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alt.freeweights.qwen / Qwen3.5-35B-A3B-GGUF
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.qwenSubject:

Qwen3.5-35B-A3B-GGUF

Date: 2026-11-14Commit: bc014a1Signed: 2DC28CC7B26A283B ✓

Image text to text model. Gguf weights, 577 GB in all. Published by unsloth under Apache-2.0.

qwen577GBQwen3.5-35B-A3B-GGUFggufpermissive
FactsParamsnot statedSize577 GBFormatsggufTaskimage text to textLicenseApache-2.0From sourcepermissive
$ fw get unsloth/Qwen3.5-35B-A3B-GGUF
# manifest sha256 2206e4524a00… · 577 GB · 32 files
$ fw verify ./Qwen3.5-35B-A3B-GGUF unsloth/Qwen3.5-35B-A3B-GGUF
From sourceHosted (signed)unsloth/Qwen3.5-35B-A3B-GGUFLast check: 2026-11-14 21:32 UTC
Run at homeGet help

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Quantized of Qwen3.5-35B-A3B.

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Overview

Size
577 GB
Weights
10.7 GB (smallest of 24 GGUF variants)
Parameters
not stated
Formats
gguf
Task
image text to text
License
Apache-2.0 (permissive)
Files
32, each with a sha256
Publisher
unsloth
Added
2026-11-14
Section
alt.freeweights.qwen
Lineage

Original release from the publisher.

Base model: Qwen/Qwen3.5-35B-A3B

Where these bytes come from
Publisher at the pinned commit→You

Sources are tried in order. A file counts only when its size and sha256 match the manifest. Sources are checked when you ask for them, not on a timer.

Sources
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From sourcehuggingface.co2026-11-14 21:32 UTCpassed

Model card

From the publisher at commit bc014a1. Shown as plain text with links; images open at the publisher.

To run Qwen3.5 locally - Read our Guide!#

Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants.

https://github.com/unslothai/unsloth/ https://discord.gg/unsloth https://unsloth.ai/docs/models/qwen3.5

Disable thinking via --chat-template-kwargs '{"enable_thinking":false}'. Read our guide.

Mar 5 'Final' Update:#

  • All GGUFs now use our new imatrix data. See some improvements in chat, coding, long context, and tool-calling use-cases.
  • GGUFs now updated with an improved quantization algorithm.
  • Rest of variants like Q8_0, Q4_K_M, BF16 are now uploaded.
  • See our new benchmarks for 122B-A10B here.

Image: horiztonal plot

For Qwen3.5-35B-A3B, we primarily reduced the maximum KLD:

Image: image

Feb 27 Update: GGUFs Refreshed + Tool-calling fixes + Benchmarks#

  • Qwen3.5 is now updated with improved tool-calling & coding performance! See improvements via Claude Code, Codex.
  • We also benchmarked GGUFs & removed MXFP4 layers from 3 quants. Read analysis here.

Please follow the correct instructions / settings in our guide here.

Fine-tuning and RL Qwen3.5#

Qwen3.5-35B-A3B#

Image: image

Qwen Chat

Note. This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.

These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

Tip. For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Alibaba Cloud Model Studio.

In particular, Qwen3.5-Flash is the hosted version corresponding to Qwen3.5-35B-A3B with more production features, e.g., 1M context length by default and official built-in tools. For more information, please refer to the User Guide.

Over recent months, we have intensified our focus on developing foundation models that deliver exceptional utility and performance. Qwen3.5 represents a significant leap forward, integrating breakthroughs in multimodal learning, architectural efficiency, reinforcement learning scale, and global accessibility to empower developers and enterprises with unprecedented capability and efficiency.

Qwen3.5 Highlights#

Qwen3.5 features the following enhancement:

  • Unified Vision-Language Foundation: Early fusion training on multimodal tokens achieves cross-generational parity with Qwen3 and outperforms Qwen3-VL models across reasoning, coding, agents, and visual understanding benchmarks.
  • Efficient Hybrid Architecture: Gated Delta Networks combined with sparse Mixture-of-Experts deliver high-throughput inference with minimal latency and cost overhead.
  • Scalable RL Generalization: Reinforcement learning scaled across million-agent environments with progressively complex task distributions for robust real-world adaptability.
  • Global Linguistic Coverage: Expanded support to 201 languages and dialects, enabling inclusive, worldwide deployment with nuanced cultural and regional understanding.
  • Next-Generation Training Infrastructure: Near-100% multimodal training efficiency compared to text-only training and asynchronous RL frameworks supporting massive-scale agent scaffolds and environment orchestration.

Image: Benchmark Results

For more details, please refer to our blog post Qwen3.5.

