Running Inkling-Small on Dual NVIDIA DGX Spark with 1M Context

X postMiaAnnouncement

Mia (@MiaAI_lab) reports running Inkling-Small across two NVIDIA DGX Spark systems with a 1M token context window using SGLang and dspark speculative drafts.

Key points

  1. Inkling-Small runs on two NVIDIA DGX Spark units with 1M context.
  2. The setup utilises SGLang combined with dspark speculative drafts.
  3. Achieved throughput is approximately 34 tok/s in a single stream and around 79 tok/s across six concurrent sessions.
  4. Unlike the text-only DeepSeek V4 Flash, Inkling-Small supports text, images, audio, and video.

Why it matters

High-throughput serving of long-context multimodal models on accessible hardware is critical for real-world deployments, and speculative decoding methods are key to improving inference speeds.

Analysis

The post highlights benchmarks for Inkling-Small at a 1M context length on dual DGX Spark systems using SGLang. The author specifically contrasts Inkling-Small with DeepSeek V4 Flash by pointing out its multimodal capabilities spanning images, audio, and video alongside text.

Original post

Mia

@MiaAI_lab · 2 August 2026

Run Inkling-Small on 2x @NVIDIAAI DGX Spark with 1M context ✨ - SGLang with dspark speculative drafts ~34 tok/s (single stream) ~79 tok/s (6 concurrent sessions) Unlike DeepSeek V4 Flash which supports only text, Inkling-Small also supports images, audio, and video. Special

129 likes13 replies106 bookmarks9.5k views

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Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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