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AI skills and agents for developers

Prompts, coding agent briefs and kits for writing and reviewing code with fewer tokens.

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Qwen3.8-9B-Distill

empero-ai · Kit

Reasons step by step through math, code and general questions, opening each answer with a thinking block. A 9B Qwen3.5 model trained on traces from a larger Qw…

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A draft model in GGUF form that speeds up Qwen3.8-27B by proposing token blocks for the main model to verify. For people who run that model locally with llama.…

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Adds Cloudflare Clef's decision head to a Qwen3.8-27B chat model, so one llama.cpp server on a 24 GB GPU both answers typed questions and chats. It is a LoRA a…

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Cuts the length of Qwen3.8-27B's reasoning on coding tasks so answers arrive sooner, as a small LoRA adapter. For people who run the base model on their own ha…

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A 27B vision-language model compressed to 3.5 bits per weight for Apple Silicon Macs with 24 GB of memory, served locally through Rapid-MLX. Suits Mac users an…

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A pre-quantized NVFP4 copy of Qwen3.8-27B that reads text, images and video and answers in text, served with SGLang on NVIDIA Blackwell GPUs. Suits developers…

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Qwen3.8-27B-QUASAR-NVFP4

QUASAR-QAT · Kit

Runs Qwen3.8-27B in 4-bit NVFP4 at 19.7 GB, trained with the QUASAR method to stay close to the full BF16 model. For people serving it with vLLM on an NVIDIA B…

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GGUF draft model that speeds up Qwen3.8-Flash-Next in llama.cpp through speculative decoding, in 334 MiB and 622 MiB files. It is not a standalone model, and i…

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GGUF quantized files of a 27.3B coding-distilled Qwen3.8 model, from 2-bit to 8-bit with an optional multi-modal supplement. They suit developers who run a cod…

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Qwen3.8-27B-MLX-8bit

lmstudio-community · Kit

Runs a 27B model that reads images and text in an 8-bit MLX build for Apple Silicon Macs. It suits people who want picture questions answered locally.

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Runs Qwen3.8-27B as an 8-bit mixed-precision MLX checkpoint with its vision encoder and MTP head, for image and text chat on Apple hardware. For people who wan…

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Runs the 27B Qwen3.8 vision-language model on MLX in about 17.5 GB, reading text, images and video with a 262,144-token context. A mixed-precision quantization…

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JDI-Decision-V0.9

JoyIndustrial · Kit

Answers multiple-choice style questions about images and text with option probabilities, using a Qwen3.8-27B decision system with built-in OCR. For developers…

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Cuts reasoning time and cost for long agent tasks, as a GGUF build of a Qwen3.8-27B fine-tune. Made for people who run agent loops on their own machine and wan…

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Serves Qwen3.8-27B in NVFP4 on one RTX 5090 with vLLM, with a checksum-verified download, FP8 KV cache, tool calls and reasoning support. For developers self-h…

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An English-only coding model in GGUF, a 42.6B mixture-of-experts quant of about 21.8 GB, for code completion, refactoring and agentic tool calls in llama.cpp o…

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Kvark-Sparkle-1.0-27B

Egzakta · Kit

Reasons over images and text with fewer thinking tokens than its base Qwen3.8-27B, so answers arrive in about half the time at similar accuracy, per its card.…

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Runs Qwen3.8-27B at 8-bit through the Splash runtime in LM Studio on Apple silicon. An unofficial package that keeps the model closer to the original than the…

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A 4-bit MLX build for Apple Silicon of a mixture-of-experts model carved from the dense Qwen3.8-27B, with 17.8B active of 27B total parameters. For people who…

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Speeds up Qwen3.8-27B NVFP4 decoding about 3.9 times on a DGX Spark, using the same weights and a tuned speculative-decoding setup. For teams serving it with v…

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Runs Qwen3.8-27B as a smaller MXFP4-quantized copy made with AMD Quark and AWQ, served through vLLM. Made for developers who want a compressed 27B vision-langu…

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Packs Qwen3.8-27B as llama.cpp GGUF files in eight sizes from 8.95 to 16.35 GiB, plus a vision projector. The author reports less drift from the BF16 model tha…

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Squeezes the Qwen3.8-Flash-Next mixture-of-experts model into about 37 GiB of text-only GGUF files for experiments. It needs a patched llama.cpp build that com…

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Qwen3.8-27B-QSA-GSQ-RCO-GGUF

pentacoxian-dev · Kit

Runs Qwen3.8-27B with sparse attention on a single 24 GB GPU at a 262K-token context with image input, as GGUF files for people with a custom llama.cpp engine…