Model Overview#

  • Type: Causal Language Model with Vision Encoder
  • Training Stage: Pre-training & Post-training
  • Language Model
    • Number of Parameters: 35B in total and 3B activated
    • Hidden Dimension: 2048
    • Token Embedding: 248320 (Padded)
    • Number of Layers: 40
    • Hidden Layout: 10 × (3 × (Gated DeltaNet → MoE) → 1 × (Gated Attention → MoE))
    • Gated DeltaNet:
      • Number of Linear Attention Heads: 32 for V and 16 for QK
      • Head Dimension: 128
    • Gated Attention:
      • Number of Attention Heads: 16 for Q and 2 for KV
      • Head Dimension: 256
      • Rotary Position Embedding Dimension: 64
    • Mixture Of Experts
      • Number of Experts: 256
      • Number of Activated Experts: 8 Routed + 1 Shared
      • Expert Intermediate Dimension: 512
    • LM Output: 248320 (Padded)
    • MTP: trained with multi-steps
  • Context Length: 262,144 natively and extensible up to 1,010,000 tokens.

Benchmark Results#

Language#

| | GPT-5-mini 2025-08-07 | GPT-OSS-120B | Qwen3-235B-A22B | Qwen3.5-122B-A10B | Qwen3.5-27B | Qwen3.5-35B-A3B

