Qwen3.6-Whittle-25B-A3B
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言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
> ### ☕ Support this work > Whittle is built by one person on a grocery budget and rented GPU hours. If this research is useful to you, or you want to see it finished: > **ko-fi.com/davida81328**. Every hour of GPU time goes straight into the next checkpoint, and every checkpoint, table and log lands in these repos. **A 27B whittled down to 16.8B with a logit lens and a pricing table, then healed with one A100 evening. It now outscores every intermediate cut, including ones 4B larger, at 20 tokens/second on two consumer 8GB GPUs.** Whittle is Qwen3.8-27B minus 20 of its 64 layers (whole interval-blocks, chosen by measured boundary cost) and minus 25% of every remaining MLP's width (weakest neurons by ‖down_column‖ × activation-std). That is a −10.1B parameter cut performed with **zero training**, followed by a single 11M-token QLoRA heal on a fully clean-lineage mix (synthetic fact frames, programmatic short-think arithmetic, hand-written code drills, public-domain long pages).
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> ### ☕ Support this work > Whittle is built by one person on a grocery budget and rented GPU hours. If this research is useful to you, or you want to see it finished: > **ko-fi.com/davida81328**. Every hour of GPU time goes straight into the next checkpoint, and every checkpoint, table and log lands in these repos. Quantized builds of Whittle MoE 27B (A18B), a post hoc mixture of experts carved from Qwen3.8-27B and taught when to stop talking. v2.1 passed every release bar: 8 percent single turn loop rate (down from 69 at first release), 22 percent structured (down from 75), zero truncated answers, knowledge battery 28 of 39. Method, measurements, and the failures along the way are on the main model card. Earlier line (Aug 2026); the current Whittle models are the Whittle-Next / Whittle-Qwen-3.8 line: Whittle-Qwen-3.8-35B-A3B.
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
> ### ☕ Support this work > Whittle is built by one person on a grocery budget and rented GPU hours. If this research is useful to you, or you want to see it finished: > **ko-fi.com/davida81328**. Every hour of GPU time goes straight into the next checkpoint, and every checkpoint, table and log lands in these repos. Ready-to-run **llama.cpp** quantisations of logic65/Whittle-Qwen-3.8-35B-A3B: a 35.1 B-total, ~3 B-active mixture-of-experts in the Qwen3.8-Flash-Next (`qwen4_exp`) format with a **10 B-parameter n-gram memory that is load-bearing** (the body measurably needs it; see the base card). Distilled from Qwen3.8-27B at the logit level on 25k verified teacher traces; built on Whittle-Next-27B-A3B. **Runs on stock llama.cpp, no patches.** The full card, measurements and caveats are on the base repo; this repo is the download. **Current.** These files are the **Phase-2 step 32010 root** (*p2-s32010*, 30 Sep 2026) of the current Whittle flagship: the complete Phase-2 distillation from Qwen3.8-27B (every usable teacher row seen once), a memory phase, and a 410-step fix for the llama.cpp web page's browser tools. The previous (p2-s6000) ladder was replaced in place; the earlier full weights stay under `bf16-s6000/`, `bf16-agentfix2/`, `bf16-lw5/`, `bf16-lw2/` and `bf16-tbl1/` on the base repo.
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基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。
基本情報を収録・詳細は順次追加
提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
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