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Importance-matrix GGUF quants of the Qwen3.8-27B-CodeForge-3xMerge model, from about 11 GB to 22.5 GB, for local use. For people running 27B models on their ow…

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Runs as a local text model, a Qwen3.6-35B-A3B fine-tune trained on data written by Qwen3.8-27B and packed as one GGUF file for llama.cpp. For people who run mo…

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Debugs and reviews code by checking real files before it proposes a fix, a Qwen3.8-27B fine-tune trained on 195M tokens of reasoning traces. For developers who…

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Qwen3.8-27B-SLQ-GGUF

kaitchup · Kit

Compresses Qwen3.8-27B into three GGUF files with different size and fidelity levels, using a custom statistically lossless quantization. For people who run th…

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A mixed-precision MLX copy of Qwen3.8-27B at about 6.9 bits per weight, with the vision encoder and multi-token prediction head included, for running locally o…

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Qwen3.8-27B Astra stop edit

jarrodwatts · Kit

A small weight edit for Qwen3.8-27B, with a script that applies it, that cuts the model's thinking length on open-ended tasks by changing a single matrix, with…

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Trims wasted reasoning in long agent tasks, as a GGUF build of the second Flash fine-tune of Qwen3.8-27B with better Python formatting. For people who run agen…

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Writes code, calls tools and works through software tasks as a coding agent. A 27.8B fine-tune of Qwen3.8-27B by Jackrong, trained on about 200,000 code and re…

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Speeds up Qwen3.8-27B by drafting blocks of tokens that the main model then checks, with output unchanged. A 1.9B draft model for SGLang and vLLM servers, not…

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Holo4-27B

Hcompany · Kit

Looks at screenshots and decides the next click, keystroke, code run or tool call, built on Qwen3.8-27B. A computer-use model for web, desktop and mobile agent…

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Runs a 27B Qwen3.8 model in GGUF files retuned for Intel Arc GPUs, with pure decode near 22 tokens a second in the author's tests. For people running llama.cpp…

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A GGUF build of Qwen3.8-Flash-Next by DavidAU with 27 reasoning modes, 27 instruct modes and 15 AI personas you switch on from the prompt. For people with larg…

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Qwen3.8-27B-AWQ-INT4

cyankiwi · Kit

A 4-bit AWQ quantization of Qwen3.8-27B by cyankiwi, a 27B vision-language model with thinking control. Weights are 21.02 GB and load in Transformers, vLLM or…

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A 17.1 GB mixed-precision GGUF of Qwen3.8-27B that keeps its multi-token prediction layer, tuned for 256K context with vision on a 24 GB GPU. For people who ru…

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Nimble-v4-max

bespokelabs · Kit

Gives a probability for every answer option when you pass a context and typed questions such as choices, yes or no, or ordered scores. A fine-tune of Qwen3.8-2…

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Signal 3.8 27B

agentionai · Kit

Gives shorter, more direct answers than Qwen3.8-27B by using fewer answer and thinking tokens, so replies finish sooner. A light fine-tune that drops into the…

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Writes and explains code and works through reasoning problems, from a weighted merge of three Qwen3.8-27B fine-tunes. For developers who want one general-purpo…

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Qwen3.8-27B-Splash

incoai · Kit

Serves Qwen3.8-27B on Apple silicon Macs through Inco AI's Splash engine, with a 4-bit model, a DFlash 2 draft and a vision encoder in one package. Works only…

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A 27B reasoning model tuned to answer plainly instead of hedging, quantized to MXFP4 so vLLM can serve it on a single 32 GB GPU, for developers who run local r…

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Qwen3.8-27B-Ridge-GGUF

empero-ai · Kit

Runs Qwen3.8-27B as a compact 3.7 bits-per-weight GGUF file that suits a 16 GB GPU, with optional image input. For people running models locally with llama.cpp…

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ttf-Qwen3.8-Flash-Next-GGUF

oguzeldereli · Kit

Runs Qwen3.8-Flash-Next, a 180B mixture-of-experts model squeezed to ternary weights, from one 40.4 GB GGUF file that is 4.6 times smaller than the FP8 release…

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ttf-Qwen3.8-27B-GGUF

oguzeldereli · Kit

Runs Qwen3.8-27B squeezed to ternary weights as GGUF files that fit on a 12 GB GPU, in an 8.2 GB and a 6.74 GB variant. For people who want a large local model…

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A set of GGUF quantizations of Qwen3.8-27B by bartowski, from Q8_0 down to 3-bit, made with an importance matrix. For people running a 27B vision-language mode…

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