CoolFace
Modelpublic

backpack-run/Qwen3-Coder-Next-GGUF

sourceHugging Faceapache-2.0updated 22d agoView on Hugging Face
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Model Card

Qwen3-Coder-Next-GGUF — Backpack GGUF

GGUF quantizations of Qwen/Qwen3-Coder-Next-GGUF, tested for llama.cpp-compatible text inference and packaged for Backpack. The original publisher produced these GGUF files; Backpack verified and repackaged the immutable artifacts without re-quantizing them.

Model

PropertyValue
Original modelQwen/Qwen3-Coder-Next-GGUF
Original publisherQwen
Upstream revisionb82fb7382639d97b38fa7672e526c760c2fb358e
ArchitectureQwen3NextForCausalLM
Parameters79,674,391,296
Context length262,144
Input modalitiestext
Output modalitiestext
Licenseapache-2.0

Available packages

QuantizationSizeApprox. RAMRecommended for
Q4KM45.1 GiB66.35 GBMost users
Q5KM52.8 GiB77.56 GBHigher quality
Q8_079.0 GiB115.5 GBPlenty of memory

Memory values are estimates, not guarantees. Runtime configuration and context length change actual use.

Backpack recommendation

Recommended: Q4_K_M. It usually offers a practical quality, size, and speed balance for local inference.

Run with llama.cpp

Using the llama.cpp revision recorded below:

bash
llama-completion --model Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf -cnv

Run with Backpack

These artifacts and backpack-model.yaml are prepared for the Backpack AI workspace.

Validation

PackageIntegrityLoadInferenceTokenizer
Q4KMpassedpassedpassedpassed
Q5KMpassedpassedpassedpassed
Q8_0passedpassedpassedpassed

Capability qualification: code

Tested with Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf. These are deterministic smoke tests, not benchmark scores.

CapabilityStatus
chatpassed
code_generationpassed
structuredtoolargumentspassed
tool_callingpassed
multiturntool_looppassed
  • —Packaged: 2026-08-31T11:20:27.760656+00:00
  • —llama.cpp revision: bdf3955159d7184f44b76091973eeff532890a35
  • —SHA-256 checksums: see checksums.sha256
  • —Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00001-of-00004.gguf: 6bcfc9f9c37901eeb92172e2ab871224dab36a453d263bcb2547f737409534da
  • —Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00002-of-00004.gguf: 817def0691ee9d08bf3dc4444be7aed29c9e52091e8fa9d97901ce7e7f6f01d3
  • —Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00003-of-00004.gguf: 23aa634d47dca9b4ca3ea249384e6f01951b24c83cdc076f37f6f43d6c99883f
  • —Qwen3-Coder-Next-Q4_K_M/Qwen3-Coder-Next-Q4_K_M-00004-of-00004.gguf: 249c768cc5f130dc731567d6edcbdacc48e14dec9e02c5dbe2b2185d2c5bdb2b
  • —Qwen3-Coder-Next-Q5_K_M/Qwen3-Coder-Next-Q5_K_M-00001-of-00004.gguf: d68162877891c4ba309c8601a69721ecfc7be2091ad99e8175a078ae59decdd3
  • —Qwen3-Coder-Next-Q5_K_M/Qwen3-Coder-Next-Q5_K_M-00002-of-00004.gguf: 3da1a3fda1061009126eb48c7098221653ab63e0a266d3b6d04f5eac3ae9aa74
  • —Qwen3-Coder-Next-Q5_K_M/Qwen3-Coder-Next-Q5_K_M-00003-of-00004.gguf: df60c7a55c6e118d4984a829b74df6b9e863dcea749ee7dc25ab5e72913624e1
  • —Qwen3-Coder-Next-Q5_K_M/Qwen3-Coder-Next-Q5_K_M-00004-of-00004.gguf: 777ac63a6f94272934996b1cfd7e5619c6804e8580ec4e00311d2a465e298c6a
  • —Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00001-of-00004.gguf: 30b7554fc0c846a5dc3ecf585884c77471f73e3da698a8ba4fabd8e7868c6533
  • —Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00002-of-00004.gguf: 3f96379de5a5c4655cb378710ea571d5e9cc96f260120a44a6477198efcdc27d
  • —Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00003-of-00004.gguf: 5dd1ce07eaae95ee430331dc9c6f3120ff88e4211ad3a0cceeaa963f25328504
  • —Qwen3-Coder-Next-Q8_0/Qwen3-Coder-Next-Q8_0-00004-of-00004.gguf: 76730702c630bf76305139165cb85421858604030851dfd64fe96a5e67cda99d

Provenance

The source model was resolved to immutable revision b82fb7382639d97b38fa7672e526c760c2fb358e. The GGUF files were quantized by Qwen and verified by Backpack against the pinned llama.cpp revision recorded above.

License and attribution

Upstream declares apache-2.0. Review the upstream model card and comply with all applicable terms.

Backpack does not claim ownership of the original model. Backpack did not quantize the upstream GGUF artifacts.

Disclaimer

Quantization can alter output quality. Memory estimates vary with runtime configuration, context length, and hardware.