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alt.freeweights.qwen / Qwen3.5-122B-A10B-GGUF
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.qwenSubject:

Qwen3.5-122B-A10B-GGUF

Date: 2026-11-15Commit: 51eab4dSigned: 2DC28CC7B26A283B ✓

Image text to text model. Gguf weights, 1.86 TB in all. Published by unsloth under Apache-2.0.

qwen1.86TBQwen3.5-122B-A10B-GGUFggufpermissive
FactsParamsnot statedSize1.86 TBFormatsggufTaskimage text to textLicenseApache-2.0From sourcepermissive
$ fw get unsloth/Qwen3.5-122B-A10B-GGUF
# manifest sha256 525c1cc97309… · 1.86 TB · 71 files
$ fw verify ./Qwen3.5-122B-A10B-GGUF unsloth/Qwen3.5-122B-A10B-GGUF
From sourceHosted (signed)unsloth/Qwen3.5-122B-A10B-GGUFLast check: 2026-11-15 04:37 UTC
Run at homeGet help

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

Quantized of Qwen3.5-122B-A10B.

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Overview

Size
1.86 TB
Weights
359 MB (smallest of 24 GGUF variants)
Parameters
not stated
Formats
gguf
Task
image text to text
License
Apache-2.0 (permissive)
Files
71, each with a sha256
Publisher
unsloth
Added
2026-11-15
Section
alt.freeweights.qwen
Lineage

Original release from the publisher.

Base model: Qwen/Qwen3.5-122B-A10B

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.co2026-11-15 04:37 UTCpassed

Model card

From the publisher at commit 51eab4d. 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 updated with an improved quantization algorithm.
  • Updated with fixed chat template for improved tool-calling & coding performance!
  • See our new benchmarks for 122B-A10B here.

Image: 122b final

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

Fine-tuning and RL Qwen3.5#

Qwen3.5-122B-A10B#

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: 122B in total and 10B activated
    • Hidden Dimension: 3072
    • Token Embedding: 248320 (Padded)
    • Number of Layers: 48
    • Hidden Layout: 16 × (3 × (Gated DeltaNet → MoE) → 1 × (Gated Attention → MoE))
    • Gated DeltaNet:
      • Number of Linear Attention Heads: 64 for V and 16 for QK
      • Head Dimension: 128
    • Gated Attention:
      • Number of Attention Heads: 32 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: 1024
    • 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

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

Files

71 files · 1.86 TBWeights 359 MB (smallest of 24 GGUF variants). Sizes and sha256 from the signed manifest.
Show all 71 files with their sha256
FileSizesha256
.gitattributes9.49 KB489b80aa8468efbfecb3b595c5e1f6d31859e695eff9a193780770d571898cad
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UD-Q3_K_XL/Qwen3.5-122B-A10B-UD-Q3_K_XL-00003-of-00003.gguf7.19 GBfd42cf1f8bae5ce0b4d4d3f39cc066745c41dfd7311785c72745887700377b06
UD-Q4_K_XL/Qwen3.5-122B-A10B-UD-Q4_K_XL-00001-of-00003.gguf10.9 MB467c9bd92ea518539cf75bf5a5fbfbd35e9a0b40d766ccaa67bf120e12041df3
UD-Q4_K_XL/Qwen3.5-122B-A10B-UD-Q4_K_XL-00002-of-00003.gguf49.6 GBecdbd42d43b0df9fa0ef9a584e09e95a43966ef03a122aba0b87a99d44d9ad98
UD-Q4_K_XL/Qwen3.5-122B-A10B-UD-Q4_K_XL-00003-of-00003.gguf27.4 GB13300e0f059e6fa21aa0fabde2a554f9deea366c0e54f268045769b214b28c97
UD-Q5_K_XL/Qwen3.5-122B-A10B-UD-Q5_K_XL-00001-of-00003.gguf10.9 MBaaddf5fad610b8d681b41547f3e9a30988ce4419438e44e089cafb83843dc6e8
UD-Q5_K_XL/Qwen3.5-122B-A10B-UD-Q5_K_XL-00002-of-00003.gguf49.7 GBfc8f3008ec634667f1f931b8537154e7b25b683e5e1a99987e5388612dc5117c
UD-Q5_K_XL/Qwen3.5-122B-A10B-UD-Q5_K_XL-00003-of-00003.gguf42.2 GBd2d333a474b940936d58f81aafa64c48ae19b07abdf7294f5c98f51d6fa3d13d
UD-Q6_K_XL/Qwen3.5-122B-A10B-UD-Q6_K_XL-00001-of-00004.gguf10.9 MB72b6bd33099fc33de1bc0e1ca512ac438e76718ad454ff7162e522720d8001c8
UD-Q6_K_XL/Qwen3.5-122B-A10B-UD-Q6_K_XL-00002-of-00004.gguf50.0 GBa77ad76dfbd31565e6bc6fe7b380ae0b1092fdd04410ea016acd2c4f7d006670
UD-Q6_K_XL/Qwen3.5-122B-A10B-UD-Q6_K_XL-00003-of-00004.gguf49.8 GB3b751ddbc1e662fab8dfea10d06d35e8aa4d480a294ee7c1db2115fbd1dfdaae
UD-Q6_K_XL/Qwen3.5-122B-A10B-UD-Q6_K_XL-00004-of-00004.gguf12.6 GB8583d095c8d0289a893265a53f953bce21682adbd9b0e9656cfcadd5776ca7a1
UD-Q8_K_XL/Qwen3.5-122B-A10B-UD-Q8_K_XL-00001-of-00005.gguf10.9 MB7912a946792c2fcdb5c63596c97aefe680fa0bb2eae6c0c60ffa76f7f41c2479
UD-Q8_K_XL/Qwen3.5-122B-A10B-UD-Q8_K_XL-00002-of-00005.gguf49.7 GB59ad6ec60382613e8c0bf692002cfe301057e9b4d938416943cd2ea28d1ec647
UD-Q8_K_XL/Qwen3.5-122B-A10B-UD-Q8_K_XL-00003-of-00005.gguf49.2 GB89c4c27ffa0a478a0de72199ce0a0611361ee24791e93a674678bd6372483b57
UD-Q8_K_XL/Qwen3.5-122B-A10B-UD-Q8_K_XL-00004-of-00005.gguf50.0 GBb74d5bc0a2bad0f8b0cb7a027fc80922860770d3d78361592393d33972b312d3
UD-Q8_K_XL/Qwen3.5-122B-A10B-UD-Q8_K_XL-00005-of-00005.gguf22.0 GBa1dd0addf37701b3089f234d48e777ac92b8f4c6f3e14dd819b915888138c913
config.json3.43 KB22ae8b715b4fe37bdd67d61282ab932c207aa0141ea000d5377715a5f386b272
imatrix_unsloth.gguf359 MB41ec0555401a2abaf73589dcea1ca83d979573d45e8e838d1df722fd26e8cf1e
mmproj-BF16.gguf912 MBc4f22a6b5101ac85930029e0eec321bfaa4c0b16851f569759d3bac3fa31c744
mmproj-F16.gguf909 MB691af71bd41d437ce4a1d989f589c4b492237d702b33819ed8f897f9fae6e725
mmproj-F32.gguf1.81 GBba889ce164a6cc7ffe34296851d0f2bbe139bd27deeb7fe3830d08bd776a28a6
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
51eab4d59d pinned now2026-11-15 04:37 UTC71 files · 1.86 TB