| Knowledge

| MMLU-Pro | 83.7 | 80.8 | 84.4 | 86.7 | 86.1 | 85.3

| MMLU-Redux | 93.7 | 91.0 | 93.8 | 94.0 | 93.2 | 93.3

| C-Eval | 82.2 | 76.2 | 92.1 | 91.9 | 90.5 | 90.2

| SuperGPQA | 58.6 | 54.6 | 64.9 | 67.1 | 65.6 | 63.4

| Instruction Following

| IFEval | 93.9 | 88.9 | 87.8 | 93.4 | 95.0 | 91.9

| IFBench | 75.4 | 69.0 | 51.7 | 76.1 | 76.5 | 70.2

| MultiChallenge | 59.0 | 45.3 | 50.2 | 61.5 | 60.8 | 60.0

| Long Context

| AA-LCR | 68.0 | 50.7 | 60.0 | 66.9 | 66.1 | 58.5

| LongBench v2 | 56.8 | 48.2 | 54.8 | 60.2 | 60.6 | 59.0

| STEM & Reasoning

| HLE w/ CoT | 19.4 | 14.9 | 18.2 | 25.3 | 24.3 | 22.4

| GPQA Diamond | 82.8 | 80.1 | 81.1 | 86.6 | 85.5 | 84.2

| HMMT Feb 25 | 89.2 | 90.0 | 85.1 | 91.4 | 92.0 | 89.0

| HMMT Nov 25 | 84.2 | 90.0 | 89.5 | 90.3 | 89.8 | 89.2

| Coding

| SWE-bench Verified | 72.0 | 62.0 | -- | 72.0 | 72.4 | 69.2

| Terminal Bench 2 | 31.9 | 18.7 | -- | 49.4 | 41.6 | 40.5

| LiveCodeBench v6 | 80.5 | 82.7 | 75.1 | 78.9 | 80.7 | 74.6

| CodeForces | 2160 | 2157 | 2146 | 2100 | 1899 | 2028

| OJBench | 40.4 | 41.5 | 32.7 | 39.5 | 40.1 | 36.0

| FullStackBench en | 30.6 | 58.9 | 61.1 | 62.6 | 60.1 | 58.1

| FullStackBench zh | 35.2 | 60.4 | 63.1 | 58.7 | 57.4 | 55.0

| General Agent

| BFCL-V4 | 55.5 | -- | 54.8 | 72.2 | 68.5 | 67.3

| TAU2-Bench | 69.8 | -- | 58.5 | 79.5 | 79.0 | 81.2

| VITA-Bench | 13.9 | -- | 31.6 | 33.6 | 41.9 | 31.9

| DeepPlanning | 17.9 | -- | 17.1 | 24.1 | 22.6 | 22.8

| Search Agent

| HLE w/ tool | 35.8 | 19.0 | -- | 47.5 | 48.5 | 47.4

| Browsecomp | 48.1 | 41.1 | -- | 63.8 | 61.0 | 61.0

| Browsecomp-zh | 49.5 | 42.9 | -- | 69.9 | 62.1 | 69.5

| WideSearch | 47.2 | 40.4 | -- | 60.5 | 61.1 | 57.1

| Seal-0 | 34.2 | 45.1 | -- | 44.1 | 47.2 | 41.4

| Multilingualism

| MMMLU | 86.2 | 78.2 | 83.4 | 86.7 | 85.9 | 85.2

| MMLU-ProX | 78.5 | 74.5 | 77.9 | 82.2 | 82.2 | 81.0

| NOVA-63 | 51.9 | 51.1 | 55.4 | 58.6 | 58.1 | 57.1

| INCLUDE | 81.8 | 74.0 | 81.0 | 82.8 | 81.6 | 79.7

| Global PIQA | 88.5 | 84.1 | 85.7 | 88.4 | 87.5 | 86.6

| PolyMATH | 67.3 | 54.0 | 60.1 | 68.9 | 71.2 | 64.4

| WMT24++ | 80.7 | 74.4 | 75.8 | 78.3 | 77.6 | 76.3

| MAXIFE | 85.3 | 83.7 | 83.2 | 87.9 | 88.0 | 86.6

  • CodeForces: evaluated on our own query set.
  • TAU2-Bench: we follow the official setup except for the airline domain, where all models are evaluated by applying the fixes proposed in the Claude Opus 4.5 system card.
  • Search Agent: most search agents built on our model adopt a simple context-folding strategy(256k): once the cumulative Tool Response length reaches a preset threshold, earlier Tool Responses are pruned from the history to keep the context within limits.
  • WideSearch: we use a 256k context window without any context management.
  • MMLU-ProX: we report the averaged accuracy on 29 languages.
  • WMT24++: a harder subset of WMT24 after difficulty labeling and rebalancing; we report the averaged scores on 55 languages using XCOMET-XXL.
  • MAXIFE: we report the accuracy on English + multilingual original prompts (totally 23 settings).
  • Empty cells (--) indicate scores not yet available or not applicable.
Vision Language#

| | GPT-5-mini 2025-08-07 | Claude-Sonnet-4.5 | Qwen3-VL-235B-A22B | Qwen3.5-122B-A10B | Qwen3.5-27B | Qwen3.5-35B-A3B

| STEM and Puzzle

| MMMU | 79.0 | 79.6 | 80.6 | 83.9 | 82.3 | 81.4

| MMMU-Pro | 67.3 | 68.4 | 69.3 | 76.9 | 75.0 | 75.1

| MathVision | 71.9 | 71.1 | 74.6 | 86.2 | 86.0 | 83.9

| Mathvista(mini) | 79.1 | 79.8 | 85.8 | 87.4 | 87.8 | 86.2

| DynaMath | 81.4 | 78.8 | 82.8 | 85.9 | 87.7 | 85.0

| ZEROBench | 3 | 4 | 4 | 9 | 10 | 8

| ZEROBench_sub | 27.3 | 26.3 | 28.4 | 36.2 | 36.2 | 34.1

| VlmsAreBlind | 75.8 | 85.5 | 79.5 | 96.7 | 96.9 | 97.0

| BabyVision | 20.9 | 18.6 | 22.2 | 40.2 / 34.5 | 44.6 / 34.8 | 38.4 / 29.6

| General VQA

| RealWorldQA | 79.0 | 70.3 | 81.3 | 85.1 | 83.7 | 84.1

| MMStar | 74.1 | 73.8 | 78.7 | 82.9 | 81.0 | 81.9

| MMBenchEN-DEV-v1.1 | 86.8 | 88.3 | 89.7 | 92.8 | 92.6 | 91.5

| SimpleVQA | 56.8 | 57.6 | 61.3 | 61.7 | 56.0 | 58.3

| HallusionBench | 63.2 | 59.9 | 66.7 | 67.6 | 70.0 | 67.9

| Text Recognition and Document Understanding

| OmniDocBench1.5 | 77.0 | 85.8 | 84.5 | 89.8 | 88.9 | 89.3

| CharXiv(RQ) | 68.6 | 67.2 | 66.1 | 77.2 | 79.5 | 77.5

| MMLongBench-Doc | 50.3 | -- | 56.2 | 59.0 | 60.2 | 59.5

| CC-OCR | 70.8 | 68.1 | 81.5 | 81.8 | 81.0 | 80.7

| AI2D_TEST | 88.2 | 87.0 | 89.2 | 93.3 | 92.9 | 92.6

| OCRBench | 82.1 | 76.6 | 87.5 | 92.1 | 89.4 | 91.0

| Spatial Intelligence

| ERQA | 54.0 | 45.0 | 52.5 | 62.0 | 60.5 | 64.8

| CountBench | 91.0 | 90.0 | 93.7 | 97.0 | 97.8 | 97.8

| RefCOCO(avg) | -- | -- | 91.1 | 91.3 | 90.9 | 89.2

| ODInW13 | -- | -- | 43.2 | 44.5 | 41.1 | 42.6

| EmbSpatialBench | 80.7 | 71.8 | 84.3 | 83.9 | 84.5 | 83.1

| RefSpatialBench | 9.0 | 2.2 | 69.9 | 69.3 | 67.7 | 63.5

| LingoQA | 62.4 | 12.8 | 66.8 | 80.8 | 82.0 | 79.2

| Hypersim | -- | -- | 11.0 | 12.7

The publisher's README is longer; it is cut here. Read the rest at the source.

