---

license: apache-2.0

base_model: Qwen/Qwen3.5-122B-A10B

base_model_relation: quantized

library_name: gguf

pipeline_tag: text-generation

tags:

- gguf

- qwen3.5

- qwen3.5-moe

- rocmfp4

- imatrix

- amd

- vulkan

- rocm

- mtp

- speculative-decoding

- experimental

---

<div align="center">

Qwen3.5 122B-A10B · ROCmFP4 iMatrix

The official Qwen checkpoint in a compact, importance-calibrated ROCmFP4 GGUF

122B total · 10B active · 60.70 GiB · 28.50 tok/s MTP-off · BF16 KLD 0.041366 · Decode 28.505

Decode speed + 36.89% faster

Size - 13.47gb smaller

</div>

> [!IMPORTANT]

> This GGUF uses custom ROCmFP4 tensor types. It requires

> ROCmFPX or a runtime with equivalent

> support. Stock llama.cpp, Ollama, LM Studio, and similar stock runtimes

> cannot load it.

I also suggest usign the template from https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates Froggeric is tha dude.

This release was tested only on AMD Strix Halo / gfx1151. Other AMD targets

may require a different ROCmFPX build and are untested; CPU-only, NVIDIA, and

non-ROCmFPX runtimes are not supported by this card.

Downloads

| Artifact | Direct download |

|---|---|

| Main iMatrix model — 60.70 GiB | Download Qwen3.5-122B-A10B-ROCmFP4-iMatrix.gguf |

| Optional MTP companion — 2.14 GiB | Download Qwen3.5-122B-A10B-ROCmFP4-MTP.gguf |

| Calibration matrix — 342.28 MiB | Download Qwen3.5-122B-A10B-Bartowski.imatrix |

Browse every repository file →

What it is

This is an iMatrix-calibrated quantization of the official

Qwen/Qwen3.5-122B-A10B

checkpoint. It was built with ROCmFPX's compact

Q4_0_ROCMFP4_STRIX_LEAN recipe; the hardware-oriented preset name is left out

of the public filename.

| | Result |

|---|---:|

| BF16 mean KLD | 0.041366 ± 0.002531 |

| Greedy decode | 28.505 tok/s |

| Sampled decode | 28.485 tok/s |

| 4,277-token prefill | 356.900 tok/s |

Files

| File | Purpose | Size | SHA-256 |

|---|---|---:|---|

| Qwen3.5-122B-A10B-ROCmFP4-iMatrix.gguf | Main text model | 65,184,265,120 bytes | 9f44eb8a8693f46af6e1b06f6219229eb074c1ec5527798e8a18d68034b381c8 |

| Qwen3.5-122B-A10B-ROCmFP4-MTP.gguf | Optional external MTP companion | 2,294,290,272 bytes | f59efaa7c184042a940df322d81921254b8e178d6eefc0fd5cdd7c5b0a9acbe3 |

| Qwen3.5-122B-A10B-Bartowski.imatrix | Calibration matrix | 358,906,272 bytes | e8bfa39dd663e70655035ad53bf715069b7f55175a8877a36bbbe18a0131fed6 |

| chat_template.jinja | Pinned Qwen3.5 chat template | 7,756 bytes | a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715 |

The main model is complete and runs independently. The 23-tensor, one-layer

MTP file is an optional external companion; no MTP layer is embedded in the

main GGUF. Runtimes call this role a draft model, but Draft is omitted from

the public filename because it does not mean unfinished.

Quality: stock and Heretic KLD

This is the card's only comparison between the stock and Heretic builds. Each

ROCmFP4 iMatrix model was replayed against saved distributions from its own

exact BF16 parent, using the same runtime, WikiText-2 token sequence, ROCm0

backend, two 512-token chunks, and 510 evaluated next-token distributions.

| Build | Mean KLD from its BF16 parent |

|---|---:|

| Stock iMatrix | 0.041366 ± 0.002531 |

| Heretic iMatrix | 0.041395 ± 0.002697 |

Lower KLD means the quantized model's next-token distribution stayed closer to

its own BF16 source. It does not rank the underlying stock and Heretic

models, and it is not an intelligence or benchmark score.

The two-chunk scope is deliberately bounded: this is the demonstrated-safe

BF16 workload on the tested 128 GB system. Treat it as a controlled calibration

comparison, not a completed large-corpus acceptance gate. The Heretic card's

headline uses a separate 11-chunk replay; its value is therefore not expected

to match the two-chunk, method-matched figure reported here.

Performance

Measured on a 128 GB AMD Strix Halo system with Vulkan/RADV, 131,072 context,

parallel 1, batch/ubatch 2048/1024, Q8_0 KV cache, flash attention, and MTP off.

