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alt.freeweights.qwen / Qwen3.5-27B-GGUF
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.qwenSubject:

Qwen3.5-27B-GGUF

Date: 2026-11-14Commit: 3221f17Signed: 2DC28CC7B26A283B ✓

Image text to text model. Gguf weights, 424 GB in all. Published by unsloth under Apache-2.0.

qwen424GBQwen3.5-27B-GGUFggufpermissive
FactsParamsnot statedSize424 GBFormatsggufTaskimage text to textLicenseApache-2.0From sourcepermissive
$ fw get unsloth/Qwen3.5-27B-GGUF
# manifest sha256 3a73c82c82ab… · 424 GB · 29 files
$ fw verify ./Qwen3.5-27B-GGUF unsloth/Qwen3.5-27B-GGUF
From sourceHosted (signed)unsloth/Qwen3.5-27B-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.

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Overview

Size
424 GB
Weights
8.57 GB (smallest of 22 GGUF variants)
Parameters
not stated
Formats
gguf
Task
image text to text
License
Apache-2.0 (permissive)
Files
29, each with a sha256
Publisher
unsloth
Added
2026-11-14
Section
alt.freeweights.qwen
Lineage

Original release from the publisher.

Base model: Qwen/Qwen3.5-27B

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.

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

Model card

From the publisher at commit 3221f17. 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://docs.unsloth.ai/models/qwen3.5

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

Mar 5 Update:#

  • All GGUFs now use our new imatrix data. See some improvements in chat, coding, long context, and tool-calling use-cases.
  • Rest of variants like UD_K_XL are now uploaded.

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

Qwen3.5-27B#

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.

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: 27B
    • Hidden Dimension: 4096
    • Token Embedding: 248320 (Padded)
    • Number of Layers: 64
    • Hidden Layout: 16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))
    • Gated DeltaNet:
      • Number of Linear Attention Heads: 48 for V and 16 for QK
      • Head Dimension: 128
    • Gated Attention:
      • Number of Attention Heads: 24 for Q and 4 for KV
      • Head Dimension: 256
      • Rotary Position Embedding Dimension: 64
    • Feed Forward Network:
      • Intermediate Dimension: 17408
    • 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 | 13.0 | 13.1