Files

32 files · 577 GBWeights 10.7 GB (smallest of 24 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 32 files with their sha256
FileSizesha256
.gitattributes4.20 KB83433ec64807a398fd90d35125507c7828bc218066adb7a0bb7fd06badb8a53e
BF16/Qwen3.5-35B-A3B-BF16-00001-of-00002.gguf49.8 GBa1c3f36db01985d678bd46e976b62398d3814fcc2b26aee7cc78c857466b8bee
BF16/Qwen3.5-35B-A3B-BF16-00002-of-00002.gguf19.5 GB13d69c9ee0fce7810ed9d383ed7fa5958d524c1136dfb4928453e8054f5d444e
Qwen3.5-35B-A3B-MXFP4_MOE.gguf21.6 GB0f135a59159030f4710477abc6f9922d2f13552c85bff736deaaef71023cd770
Qwen3.5-35B-A3B-Q3_K_M.gguf16.4 GB5607c8fcc8b04ada7d1a1152b9a5b6c1e67e6768232c16f6b03d9719d5ab1b2d
Qwen3.5-35B-A3B-Q3_K_S.gguf15.3 GB315cce210c0406ae05c4e482ceba154c9225fa0bb4c9e779465209dec08e625d
Qwen3.5-35B-A3B-Q4_K_M.gguf22.0 GB3b46d1066bc91cc2d613e3bc22ce691dd77e6f0d33c9060690d24ce6de494375
Qwen3.5-35B-A3B-Q4_K_S.gguf20.7 GBee93ceffed5ce4df8b09bcbaf59a286d531025a1ebde9cf204c74e800c47d57e
Qwen3.5-35B-A3B-Q5_K_M.gguf26.2 GB93198787ca7744a813f437317ff086b9abeb3f6fabbd5fa5702aa893fa315d89
Qwen3.5-35B-A3B-Q5_K_S.gguf24.8 GBac6ea71c0a694e6e90554f8cb0daacecb7873b93a08ad009d1d524c322a2d25c
Qwen3.5-35B-A3B-Q6_K.gguf28.9 GB56ddab06cc049b66fee8cff294c0b0e5e848f3381ed0da1a3a16a7bd80e8280a
Qwen3.5-35B-A3B-Q8_0.gguf36.9 GB3808866c016ab02b4adb26b873f7008a2cdd2c0704a39704050119ab0631db46
Qwen3.5-35B-A3B-UD-IQ2_M.gguf11.4 GB187b5bbb81d7ec1dc228cb04120302cc0d486cb3c988501af87e5f02e15ace0e
Qwen3.5-35B-A3B-UD-IQ2_XXS.gguf10.7 GB2a809de317cfd49ac9130b95619ee6ac039a855e467015b3e996eb61af84718b
Qwen3.5-35B-A3B-UD-IQ3_S.gguf13.6 GBca6e9542e9f9e34f28d59e1e335b3629825daf30a4c0b5c1ec9d2f898c061fb6
Qwen3.5-35B-A3B-UD-IQ3_XXS.gguf13.1 GB9f7f59280fcac9373f9122de0ed7a19e014fc14120a68b343ea46ac5f5dd96cd
Qwen3.5-35B-A3B-UD-IQ4_NL.gguf17.8 GB6aec31ed654fbf12f9950c98bab0a09faea433ffdc4b3acfeb55a1f050e3e444
Qwen3.5-35B-A3B-UD-IQ4_XS.gguf17.5 GB745def087c9ec34d12a94eb9b31eb52dba958b36def510b7e8f6f2e6bf1be123
Qwen3.5-35B-A3B-UD-Q2_K_XL.gguf12.2 GB855b8d11f4b52e7ea4b9eeea2fbe3555c4d96d5b7b74702b6144810db3e77270
Qwen3.5-35B-A3B-UD-Q3_K_XL.gguf16.6 GBfef37f41877128b0c82195c5cd173ca0e02394f48c7667dbf96172fa300fc945
Qwen3.5-35B-A3B-UD-Q4_K_L.gguf20.2 GBb65bba850b65e989ac8c37978970b2fe2ed3aa404fcb8408c9b3f2df13e6ab0b
Qwen3.5-35B-A3B-UD-Q4_K_XL.gguf22.2 GB1b0ac637dfa092bbba2793977db9485a40c4f8b42df5fe342f0076d61b66ae83
Qwen3.5-35B-A3B-UD-Q5_K_XL.gguf26.4 GBfa35af22dd694b8146bfb990c1227d834ee8ab83a4b91772105a14a9e09fde3d
Qwen3.5-35B-A3B-UD-Q6_K_S.gguf28.5 GB9812147c6c561c5229d72f14717618f9e1fc62f26a98e720569981891830b5d8
Qwen3.5-35B-A3B-UD-Q6_K_XL.gguf32.1 GBc5cd54592ac3a1fc20340841e57769ce8d0b685bb39d7879ab657f301c17155d
Qwen3.5-35B-A3B-UD-Q8_K_XL.gguf48.7 GB86aaf646491f623ce0a7d6983ea8788e36b09d59e5543a4799ccc57ee3af15a9
README.md96.0 KBe2f5f097b5c94a88e863b63f3b2a95131c24c4845f61c191337ee89be10414f4
config.json3.23 KB828c229801ef1fb269c67b0012fed4c5694b8d14edf2c3f933159a50b295766f
imatrix_unsloth.gguf_file192 MB01f37f18b7edb65e42f00bcc75dc9fb9ea502a3ffe5dd4db72304fc34934a71d
mmproj-BF16.gguf903 MBabe81a7212be307a7723ab47a51a87e5c46d0622273ccb04a6a6feba18b21d63
mmproj-F16.gguf899 MBa516ab92e8240da4734d68352bdfba84c16e830ee40010b8fac80d69c77272ff
mmproj-F32.gguf1.79 GB5de13d9052180b24cceda247af3023e3a2cbe785612198efe05b81905e3a5dc7
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
bc014a17be pinned now manifest updated, same commit2026-11-14 21:32 UTC32 files · 577 GB
bc014a17be2026-11-14 21:32 UTC32 files · 577 GB