Use it

$ fw get unsloth/Qwen3.5-122B-A10B-GGUF
# manifest sha256 525c1cc97309… · 1.86 TB · 71 files
$ fw verify ./Qwen3.5-122B-A10B-GGUF unsloth/Qwen3.5-122B-A10B-GGUF
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-122B-A10B-GGUF.json --dir ./Qwen3.5-122B-A10B-GGUF $ python3 fw.py verify ./Qwen3.5-122B-A10B-GGUF ./unsloth__Qwen3.5-122B-A10B-GGUF.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-122B-A10B-GGUF --revision 51eab4d59d53f573fb9206cb3ce613f1d0aa392b --local-dir ./Qwen3.5-122B-A10B-GGUF
llama.cppDownload one GGUF variant (imatrix_unsloth, 359 MB), then serve it.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/Qwen3.5-122B-A10B-GGUF --include "imatrix_unsloth*" --local-dir ./Qwen3.5-122B-A10B-GGUF $ llama-server -m ./Qwen3.5-122B-A10B-GGUF/imatrix_unsloth.gguf
OllamaMake an Ollama model from the downloaded file.
$ printf 'FROM ./Qwen3.5-122B-A10B-GGUF/imatrix_unsloth.gguf\n' > Modelfile $ ollama create qwen3.5-122b-a10b-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. 2026-11-15
Text in
README.md
Text sha256
99a4dd08b5afd32c0fdb727a14cb53289de896b8b0a439e62b2f71a76590da1f
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: Qwen3.5-122B-A10B-GGUFDate: 2026-11-15Commit: 51eab4dSigned: 2DC28CC7B26A283B ✓
Upstream
unsloth/Qwen3.5-122B-A10B-GGUF
Pinned commit
51eab4d59d53f573fb9206cb3ce613f1d0aa392b
Manifest
Qwen3.5-122B-A10B-GGUF.json · .minisig
Manifest sha256
525c1cc97309ded8c4f3aa415c78bd0250060941d4d2cb21acf4dbe2314c86aa
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 04:37 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-122B-A10B-GGUF.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/Qwen3.5-122B-A10B-GGUF.json.minisig $ minisign -Vm Qwen3.5-122B-A10B-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/Qwen3.5-122B-A10B · 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/Qwen3.5-122B-A10B-GGUF
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. Qwen3.5-122B-A10B-GGUF.json. Provenance. Takedown history: none.
Source
huggingface.co/unsloth/Qwen3.5-122B-A10B-GGUF

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