validated intel arc recipes · text, vision, and video

Battlemage inference & video recipes.

Six validated LLM model families on llama.cpp SYCL and vLLM XPU, plus MiniMax H3 text-to-video on ComfyUI. Exact image digests, required patches, and verifiable execution recipes.

inference cookbook · text & vision

Intel Arc Pro B70 inference cookbook

Six model families, one page per family, each pinned to its own container digest and patch list: Qwen3.8-27B, Qwen3.6-35B-A3B, Qwen3.6-27B, Nemotron-3.5-Lightning, Ornith-1.5-35B-A3B, and Muse-Glimmer-30B.

videogen cookbook · video generation

Intel Arc Pro B70 videogen cookbook

MiniMax H3 FL2VA text-to-video on ComfyUI 0.33.0 with PyTorch 2.13.0+xpu. Six weight files (~40 GiB), a two-card role split (UNet+VAE on GPU0, CLIP on GPU1), and single-card CPU-CLIP fallback.

text & vision recipes

Six validated model recipes.

Alibaba · Qwen VLLM XPU · DENSE 27B · THE LIVING RECIPE

Qwen3.8-27B GPTQ-INT4 + MTP4

quantized on the B70 with gptqmodel 7.3.2

Tested on 1× B70 (32GB)

106.7 tok/s C1 (n=5, cache on) · C5 127.4 Σ-streams

The most-served model on this host. Draft-INT4 overlay lifts the cache-off cell to 112.7; concurrent serving via mixed-split v5 reaches C32 224.2 on short prompts. Also includes Windows 11 standalone kits.

Stack & configuration
Image: vllm/vllm-openai-xpu@sha256:f01e24f6… · vLLM 0.27.2rc1.dev77
Artifact: SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16 (~18.2 GiB)
Context: 100,000 default; 131,072 loads at util 0.88 with fp8 KV
Patches: mtp_nightly + mtp_boundary (required)
Alibaba · Qwen VLLM XPU · MOE 35B (3B ACTIVE)

Qwen3.6-35B-A3B Native MTP 1/2/4

MTP-preserved community GPTQ, full 128K window

Tested on 1× B70 (32GB)

170.9 tok/s MTP4 (p512/g128, n=5) · 101.6 tok/s at 128K

MoE decode reads only ~3 GB of active experts per token, self-limiting to ~140 W. Runs at 150 W cap with identical speed and 80 W less heat. MTP2 beats MTP4 deep in context.

Stack & configuration
Image: vllm/vllm-openai-xpu@sha256:2c427ef4… · vLLM 0.26.1rc1.dev457
Artifact: llmfan46/Qwen3.6-35B-A3B-uncensored-heretic-Native-MTP-Preserved-GPTQ-Int4
Context: 131,072 · scheduler 8,192 · util 0.85 · fp16 KV
Patches: mtp_nightly then mtp_boundary
Alibaba · Qwen VLLM XPU · DENSE 27B · FP8 KV

Qwen3.6-27B Dense + mandatory fp8 KV

MTP-preserved community GPTQ, heretic-v2 base

Tested on 1× B70 (32GB)

69.3 tok/s MTP4 · 47.6 tok/s held at full 128K

FP16 KV requires ~9.5 GiB at 128K and fails to fit; fp8 halves requirement. In 32K document sessions, follow-up TTFT drops from 38.2 s to 4.1–4.5 s on 91% prefix hits.

Stack & configuration
Image: 2c427ef4 digest · vLLM 0.26.1rc1.dev457
Artifact: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved-GPTQ-Int4
Context: 131,072 ceiling · util 0.88 for MTP4
Power: 180 W sustained sweet spot
NVIDIA VLLM XPU · MAMBA2 + LATENTMOE (3B ACTIVE)

Nemotron-3.5-Lightning DFlash n=7

GPTQ-INT4 G64 target + NVFP4→BF16 DFlash draft

Tested on 1× B70 (32GB)

186.6 tok/s C1 (p2048/g128, n=5, accept 56.5%)

Native MTP accepts 0% on this stack; converted DFlash draft delivers 1.81× speedup over matched control. Capacity run completed 119,904 tokens at 120K limit.

Stack & configuration
Image: vllm/vllm-openai-xpu@sha256:1da0a954… · vLLM 0.26.1rc1.dev668
Artifact: SergiioB/Nemotron-3.5-Lightning-30B-A3B-GPTQ-Int4-sym-G64-BF16
Context: 120,000 · util 0.88 with fp16 KV
Patches: Upstreamed fixes vllm#52159 and vllm-xpu-kernels#524
Arcee AI VLLM XPU · MOE 35B (3B ACTIVE)

Ornith-1.5-35B-A3B MTP4 170.8 tok/s

Native-MTP GPTQ-INT4, full 131,072 context

Tested on 1× B70 (32GB)

170.8 tok/s MTP4 (p512/g128) · identical to Qwen3.6 MoE

Confirms architectural identity to Qwen3.6-35B-A3B under vLLM XPU MTP speculative decoding. Full 128K context capacity demonstrated on real Battlemage silicon.

Stack & configuration
Image: 2c427ef4 digest · vLLM 0.26.1rc1.dev457
Artifact: SergiioB/Ornith-1.5-35B-A3B-Native-MTP-GPTQ-Int4-sym-G128-BF16
Context: 131,072 · scheduler 8,192 · util 0.85
Patches: Same MTP suite as Qwen3.6 MoE
Muse LLAMA.CPP SYCL · GGUF VISION + TEXT

Muse-Glimmer-30B GGUF Q4_K_M

Multimodal vision + 128K context on llama.cpp SYCL

Tested on 1× B70 (32GB)

42.8 tok/s decode · 3,240 tok/s pp512 · flash attention

Carries GGUF workflows on SYCL. Flash attention with q8_0 key cache and q4_1 value cache delivers high-speed multimodal inference at 128K context window.

Stack & configuration
Build: llama.cpp SYCL (DPC++ 2024.2.1) with -DGGML_SYCL_F16=ON
Artifact: Muse-Glimmer-30B-Q4_K_M.gguf
KV Cache Policy: -ctk q8_0 -ctv q4_1 -fa 1 (flash attention mandatory)