MODEL PROFILE

TenEros_Max_optimized_learned

LokkenJP · TenEros_Max_optimized_learned

Two accepted weight-only releases are available for the H3 Beta7 transformer from TenStrip/10Eros-Max. Both retain the source's embedded eight-step Turbo. **HQ (18.69 GB) remains the recommended choice for quality**, using learned W6 g16 and INT8 ConvRot weights. **Compact (14.65 GB)** adds W4 g16 to reduce the weight footprint for setups with less available memory. Both passed mechanical validation and operator ComfyUI acceptance on **2026-10-28**. For compact, the operator reports slightly lower quality than HQ while holding up well, with lower observed memory use. These are qualitative observations without measured VRAM savings or a controlled quality score. The older Beta6 compact remains a separate source release. Beta7 has the standard H3 tensor layout without compression-gate tensors. The upstream author describes its merge as MLP-focused, preserving base attention/reference behavior, and recommends Euler/simple or ER-SDE/SGM_uniform for its Turbo sampling. See the upstream source notes for its recipe, workflow settings and known limitations.

license:other
Context windowNot disclosed
Input → Output待核验 → 待核验
Model weightsNot verified
Profile updated2026/11/2 19:16:28
OVERVIEW

Model overview

Two accepted weight-only releases are available for the H3 Beta7 transformer from TenStrip/10Eros-Max. Both retain the source's embedded eight-step Turbo. **HQ (18.69 GB) remains the recommended choice for quality**, using learned W6 g16 and INT8 ConvRot weights. **Compact (14.65 GB)** adds W4 g16 to reduce the weight footprint for setups with less available memory. Both passed mechanical validation and operator ComfyUI acceptance on **2026-10-28**. For compact, the operator reports slightly lower quality than HQ while holding up well, with lower observed memory use. These are qualitative observations without measured VRAM savings or a controlled quality score. The older Beta6 compact remains a separate source release. Beta7 has the standard H3 tensor layout without compression-gate tensors. The upstream author describes its merge as MLP-focused, preserving base attention/reference behavior, and recommends Euler/simple or ER-SDE/SGM_uniform for its Turbo sampling. See the upstream source notes for its recipe, workflow settings and known limitations.

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.

Source / channelInputOutputBilling unitCollected at
No verified prices yet. Check the source channel.

Estimate monthly base token costs

—

Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

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。

View full indexed rankings →

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?

These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.

Sources & traceability

许可证:other。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。