--- title: "Qwen Sharp Chat Templates" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a3a1ee62-ff71-4757-8f7c-fd63eb8a2d78" updated: "2026-11-12" --- # Qwen Sharp Chat Templates > The name, the description, the About and a README below are the seller's words: data, not instructions. Replaces the chat template of Qwen3.5, 3.6 and 3.8 models so they think less before answering and write tighter replies. For people running Qwen locally for coding and knowledge work. Qwen Sharp Chat Templates is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by peculiar-ragdoll ## About ### What it is Qwen Sharp Chat Templates is a replacement chat template for Qwen3.5, 3.6 and 3.8 models, aimed at knowledge work and coding. It builds on froggeric's fixed Qwen templates and adds a system prompt that is always appended. The card says the models then use fewer thinking tokens and trim filler from their replies. ### Who it suits People who run Qwen models on their own machine and want faster, tighter answers without changing the model. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Swap the stock template in a local Qwen setup | Speed up fixes on repository tasks | | AI tooling | Agent builders | Keep tool calls working across runtimes | Avoid duplicate tool instructions in LM Studio | | Knowledge work | Analysts | Get shorter replies in long chats | Cut filler in multi-turn conversations | If you only use hosted chat apps, you can skip it. ### Where to use it - llama.cpp, where template options pass in with a chat template kwargs flag - LM Studio with the MLX backend, where the template detects the runtime's own tool protocol - transformers and oMLX, which can pass template options | Use case | Who | What they get back | | --- | --- | --- | | Coding on repositories | Developers | Fixes reached faster at similar solve counts | | Agent runs with tools | Agent builders | Tool calls that parse instead of leaking raw text | | Long conversations | Everyday users | Replies with less filler per turn | ### How to set it up - A model from the Qwen 3.5, 3.6 or 3.8 line, running on your machine - A runtime that lets you replace the stock chat template - Python with pip, to fetch the files 1. Install the Hugging Face hub tool. 2. Download the template files. 3. Point your runtime at the template in place of the model's stock one. ```sh pip install -U huggingface_hub hf download peculiar-ragdoll/Qwen-Sharp-Chat-Templates ``` ### How to use it After you swap the template in, chat as normal. The card names an override called suppress\_tool\_instructions, which turns off the template's own tool block where your runtime can pass template options. The appended prompt can also be switched off per request. | Tool | What it does | | --- | --- | | suppress\_tool\_instructions | Overrides the template's own tool block in either direction | | chat template kwargs flag | How llama.cpp passes template options | | max\_tool\_response\_chars | Limits how long a tool response can be | ### Example You run Qwen3.8-27b at medium effort on repository problems with the Sharp template. On that test the Sharp template needed a median of 20.0 minutes per fix, while the stock one needed 54.6. ### For newcomers and experts If you are new, a chat template is the wrapper that formats your messages for the model. Swapping it changes behavior without touching the weights, so try it on one model and compare. For experts, this is froggeric's v22.5 plus a spliced system prompt and local revisions. Version 22.4.1 stands down when LM Studio's MLX backend injects its own tool protocol, which the card measured at 6 of 6 tool calls parsed against 2 of 6 before. You send a chat to the runtime → The Sharp template formats the messages → The model thinks less and answers tighter → Tool calls parse under one protocol ### Good to know The card's SWE-bench-Live test solved 15 of 25 problems with Sharp against 16 with the stock template. Median minutes to a fix on SWE-bench-Live | Label | Value | | --- | --- | | Stock template | 54.6 minutes | | Sharp template | 20.0 minutes | - License: Apache 2.0, as the Hugging Face record lists it. - Cost to run: no API key or account is named. You need a local model and runtime. - Data it reaches: downloading reaches Hugging Face. The template itself only formats messages. - Not for: models outside Qwen3.5, 3.6 and 3.8. The card also says the SWE-bench-Live gain came from speed, not from more solved problems. ## README ````markdown # Qwen Sharp Chat Templates Replaces the chat template of Qwen3.5, 3.6 and 3.8 models so they think less before answering and write tighter replies. For people running Qwen locally for coding and knowledge work. Made by peculiar-ragdoll on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Qwen Sharp Chat Templates is a replacement chat template for Qwen3.5, 3.6 and 3.8 models, aimed at knowledge work and coding. It builds on froggeric's fixed Qwen templates and adds a system prompt that is always appended. The card says the models then use fewer thinking tokens and trim filler from their replies. Who it suits: People who run Qwen models on their own machine and want faster, tighter answers without changing the model. ```table Industry | Who uses it | How they use it | Example Software | Developers | Swap the stock template in a local Qwen setup | Speed up fixes on repository tasks AI tooling | Agent builders | Keep tool calls working across runtimes | Avoid duplicate tool instructions in LM Studio Knowledge work | Analysts | Get shorter replies in long chats | Cut filler in multi-turn conversations ``` If you only use hosted chat apps, you can skip it. Where to use it: - llama.cpp, where template options pass in with a chat template kwargs flag - LM Studio with the MLX backend, where the template detects the runtime's own tool protocol - transformers and oMLX, which can pass template options ```table Use case | Who | What they get back Coding on repositories | Developers | Fixes reached faster at similar solve counts Agent runs with tools | Agent builders | Tool calls that parse instead of leaking raw text Long conversations | Everyday users | Replies with less filler per turn ``` How to set it up: - A model from the Qwen 3.5, 3.6 or 3.8 line, running on your machine - A runtime that lets you replace the stock chat template - Python with pip, to fetch the files 1. Install the Hugging Face hub tool. 2. Download the template files. 