.
---
What was NOT measured
- No perplexity run, and no quality A/B against the baseline or the source. The checks
above are memorized-fact prompts — necessary but not sufficient; a damaged model can pass them.
- No long-context testing.
- No tool-calling evaluation.
Base model licence inherited; credit for the model goes to its authors.
Run kingjones777/Mellum2-12B-A2.5B-Thinking-ROCmFP4-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models