Values are medians from repeated runs of this stock artifact.

| Workload | Prompt tokens | Repeats | Decode | Prompt processing |

|---|---:|---:|---:|---:|

| Greedy, 256 generated tokens | 52 | 5 | 28.505 tok/s | 71.934 tok/s |

| Sampled, 256 generated tokens | 52 | 3 | 28.485 tok/s | 70.957 tok/s |

| 4,277-token prefill + 128 generated | 4,277 | 3 | 28.107 tok/s | 356.900 tok/s |

These are single-system measurements, not general performance guarantees. The

MTP companion is included for compatible runtimes, but this card does not claim

an MTP speed result for the iMatrix artifact.

Quantization and matrix provenance

The model was quantized once from the validated BF16 GGUF using the

Q4_0_ROCMFP4_STRIX_LEAN preset and the importance matrix published with

bartowski/Qwen_Qwen3.5-122B-A10B-GGUF

at revision f89fb67573c0155d8e5b6556204d86c75cdce0d8.

| Tensor type | Count |

|---|---:|

| Q4_0_ROCMFP4_FAST | 457 |

| Q4_0_ROCMFP4 | 60 |

| F32 | 361 |

| Q5_K | 1 |

In this preset, attention K/V tensors retain dual-scale ROCmFP4 protection,

most transformer weights use the compact FAST layout, and token

embeddings use Q5_K while the separate output head uses the FAST layout. The

artifact contains 879 tensors across 48 blocks and no embedded MTP layer.

The matrix contains 612 entries from 802 × 512-token chunks. Structural

inspection found finite paired tensors and 37,323 of 37,332 expert count slots

covered; nine slots had zero observations. A quantizer dry run accepted all 612

importance entries. The matrix publisher identified the official upstrQwen3-235B-A22Beam

model but did not pin an immutable upstream weight revision, so that provenance

limitation is recorded here rather than silently inferred.

Run

Use the ROCmFPX-built llama-server, not a stock llama.cpp binary:

llama-server \
  --model Qwen3.5-122B-A10B-ROCmFP4-iMatrix.gguf \
  --host 127.0.0.1 --port 8080 \
  -dev Vulkan0 --n-gpu-layers 999 \
  --ctx-size 131072 --parallel 1 \
  --flash-attn on --batch-size 2048 --ubatch-size 1024 \
  --cache-type-k q8_0 --cache-type-v q8_0 \
  --jinja --reasoning-format deepseek

Adjust context and cache settings for your memory budget. The tested runtime

was charlie12345/ROCmFPX commit

a6a93765f7ce9779c13f9881164a65f7a9f31198, built in Release mode for

gfx1151 with Vulkan and HIP enabled. Correct inference also requires the

duplicate Qwen3.5 MoE down-scale fix from

llama.cpp PR #24331, commit

02810c7: without it, the expert down scale

is applied twice. The pinned ROCmFPX commit did not yet contain the fix, so the

tested runtime applied that exact nine-line correction locally; use a newer

ROCmFPX revision or equivalent runtime that includes it. Results with other

revisions have not yet been established.

The GGUF embeds the same chat template shipped separately in this repository,

so the command uses --jinja without an external template path.

--reasoning-format deepseek is the tested llama.cpp parser for this template's

reasoning output, not a claim that the model is a DeepSeek derivative. The model

file alone occupies 60.70 GiB; leave additional memory for the runtime and KV

cache, especially at the tested 131,072-token context.

To enable the optional companion, append:

  --spec-type draft-mtp \
  --spec-draft-model Qwen3.5-122B-A10B-ROCmFP4-MTP.gguf \
  --spec-draft-device Vulkan0 --spec-draft-ngl 999 \
  --spec-draft-type-k f16 --spec-draft-type-v f16 \
  --spec-draft-n-max 2 --spec-draft-p-min 0.6 \
  --spec-draft-p-split 0.10 --spec-draft-backend-sampling

Tested system

| | |

|---|---|

| Platform | AMD Strix Halo, 128 GB unified memory |

| GPU target | Radeon 8060S / gfx1151 |

| Backend | Vulkan / RADV for serving; ROCm for bounded BF16 KLD collection |

| Kernel | Linux 6.17.0-1028-oem |

| Mesa | 25.2.8 |

No vision projector is included; treat this release as text-only.

Lineage and credits

• Official model and MTP tensors: Qwen/Qwen3.5-122B-A10B, revision dc4d348443bc740c68e2d77492492c11606384d5, Apache 2.0.
• Importance matrix: bartowski/Qwen_Qwen3.5-122B-A10B-GGUF, revision f89fb67573c0155d8e5b6556204d86c75cdce0d8.
• ROCmFP4 implementation, quantizer, and compatible runtime: charlie12345/ROCmFPX.
• Strix Halo deployment stack: hec-ovi/llama-vulkan-strix.
• Conversion, validation, benchmarking, and packaging: vmlinux.

Please preserve this lineage, the Apache 2.0 license, and a description of your

changes when redistributing derivatives.

License

The distributed model derivative is provided under the upstream Apache License

2.0, whose text is included as LICENSE. Runtime and tooling repositories

retain their own licenses. No runtime source code is bundled in this model

repository.