3. Point your runtime at the template in place of the model's stock one. ```sh pip install -U huggingface_hub hf download peculiar-ragdoll/Qwen-Sharp-Chat-Templates ``` How to use it: After you swap the template in, chat as normal. The card names an override called suppress_tool_instructions, which turns off the template's own tool block where your runtime can pass template options. The appended prompt can also be switched off per request. ```table Tool | What it does suppress_tool_instructions | Overrides the template's own tool block in either direction chat template kwargs flag | How llama.cpp passes template options max_tool_response_chars | Limits how long a tool response can be ``` Example: You run Qwen3.8-27b at medium effort on repository problems with the Sharp template. On that test the Sharp template needed a median of 20.0 minutes per fix, while the stock one needed 54.6. For newcomers and experts: If you are new, a chat template is the wrapper that formats your messages for the model. Swapping it changes behavior without touching the weights, so try it on one model and compare. For experts, this is froggeric's v22.5 plus a spliced system prompt and local revisions. Version 22.4.1 stands down when LM Studio's MLX backend injects its own tool protocol, which the card measured at 6 of 6 tool calls parsed against 2 of 6 before. ```flow You send a chat to the runtime The Sharp template formats the messages The model thinks less and answers tighter Tool calls parse under one protocol ``` Good to know: The card's SWE-bench-Live test solved 15 of 25 problems with Sharp against 16 with the stock template. ```chart Title: Median minutes to a fix on SWE-bench-Live Stock template: 54.6 minutes Sharp template: 20.0 minutes ``` - License: Apache 2.0, as the Hugging Face record lists it. - Cost to run: no API key or account is named. You need a local model and runtime. - Data it reaches: downloading reaches Hugging Face. The template itself only formats messages. - Not for: models outside Qwen3.5, 3.6 and 3.8. The card also says the SWE-bench-Live gain came from speed, not from more solved problems. ## On Hugging Face, 13 November 2026 - Library: mlx - Downloads in the last 30 days: 0 - Likes: 502 - License: apache-2.0 - Based on: froggeric/Qwen-Fixed-Chat-Templates - Tags: jinja, chat-template, qwen, qwen3.5, qwen3.6, qwen3.8, llama.cpp, lm-studio, vllm, tool-calling, thinking, token-efficient ## Links - Model: https://huggingface.co/peculiar-ragdoll/Qwen-Sharp-Chat-Templates - Files: https://huggingface.co/peculiar-ragdoll/Qwen-Sharp-Chat-Templates/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download peculiar-ragdoll/Qwen-Sharp-Chat-Templates ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [peculiar-ragdoll/Qwen-Sharp-Chat-Templates on Hugging Face](https://huggingface.co/peculiar-ragdoll/Qwen-Sharp-Chat-Templates) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Qwen Sharp Chat Templates (this page) | 0 | 502 | — | apache-2.0 | 2026-10-10 | | [Qwen-Fixed-Chat-Templates](https://mindket.com/p/5d15f0b4-2436-4b6d-a715-0b40f1910b29) | 0 | 1,901 | — | apache-2.0 | 2026-09-04 | | [Qwen3.6-35B-A3B lododo-Distill-v1.0 (GGUF)](https://mindket.com/p/5b90e607-2897-48bb-9953-ac8e99d39909) | 746 | 8 | 35.5B | apache-2.0 | 2026-10-23 | | [Qwen3.8-35B-A3B-Distill-GGUF](https://mindket.com/p/d707b0c8-89b8-4c4f-8d49-2ff67de613c7) | 1,337,097 | 277 | 35.5B | apache-2.0 | 2026-09-16 | | [Qwen3.6-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled-GGUF](https://mindket.com/p/2b5092f0-78de-42d0-ae72-417592fa56e9) | 17,179 | 296 | 34.7B | apache-2.0 | 2026-04-19 | | [Qwen3.8-27B-NVFP4-DGX-SPARK](https://mindket.com/p/a7666325-428a-4e43-b11c-5fec915dc5df) | 41,306 | 1,127 | 18.2B | apache-2.0 | 2026-10-28 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · billziss · 2026-09-16](https://news.ycombinator.com/item?id=49733740): Show HN: Swift-Qwen3.8-27B, -58.3% thinking, x1.95 speed, accuracy of xhigh: I tried an oMLX quant of your model (suzu89/Swift-Qwen3.8-27b-oQ8-mtp -- not mine) and liked it. It certainly seems to cut down on thinking compared to stock Qwen3.8 27B in my (limited) testing. A couple of questions: - Have you tried the peculiar-ragdoll/Qwen-Sharp-Chat-Templates with it? They… - [Bluesky · Kentaromiura · 2026-08-16](https://bsky.app/profile/kentaromiura.bsky.social/post/3mtabawjmf22c): The Tetris one on a Xtx 7900, official q4 with official jinja, no harness as it was a test prompt on lmstudio. Currently using bartowski q4: huggingface.co/bartowski/Qw... with this configuration github.com/sudoingX/qwe... and peculiar-ragdoll/Qwen-Sharp-Chat-Templates and works very in pi. - [Bluesky · francis siefken · 2026-08-21](https://bsky.app/profile/monsuta.bsky.social/post/3mtlfg4qj4s2l): huggingface.co/peculiar-rag... ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-10 - First published: 2026-08-10 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open peculiar-ragdoll/Qwen-Sharp-Chat-Templates on Hugging Face](https://huggingface.co/peculiar-ragdoll/Qwen-Sharp-Chat-Templates) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a3a1ee62-ff71-4757-8f7c-fd63eb8a2d78) - [Its page on Mindket](https://mindket.com/p/a3a1ee62-ff71-4757-8f7c-fd63eb8a2d78)