MODEL PROFILE

Cyber-Tiel-Coder-35B-A3B-MTP-TTQ-GGUF

TokenTinkerer · Cyber-Tiel-Coder-35B-A3B-MTP-TTQ-GGUF

**TTQ** (TokenTinkerer Quant) is a ten-rung GGUF ladder built from peculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-GGUF-MTP, from 3.34 bpw to 6.64 bpw. Every rung is **tensor-for-tensor the same shape** as our published Qwen3.6-35B-A3B TTQ ladder — the same ten ftypes in the same places on 733 body tensors — with the model's grafted MTP head carried at the precision upstream ships it. Every claim below is a measurement, not an estimate. > ⚠️ **This is a quant of an abliterated (uncensored) model.** It inherits CyberTiel's behaviour and > its usage warnings: it will not refuse, and with tool access it can do real harm. Read > the base model card > before running it, and sandbox it at the OS level. > **Source caveat — there is no full-precision release of this model.** The ladder is built from > upstream's highest rung, `UD-Q8_K_XL` (~8.6 bpw), which is therefore **both** the requantization > source for every file here **and** the reference against which all KLD figures are measured. Two > consequences: every quality number is relative to *that file* rather than to true full precision, > and an unknown fraction of each divergence is inherited from it. Comparisons *between* files remain > valid — they share one reference — and the same caveat applies to our Qwen TTQ ladder.

Text generationlicense:mit
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/31 05:07:55
OVERVIEW

Model overview

**TTQ** (TokenTinkerer Quant) is a ten-rung GGUF ladder built from peculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-GGUF-MTP, from 3.34 bpw to 6.64 bpw. Every rung is **tensor-for-tensor the same shape** as our published Qwen3.6-35B-A3B TTQ ladder — the same ten ftypes in the same places on 733 body tensors — with the model's grafted MTP head carried at the precision upstream ships it. Every claim below is a measurement, not an estimate. > ⚠️ **This is a quant of an abliterated (uncensored) model.** It inherits CyberTiel's behaviour and > its usage warnings: it will not refuse, and with tool access it can do real harm. Read > the base model card > before running it, and sandbox it at the OS level. > **Source caveat — there is no full-precision release of this model.** The ladder is built from > upstream's highest rung, `UD-Q8_K_XL` (~8.6 bpw), which is therefore **both** the requantization > source for every file here **and** the reference against which all KLD figures are measured. Two > consequences: every quality number is relative to *that file* rather than to true full precision, > and an unknown fraction of each divergence is inherited from it. Comparisons *between* files remain > valid — they share one reference — and the same caveat applies to our Qwen TTQ ladder.

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?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

Are these real-time billing prices?

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Sources & traceability

许可证:mit。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。