NeuralDaredevil 8B is an 8 billion parameter language model based on the LLaMA architecture, designed for robust text generation tasks. It excels in generating coherent and contextually rich text, making it suitable for applications like creative writing, content generation, and even basic conversational agents. With a context length of 8192 tokens, it can handle longer sequences of text, which is particularly useful for tasks requiring a deep understanding of context, such as summarization or document analysis. The model is available in multiple quantizations, including BF16, Q4_K_M, and Q8_0, which allows for efficient deployment on a variety of hardware setups.
In its size class, NeuralDaredevil 8B holds its own, offering a balance between performance and resource efficiency. While it may not outperform the largest models in terms of raw capabilities, it provides a significant advantage in terms of practicality and accessibility. Users with mid-range GPUs, such as those with 5.1 to 16.5 GB of VRAM, can run this model without excessive computational strain. This makes it an excellent choice for developers, hobbyists, and small teams who need a powerful yet manageable text generation tool. Ideal use cases include content creators looking to generate high-quality text quickly, researchers experimenting with NLP, and businesses needing to automate text-based tasks without investing in high-end hardware.
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| BF16 | 16 | 16 GB | 16.5 GB | 17 GB | 100% |
| Q4_K_M | 4.5 | 4.583 GB | 5.08 GB | 5.58 GB | 85% |
| Q8_0 | 8 | 7.954 GB | 8.45 GB | 8.95 GB | 98% |
Context window & KV cache
Adds 1.00 GB to VRAMLong chats and RAG inputs cost real memory. Drag to see how 32K vs 128K context shifts your grade.
Model native max: 8K tokens. KV-cache estimate is approximate (±30 %); real usage depends on attention layout.
How to run NeuralDaredevil 8B (abliterated)
Pick a runtime — copy & paste. Commands are pre-filled with this model’s repo.
GUI. Browse → download → chat. MLX on Apple Silicon.
LM Studio home →- 1
Open LM Studio
Go to the 🔍 Search tab.
- 2
Search for
bartowski/NeuralDaredevil-8B-abliterated-GGUF - 3
Download
Pick the Q4_K_M quant — best balance of size vs. quality.
- 4
Chat
Hit ▶ Load Model and start chatting. Toggle 'Local Server' to expose an OpenAI-compatible API on :1234.
Community benchmarks
Real tokens/sec reports from people running NeuralDaredevil 8B (abliterated) on actual hardware.
No community runs yet for this model. Be the first to submit your numbers.
Self-host serving plan
Want to host NeuralDaredevil 8B (abliterated)for many users? Or run it on a card that’s technically too small? Slide the knobs.
VRAM needed
6.3 GB
5.1 GB weights + 0.7 GB KV
Aggregate tok/s
31
across 1 user
Per-user tok/s
31
8 B dense
✅ Fits in 24 GB VRAM with 17.7 GB headroom. Pure-GPU inference — full speed.
Throughput is a sub-linear estimate: doubling users adds ~70 % of single-user TPS until ~8, then plateaus on memory bandwidth. MoE models scale concurrency much better because each user activates a different subset of experts.
See It In Action
Real model outputs generated via RunThisModel.com — watch responses stream in real time.
Outputs generated by real AI models via RunThisModel.com. Generation speed shown is from cloud inference. Local speeds vary by hardware — check your device.
how much VRAM do I need to run NeuralDaredevil 8B (abliterated)?
NeuralDaredevil 8B (abliterated) requires 5.08 GB VRAM minimum with BF16 quantization. For full precision you need 16.5 GB.
which quant should I pick?
Q4_K_M is the best quality/VRAM balance — ~92% of FP16 quality at ~25% the footprint. Q8_0 is near-lossless if you have the headroom.
What GPU do I need to run NeuralDaredevil 8B (abliterated)?
To run NeuralDaredevil 8B (abliterated), you need a GPU with at least 5.1 GB of VRAM for the lowest quantization level, up to 16.5 GB for the highest. NVIDIA GPUs like the RTX 3060 or higher are recommended.
Is NeuralDaredevil 8B (abliterated) good for coding?
NeuralDaredevil 8B (abliterated) is well-suited for coding tasks due to its strong performance in generating code and understanding programming concepts, making it a valuable tool for developers.
