MODEL PROFILE

Qwen3.6-35B-A3B-heretic-NVFP4

AEON-7 · Qwen3.6-35B-A3B-heretic-NVFP4

> ✅ **Validated on the unified AEON vLLM Ultimate image `ghcr.io/aeon-7/aeon-vllm-ultimate:latest`** (= `:2026-06-18-v0.23.0-dflashfix`; rollback `:2026-06-11-pr41703`) — vLLM 0.23.0 built from source for GB10 / sm_121a + the AEON DFlash stack. Loads + serves cleanly (compressed-tensors MoE) — **including working multimodal image understanding** (a vision tensor-prefix bug was fixed 2026-06-18 — see the **Vision fix** section below) — and with DFlash `num_speculative_tokens: 11` now scales to **c=64** with **up to ~740 tok/s aggregate** and **no concurrency crash**. This single image supersedes the older `vllm-spark-omni-q36:v1.2` container. **Recommended container base.** > **🚀 PRODUCTION DEPLOYMENT GUIDE: github.com/AEON-7/Qwen3.6-35B-A3B-heretic-NVFP4-DFlash** > > The GitHub repo is the **definitive turn-key setup** for DGX Spark — end-to-end > deployment guide, validated OpenClaw config, and a concurrency-sweep benchmark harness. > > - Image: `ghcr.io/aeon-7/aeon-vllm-ultimate:latest` (vLLM 0.23.0 source-built for sm_121a + the AEON speculative-decoding stack — see What we fixed for the DGX Spark) > - Pairs with `z-lab/Qwen3.6-35B-A3B-DFlash` drafter (must be **post 2026-04-19** revision) > - **Production-stable** under sustained chat load and concurrent agent fleets up to c=64 on DGX Spark v1 of this checkpoint had `model.language_model.layers.X.*` keys remapped to `model.layers.X.*` so vLLM's text-only `Qwen3_5MoeForCausalLM` loader would pick them up. That layout was unstable in production — intermittent NaN/crash in the prefix-strip codepath during real chat sessions.

Visual QAmultimodalreasoninglicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/11/2 19:15:58
OVERVIEW

Model overview

> ✅ **Validated on the unified AEON vLLM Ultimate image `ghcr.io/aeon-7/aeon-vllm-ultimate:latest`** (= `:2026-06-18-v0.23.0-dflashfix`; rollback `:2026-06-11-pr41703`) — vLLM 0.23.0 built from source for GB10 / sm_121a + the AEON DFlash stack. Loads + serves cleanly (compressed-tensors MoE) — **including working multimodal image understanding** (a vision tensor-prefix bug was fixed 2026-06-18 — see the **Vision fix** section below) — and with DFlash `num_speculative_tokens: 11` now scales to **c=64** with **up to ~740 tok/s aggregate** and **no concurrency crash**. This single image supersedes the older `vllm-spark-omni-q36:v1.2` container. **Recommended container base.** > **🚀 PRODUCTION DEPLOYMENT GUIDE: github.com/AEON-7/Qwen3.6-35B-A3B-heretic-NVFP4-DFlash** > > The GitHub repo is the **definitive turn-key setup** for DGX Spark — end-to-end > deployment guide, validated OpenClaw config, and a concurrency-sweep benchmark harness. > > - Image: `ghcr.io/aeon-7/aeon-vllm-ultimate:latest` (vLLM 0.23.0 source-built for sm_121a + the AEON speculative-decoding stack — see What we fixed for the DGX Spark) > - Pairs with `z-lab/Qwen3.6-35B-A3B-DFlash` drafter (must be **post 2026-04-19** revision) > - **Production-stable** under sustained chat load and concurrent agent fleets up to c=64 on DGX Spark v1 of this checkpoint had `model.language_model.layers.X.*` keys remapped to `model.layers.X.*` so vLLM's text-only `Qwen3_5MoeForCausalLM` loader would pick them up. That layout was unstable in production — intermittent NaN/crash in the prefix-strip codepath during real chat sessions.

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.

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Estimate monthly base token costs

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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。

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。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。