Qwen3.8-Flash-Next — Blackfrost NVFP4

Quantized Blackfrost Qwen3.8-Flash-Next · routed-expert NVFP4 · FP8 PLE

Built by Blackfrost

Weights published

This repository contains the Blackfrost NVFP4 checkpoint as 206 indexed safetensors shards with its verified configuration, tokenizer, and Qwentium chat template.

Blackfrost's proprietary modification process and associated research artifacts are not included in this repository.

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Why this model exists

Qwen3.8-Flash-Next is Qwen's experimental preview of the architecture leading into Qwen4. It combines a large sparse model with low active compute, native multimodality, hybrid attention, four gated residual branches, n-gram embeddings, and multi-token prediction.

This checkpoint is the reduced-memory NVFP4 release of the Blackfrost BF16 research edition. It preserves the parent model's weight-level refusal-surface modification and Qwentium operational chat template while quantizing the routed-expert projections for efficient serving on supported NVIDIA hardware.

It is not a fine-tune, merge, LoRA, or pruned model.

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Specifications

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Lineage

Blackfrost's proprietary modification process and associated research artifacts are not included in this repository.

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Artifact verification

The published checkpoint passed structural and serving verification before release:

• all 206 weight shards are indexed and readable;
• routed-expert NVFP4 values were rebuilt from the selected BF16 parent and passed deterministic requantization checks;
• non-target model state remains exact to the compatible quantized reference;
• configuration, tokenizer, processor, and Qwentium template files are complete; and
• the checkpoint loaded and completed deterministic generation on the validated serving shape.

These are artifact-integrity checks. They are not capability benchmarks or safety proofs.

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Behavioral evaluation

No behavioral score is published for this quantized checkpoint until its evaluation has completed manual adjudication. Results from the BF16 parent must not be attributed to this NVFP4 artifact.

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Qwentium chat template

The default Qwen chat template includes the Blackfrost Qwentium operational prompt. The template preserves Qwen's message structure, tool descriptions, multimodal inputs, reasoning controls, and caller-supplied system context.

The embedded prompt is a behavioral instruction, not an authorization system or security boundary. If a serving harness supplies a replacement chat template, it may bypass the embedded prompt. Record the exact template and template arguments in every evaluation report.

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Deployment

The command below records the SGLang configuration validated for this published checkpoint.

docker run --rm --gpus all \
  --network host --ipc host --shm-size 64g \
  lmsysorg/sglang@sha256:12d3392bdc8be8d35e9a95f191df6aef99c5114bdbefd41bfdc7e760e6d25ec1 \
  serve \
    --model-path Blackfrost-AI/Qwen3.8-Flash-Next-DERISKED-NVFP4 \
    --served-model-name Qwen3.8-Flash-Next-Blackfrost-NVFP4 \
    --host 0.0.0.0 \
    --port 8000 \
    --tp 2 \
    --quantization modelopt_fp4 \
    --fp4-gemm-backend flashinfer_cutlass \
    --page-size 64 \
    --mamba-radix-cache-strategy extra_buffer \
    --mamba-track-interval 64 \
    --chunked-prefill-size 4096 \
    --max-running-requests 36 \
    --context-length 262144 \
    --mem-fraction-static 0.80 \
    --allow-auto-truncate \
    --linear-attn-prefill-backend flashinfer \
    --linear-attn-decode-backend flashinfer \
    --mamba-ssm-dtype bfloat16 \
    --reasoning-parser auto \
    --sampling-defaults model

The model's recommended sampling defaults are temperature 1.0, top-p 0.95, and top-k 20.

OpenAI-compatible health and generation checks:

curl http://127.0.0.1:8000/health

curl http://127.0.0.1:8000/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "Qwen3.8-Flash-Next-Blackfrost-NVFP4",
    "messages": [{"role": "user", "content": "Return exactly: READY"}],
    "temperature": 0,
    "max_tokens": 64
  }'

The validated configuration uses two B200 GPUs and BF16 KV cache. Increase context or concurrency only after measuring memory headroom for the actual workload, modalities, and cache settings.

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Security and deployment responsibility

This checkpoint has a deliberately reduced refusal surface inherited from its BF16 parent. Open weights do not provide an application policy, authorization system, audit trail, sandbox, or access-control boundary. Operators remain responsible for enforcing those controls outside the model.

For production or shared use, Blackfrost recommends authenticated inference endpoints, independent request and tool-execution logging, least-privilege credentials, sandboxed code and file access, and explicit human approval for irreversible actions.

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License and disclaimer

This derivative remains subject to the Qwen Community License 1.0 shipped with the upstream Qwen3.8-Flash-Next release. Review the upstream license before commercial deployment, especially its separate-license condition for Model-as-a-Service and AI Work Assistant businesses.

Refusal behavior has been deliberately modified at the weight level in the BF16 parent. This is not a safety-stock checkpoint and must not be deployed, marketed, or evaluated as one.

No warranty of any kind. The checkpoint is provided "as is." Nothing here guarantees that any input will be accepted or refused, that every upstream capability is retained, or that any category of output is unreachable. Measurements describe only the exact artifacts, templates, samplers, serving engines, and review criteria under which they were produced.

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Contact Blackfrost

@Blackfrost_AI on X

For reproducible bug reports, include the serving engine and image digest, GPU SKU, driver version, complete launch flags, prompt template, sampler settings, and observed failure mode.

Blackfrost Softwares Corp.
Frontier model engineering

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Qwen3.8-Flash-Next — Blackfrost NVFP4 · © 2026 Blackfrost Softwares Corp.
@Blackfrost_AI