Blackfrost-AI/DeepSeek-V4.1-Flash-DERISKED-FP8

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🤗 Hugging Face 来源image-text-to-textmit763B 参数765 GBsafetensors✓ 48 个校验和今天更新
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DeepSeek V4.1 Flash DERISKED FP8

Blackfrost Research · multimodal reasoning · 1M context · FP8

Built by Blackfrost Research · Las Vegas, Nevada

PRIVATE EVALUATION CHECKPOINT. Access is limited to approved Blackfrost Research partners while validation is in progress.

Model

This repository contains a complete, directly loadable FP8 checkpoint derived from DeepSeek V4.1 Flash. It does not require an adapter or a second model repository at inference time.

The upstream multimodal architecture is preserved, including vision, Engram conditional memory, CSA2 attention and the in-checkpoint DSpark draft components. The checkpoint uses the native DeepseekV41ForCausalLM architecture and DeepSeek V4.1 prompt encoder.

Model ID Blackfrost-Research/DeepSeek-V4.1-Flash-DERISKED-FP8
Base deepseek-ai/DeepSeek-V4.1-Flash
Architecture DeepseekV41ForCausalLM
Format FP8 safetensors, 48 shards
Modalities Text and vision
Context 1,048,576 tokens
Speculative decoding DSpark, 5 draft tokens in the validated profile
Validated hardware 8× NVIDIA B300, TP8 with expert parallelism
Serving API OpenAI-compatible vLLM

Recommended generation settings

Setting Value
Temperature 1.0
Top-p 0.95
Reasoning enabled
Reasoning effort 100

Use the native DeepSeek V4.1 tokenizer and reasoning parser. Current vLLM returns hidden reasoning in the structured reasoning field while keeping the final response in content. Client interfaces should display content as the assistant answer.

Deployment

The deployment-kit/vllm directory provides:

  • a Docker launcher using the latest CUDA vLLM nightly;
  • a native vLLM launcher;
  • the validated TP8 and expert-parallel settings;
  • DSpark speculative decoding;
  • health and reasoning-parser verification.

Quick start:

export HF_TOKEN=hf_your_read_token
./deployment-kit/vllm/serve-docker.sh

The OpenAI-compatible endpoint starts at http://127.0.0.1:18000/v1 by default.

People using an automation agent should give it AGENTS.md before deployment. That file contains the required model, parser and verification invariants.

Evaluation

Bare 450 refusal benchmark

Completed 450/450 prompts with 0 request errors in 1,014 seconds. Phase 1 is the refusal-substring screen. Phase 2 reports confirmed true holds from the 19-row review pool.

Dataset Phase-1 substring Phase-2 true
AdvBench 1/150 1
StrongREJECT 3/150 2
XSTest 8/150 2
Harmful: AdvBench + StrongREJECT 4/300 3/300
XSTest safe subset 2/75 0/75
Incoherent 7 box-drawing false positives 0
All 12/450 5/450

The behavior floor remained intact in this run: all 450 prompts completed, the seven box-drawing substring hits were false positives, and final incoherent output was zero.

Additional partner capability and refusal results will be added with their runtime, hardware, prompt settings and sample counts after review.

Intended use

  • Controlled research and partner evaluation
  • Long-context reasoning and code analysis
  • Multimodal document and image analysis
  • Authorized security research and defensive engineering

Operators are responsible for access control, workload authorization and review of generated output.

Limitations

  • This is a research checkpoint under active evaluation.
  • Output quality depends on the DeepSeek V4.1 prompt encoder and generation settings.
  • A generic DeepSeek V4 tokenizer or reasoning parser can produce malformed prompts or expose reasoning delimiters in assistant content.
  • Hardware profiles other than the validated TP8 configuration require independent memory and throughput testing.

License and attribution

This checkpoint is derived from DeepSeek V4.1 Flash and is distributed under the upstream MIT license included in this repository. Review the upstream model card and technical report for architecture details.