MODEL PROFILE

NVIDIA-Nemotron-3.5-Bolt-74B-A9B-Abliterated-24GB-GGUF

BoldingBuilds · NVIDIA-Nemotron-3.5-Bolt-74B-A9B-Abliterated-24GB-GGUF

An uncensored edit of **NVIDIA Nemotron-3.5-Bolt-74B-A9B**, a hybrid Mamba/MoE model, produced by editing NVIDIA's **shipped 24GB 2-bit GGUF** (nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF) **directly** — no BF16 requantize at any point. That matters for this model specifically. Bolt is a LatentMoE: every routed expert sums through one dense `ffn_latent_up` per layer, and the experts themselves are ~17GB of IQ2_XXS weights produced by NVIDIA's quantization-aware distillation. A conventional abliterate-then-requantize pipeline would throw that QAD work away. Instead the projection is applied in place and codes are re-picked under the **original block scales**, so at λ=0 the output file is byte-identical to the input by construction — which is the self-test the build gates on (verified: all edited tensors byte-identical at λ=0). The published file is the same length as NVIDIA's, 22,018,326,528 bytes. Bolt is multimodal, so the projector ships alongside. The edit touched only text-model tensors, so the projector is byte-for-byte NVIDIA's file; download both or vision silently does nothing.

Visual QAmultimodallicense:other
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/10/30 14:48:25
OVERVIEW

Model overview

An uncensored edit of **NVIDIA Nemotron-3.5-Bolt-74B-A9B**, a hybrid Mamba/MoE model, produced by editing NVIDIA's **shipped 24GB 2-bit GGUF** (nvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-24GB-GGUF) **directly** — no BF16 requantize at any point. That matters for this model specifically. Bolt is a LatentMoE: every routed expert sums through one dense `ffn_latent_up` per layer, and the experts themselves are ~17GB of IQ2_XXS weights produced by NVIDIA's quantization-aware distillation. A conventional abliterate-then-requantize pipeline would throw that QAD work away. Instead the projection is applied in place and codes are re-picked under the **original block scales**, so at λ=0 the output file is byte-identical to the input by construction — which is the self-test the build gates on (verified: all edited tensors byte-identical at λ=0). The published file is the same length as NVIDIA's, 22,018,326,528 bytes. Bolt is multimodal, so the projector ships alongside. The edit touched only text-model tensors, so the projector is byte-for-byte NVIDIA's file; download both or vision silently does nothing.

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。