| SUNRGBD | -- | -- | 34.9 | 36.2 | 35.4 | 33.4

| Nuscene | -- | -- | 13.9 | 15.4 | 15.2 | 14.6

| Video Understanding

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

Files

29 files · 424 GBWeights 8.57 GB (smallest of 22 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 29 files with their sha256
FileSizesha256
.gitattributes3.24 KB51e73cc5d71bdf74e426c43b324ec0a7561e425a02951fc47d5ccbd9c08b3787
BF16/Qwen3.5-27B-BF16-00001-of-00002.gguf50.0 GBc834354ad4ddc2054ac400842ea20d8801bd6718f6cda95baeed6796b5e17e4f
BF16/Qwen3.5-27B-BF16-00002-of-00002.gguf3.85 GBcd31f613eff781cde1bfe2b897a1eb37104bf0072a7bc5d1b4e9d363bd75a9bc
Qwen3.5-27B-IQ4_NL.gguf15.7 GB2329e260f3b6d1aef7f7813bc47c16e2efc01cd7c032577549c4971235d6a96c
Qwen3.5-27B-IQ4_XS.gguf15.0 GBfb829c84491b30cda875b7366e29ce3e4cede19b40daf5b824003936bfc4dbbb
Qwen3.5-27B-Q3_K_M.gguf13.5 GBf08ce37ebe8a7130db0c198262336773976b1e374f2444f898c41117710f0bb3
Qwen3.5-27B-Q3_K_S.gguf12.3 GB4da64157d83ede86cce1b7c354ba6532181cae158a791324cdf3855ec0df691f
Qwen3.5-27B-Q4_0.gguf15.7 GB4830d88d6abe246a070f549fc906b3f79b0116173da4225ae6b0ffc2387a622d
Qwen3.5-27B-Q4_1.gguf17.2 GB327aa26b00adf147d7ae51fa4bff24643444dd421c4620bf2d238f05afb728b1
Qwen3.5-27B-Q4_K_M.gguf16.7 GB84b5f7f112156d63836a01a69dc3f11a6ba63b10a23b8ca7a7efaf52d5a2d806
Qwen3.5-27B-Q4_K_S.gguf15.8 GB223f8c0a94be9e94c36e3c4abf742067a0eea452f31b6b264824c030957508ee
Qwen3.5-27B-Q5_K_M.gguf19.6 GBe41a488a3f013dbfb323563d7250105b1e708daf084942f9011344ad1525996f
Qwen3.5-27B-Q5_K_S.gguf18.9 GBf4d4f26d54c36608a559f21df730ad55ff90943fb41ef9406c2733972644a9e8
Qwen3.5-27B-Q6_K.gguf22.5 GB69e0f8527e0d937097cbcd486b51e2effaed963f49ef7962c9ef3eab45164ff8
Qwen3.5-27B-Q8_0.gguf28.6 GB6b0a101b0a86697fe11eabcc1a7db72699a9f3d4b18b6a1ac75ea3fb2c26c450
Qwen3.5-27B-UD-IQ2_M.gguf10.2 GB3c05eb29a4eacbe0caf80990c14f5857d0581af0b162934a42357960a99fb4ba
Qwen3.5-27B-UD-IQ2_XXS.gguf8.57 GB097435ea0befcd2edca4934b5ff387388d0396dea6b5c4c17a02ed8c696ae958
Qwen3.5-27B-UD-IQ3_XXS.gguf11.5 GBb694e54fe124e299e1342a9f0b81f1a51e3c8bbccf11c0bd94394b28cc8ae2f9
Qwen3.5-27B-UD-Q2_K_XL.gguf11.2 GB413992235c68b6da9dbb142f6da1c0eb011b58dc86b2a4809dde0008f216cd68
Qwen3.5-27B-UD-Q3_K_XL.gguf14.4 GBf97830c686a5e87f9949fa58c2b735afc929553addd84d9b50c068e201510c9e
Qwen3.5-27B-UD-Q4_K_XL.gguf17.6 GB13cb6228344898afa50d963c02ae0d991ae25094eea8837db8d0e452e91c5888
Qwen3.5-27B-UD-Q5_K_XL.gguf20.2 GB423ebe4779f784a2921da340a0fab0c372fbafb4b9eb502ae3768218de01597a
Qwen3.5-27B-UD-Q6_K_XL.gguf25.7 GB816bfc5160e699c123c7900ccaf3189e2e442407389281c852f1e4b685a8395d
Qwen3.5-27B-UD-Q8_K_XL.gguf35.5 GB40bfd1604775f784b7e2d51eb8997435f9e9541d0481f50619c7823f73a2ebef
README.md93.9 KB73cf7402d2fce28461118120566e1b1aa48116d3ba76e00271ba99100010a0bb
imatrix_unsloth.gguf_file13.6 MB8ecdca2d8353f90ab4e0dd56237ccc3b77917b57847b4b657bc3712141680ea5
mmproj-BF16.gguf931 MB29fe388bf3a45b981b2b38b966834f90cbabf998158d75ff1dd1b70a9f5f121c
mmproj-F16.gguf928 MB458bc46d8f275866fde5d88c9c554d9d462a6e8e3a028090d9850e17ab6a1217
mmproj-F32.gguf1.84 GBcb04ce8bd243483434f3e05a51a3821258cac74187e409547742a729452b0756
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
3221f178a6 pinned now manifest updated, same commit2026-11-14 21:32 UTC29 files · 424 GB
3221f178a62026-11-14 21:32 UTC29 files · 424 GB

Use it

$ fw get unsloth/Qwen3.5-27B-GGUF
# manifest sha256 3a73c82c82ab… · 424 GB · 29 files
$ fw verify ./Qwen3.5-27B-GGUF unsloth/Qwen3.5-27B-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-27B-GGUF.json --dir ./Qwen3.5-27B-GGUF $ python3 fw.py verify ./Qwen3.5-27B-GGUF ./unsloth__Qwen3.5-27B-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-27B-GGUF --revision 3221f178a6b842d04f1fb42f1c413534adcc0a6a --local-dir ./Qwen3.5-27B-GGUF
llama.cppDownload one GGUF variant (Qwen3.5-27B-UD-IQ2_XXS, 8.57 GB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-27B-GGUF --include "Qwen3.5-27B-UD-IQ2_XXS*" --local-dir ./Qwen3.5-27B-GGUF $ llama-server -m ./Qwen3.5-27B-GGUF/Qwen3.5-27B-UD-IQ2_XXS.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./Qwen3.5-27B-GGUF/Qwen3.5-27B-UD-IQ2_XXS.gguf\n' > Modelfile $ ollama create qwen3.5-27b-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
73cf7402d2fce28461118120566e1b1aa48116d3ba76e00271ba99100010a0bb
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: Qwen3.5-27B-GGUFDate: 2026-11-14Commit: 3221f17Signed: 2DC28CC7B26A283B ✓
Upstream
unsloth/Qwen3.5-27B-GGUF
Pinned commit
3221f178a6b842d04f1fb42f1c413534adcc0a6a
Manifest
Qwen3.5-27B-GGUF.json · .minisig
Manifest sha256
3a73c82c82abd08e764d8494857ef8ede108f8e0bf585fd0d27b687a41601645
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/Qwen3.5-27B-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-27B-GGUF.json.minisig $ minisign -Vm Qwen3.5-27B-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/Qwen3.5-27B · 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/Qwen3.5-27B-GGUF
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. Qwen3.5-27B-GGUF.json. Provenance. Takedown history: none.
Source
huggingface.co/unsloth/Qwen3.5-27B-GGUF

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