Use it

$ fw get unsloth/Qwen3.5-35B-A3B-GGUF
# manifest sha256 2206e4524a00… · 577 GB · 32 files
$ fw verify ./Qwen3.5-35B-A3B-GGUF unsloth/Qwen3.5-35B-A3B-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-35B-A3B-GGUF.json --dir ./Qwen3.5-35B-A3B-GGUF $ python3 fw.py verify ./Qwen3.5-35B-A3B-GGUF ./unsloth__Qwen3.5-35B-A3B-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-35B-A3B-GGUF --revision bc014a17be43adabd7066b7a86075ff935c6a4e2 --local-dir ./Qwen3.5-35B-A3B-GGUF
llama.cppDownload one GGUF variant (Qwen3.5-35B-A3B-UD-IQ2_XXS, 10.7 GB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-35B-A3B-GGUF --include "Qwen3.5-35B-A3B-UD-IQ2_XXS*" --local-dir ./Qwen3.5-35B-A3B-GGUF $ llama-server -m ./Qwen3.5-35B-A3B-GGUF/Qwen3.5-35B-A3B-UD-IQ2_XXS.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./Qwen3.5-35B-A3B-GGUF/Qwen3.5-35B-A3B-UD-IQ2_XXS.gguf\n' > Modelfile $ ollama create qwen3.5-35b-a3b-gguf -f Modelfile
Run at home

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-14
Text in
README.md
Text sha256
e2f5f097b5c94a88e863b63f3b2a95131c24c4845f61c191337ee89be10414f4
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.qwenSubject: Qwen3.5-35B-A3B-GGUFDate: 2026-11-14Commit: bc014a1Signed: 2DC28CC7B26A283B ✓
Upstream
unsloth/Qwen3.5-35B-A3B-GGUF
Pinned commit
bc014a17be43adabd7066b7a86075ff935c6a4e2
Manifest
Qwen3.5-35B-A3B-GGUF.json · .minisig
Manifest sha256
2206e4524a00edca3faae27dc548bbe8d9fcc7c7e9e7da5fda9aee6ecd8094ab
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 21:32 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-35B-A3B-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-35B-A3B-GGUF.json.minisig $ minisign -Vm Qwen3.5-35B-A3B-GGUF.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

Parent

Qwen/Qwen3.5-35B-A3B · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-35B-A3B-GGUF
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. Qwen3.5-35B-A3B-GGUF.json. Provenance. Takedown history: none.
Source
huggingface.co/unsloth/Qwen3.5-35B-A3B-GGUF

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