MODEL PROFILE

Whittle-Qwen-3.8-35B-A3B-GGUF

logic65 · Whittle-Qwen-3.8-35B-A3B-GGUF

> ### ☕ 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.

Text generationreasoningcodelicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/1 01:15:41
OVERVIEW

Model overview

> ### ☕ 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.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。