NeuralDaredevil 8B (abliterated) vs Llama 3.1 8B?
NeuralDaredevil 8B (abliterated) offers better quality retention compared to Llama 3.1 8B, especially after the ablation and DPO recovery process, resulting in minimal regression from the official Instruct model.
Can I run NeuralDaredevil 8B (abliterated) on a Mac?
Yes, you can run NeuralDaredevil 8B (abliterated) on a Mac with an M1 or M2 chip, provided you have the necessary software and drivers installed to support GPU acceleration.
How much VRAM does NeuralDaredevil 8B (abliterated) need?
The VRAM requirement for NeuralDaredevil 8B (abliterated) ranges from 5.1 GB to 16.5 GB, depending on the quantization level used. Lower quantization levels require less VRAM but may impact performance.
Is NeuralDaredevil 8B (abliterated) censored?
NeuralDaredevil 8B (abliterated) is not explicitly censored, but it has been fine-tuned to minimize harmful outputs and adhere to ethical guidelines.
Is NeuralDaredevil 8B (abliterated) commercial-use allowed?
Yes, NeuralDaredevil 8B (abliterated) is licensed under the Llama 3 license, which allows for commercial use as long as you comply with the terms of the license.
NeuralDaredevil 8B (abliterated) context length?
NeuralDaredevil 8B (abliterated) supports a context length of 8192 tokens, allowing for longer and more complex inputs and outputs.
Does NeuralDaredevil 8B (abliterated) support function calling?
Yes, NeuralDaredevil 8B (abliterated) supports function calling, enabling it to interact with external systems and APIs effectively.
NeuralDaredevil 8B (abliterated) quantization options?
NeuralDaredevil 8B (abliterated) supports various quantization options, including 4-bit, 8-bit, and 16-bit, allowing you to balance between performance and resource usage.
Can NeuralDaredevil 8B (abliterated) run on CPU?
While NeuralDaredevil 8B (abliterated) can run on a CPU, it will be significantly slower compared to running on a GPU. A high-end CPU is recommended for acceptable performance.
NeuralDaredevil 8B (abliterated) fine-tuning?
NeuralDaredevil 8B (abliterated) can be fine-tuned using frameworks like Hugging Face Transformers. Fine-tuning can improve its performance on specific tasks or domains.
NeuralDaredevil 8B (abliterated) system requirements?
To run NeuralDaredevil 8B (abliterated), you need a system with at least 16 GB of RAM, a modern CPU, and a GPU with 5.1 GB to 16.5 GB of VRAM, depending on the quantization level.
NeuralDaredevil 8B (abliterated) performance benchmark?
NeuralDaredevil 8B (abliterated) processes around 100-200 tokens per second on a high-end GPU like the RTX 3090, with lower performance on less powerful hardware.
NeuralDaredevil 8B (abliterated) for RAG?
NeuralDaredevil 8B (abliterated) can be used for Retrieval-Augmented Generation (RAG) tasks, enhancing its ability to generate contextually relevant responses by integrating external data sources.
NeuralDaredevil 8B (abliterated) for agents?
NeuralDaredevil 8B (abliterated) is suitable for creating conversational agents and chatbots, thanks to its strong language generation capabilities and support for function calling.
NeuralDaredevil 8B (abliterated) for coding vs general?
NeuralDaredevil 8B (abliterated) performs well in both coding and general language tasks, but it excels in coding due to its specialized training and strong code generation abilities.
NeuralDaredevil 8B (abliterated) vs ChatGPT?
NeuralDaredevil 8B (abliterated) offers similar capabilities to ChatGPT but with a focus on minimal regression from the official Instruct model and stronger performance in coding tasks.
NeuralDaredevil 8B (abliterated) download size?
The download size for NeuralDaredevil 8B (abliterated) varies depending on the quantization level, ranging from approximately 4 GB for 4-bit quantization to 16 GB for 16-bit quantization.
Best quant for NeuralDaredevil 8B (abliterated)?
The best quantization level for NeuralDaredevil 8B (abliterated) depends on your hardware. For most users, 8-bit quantization offers a good balance between performance and resource efficiency.