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Piecrust/Spike-9B-MLX

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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Spike-9B · MLX (4-bit)

Spike is the assistant in the Spike AI iOS app. This is the largest Spike tool model — 4-bit MLX for Apple silicon, served via mlx-swift / mlx-vlm. 📱 Get it on the App Store: https://apps.apple.com/app/spike-ai/id6749781844

A LoRA fine-tune of Qwen/Qwen3.5-9B (a vision-language model), specialized for Spike's tool-calling — reminders, calendar, Apple Home, maps, web, files, code, and the SSH/agent toolset — plus vision (flyer → calendar, note → reminder, receipt → answer), while staying a natural conversationalist. English + German. Tool grammar: tool:<name> {json}.

Files

4-bit MLX weights (model.safetensors, ≈5.8 GB) + tokenizer, processor, chat template. Load with mlx-swift / mlx-vlm on Apple silicon.

Qwen3.5 is a new hybrid (linear-attention + full-attention) architecture; a text-only GGUF build is also available for llama.cpp servers. This is a server-class 9B — it targets Macs / workstations, not phones (the on-device app ships the 2B / 4B builds).

Eval — Spike harness (base Qwen3.5-9B → Spike-9B)

Metric	Base	Spike-9B
Tool calls · thinking-off	52.0%	99.8%
Tool calls · thinking-on	—	99.8%
Vision (image → tool / answer)	72.5%	100%
Normal-chat tool-leak (lower=better)	1.6%	0%

Trained text+thinking+German, then a vision-replay stage, then a conversation-repair stage (distilled base-model chat + contrastive tool/vision replay) so it keeps enable_thinking reasoning and vision, tool-calls at 99.8%, and does not hijack casual chat into tool calls.

Usage notes

—Trained on Spike's compact system prompt; use that exact prompt for best results.
—Supports optional reasoning via the enable_thinking chat-template kwarg.
—Vision: pass an image with the user turn; the model reads it and answers or calls a tool.
—Tool calls are plain text tool:<name> {json} — one per turn.

License

Derivative of Qwen3.5-9B under the Apache 2.0 License.