Instructions to use loopai-hq/Qwen3.6-35B-A3B-Pulsar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use loopai-hq/Qwen3.6-35B-A3B-Pulsar with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("loopai-hq/Qwen3.6-35B-A3B-Pulsar") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use loopai-hq/Qwen3.6-35B-A3B-Pulsar with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "loopai-hq/Qwen3.6-35B-A3B-Pulsar" --prompt "Once upon a time"
- Atomic Chat
Qwen3.6-35B-A3B-Pulsar
Qwen3.6-35B-A3B on a Mac at 264.3 tok/s, served by Pulsar.
Pulsar is a fork of Inco AI's open-source Splash engine. Qwen3.6-35B-A3B is a mixture-of-experts (MoE) model: 35B parameters in many small expert blocks, of which only about 3B work on each token, so it is fast for its size. This repository holds Inco AI's Splash package for it (the 4-bit model, its DFlash 2 draft model, the vision encoder and the tokenizer), unchanged, plus Pulsar's guesser token list. A model writes one token at a time; a token is a word or part of a word. A small guesser, the draft model, proposes the next few tokens and the full model checks every one before it keeps it, so you get the full model's answers, faster.
Speed
On an M5 Max (128 GB), greedy, measured on Inco AI's Splash package without the guesser list (2026-10-10):
- Pulsar 1.1.5 writes Qwen3.6-35B-A3B at 264.3 tokens per second (tok/s) on average across 13 prompts, from short chat to a 32K-token agent task.
- On the 32K-token agent prompt, Pulsar 1.1.6 writes 139.9 tok/s, 3.6% faster than 1.1.5's 135.1.
With the guesser token list, on the same Mac:
- Pulsar 1.1.7 writes 282.7 tok/s across the 13 prompts, 4.8% faster than 1.1.6's 269.7 (both with the guesser token list, greedy, 2026-10-10).
Since 2026-10-10 this package also ships Pulsar's guesser token list (draft/head-ranked.u32); answers are unchanged
(greedy, 12 prompts identical with and without it).
Installed before 2026-10-10? Pulsar keeps an installed model as it is. To pick up the list, remove the model link (the weights stay in the cache) and serve again; it downloads about 1 MB:
rm "$HOME/Library/Application Support/Splash/models/loopai-hq/Qwen3.6-35B-A3B-Pulsar"
./pulsar serve --model loopai-hq/Qwen3.6-35B-A3B-Pulsar
More numbers: BENCHMARKS.md.
Quick start
Apple silicon M3 or newer (measured on M5 Max), macOS 26.4 or later.
# Download pulsar-1.1.7-macos-arm64.tar.gz from https://github.com/loopai-hq/pulsar/releases/latest, then:
tar -xzf pulsar-1.1.7-macos-arm64.tar.gz && cd pulsar
./pulsar serve --model loopai-hq/Qwen3.6-35B-A3B-Pulsar
Open http://127.0.0.1:8000 to chat. The server speaks the OpenAI and Anthropic APIs, and ./pulsar opencode,
./pulsar claude or ./pulsar codex opens your coding agent already connected. More in the
README.
What's inside
target/ Qwen3.6-35B-A3B, 4-bit (8-bit expert routers) Inco AI's Splash package, unchanged
draft/ DFlash 2 draft model Inco AI's Splash package, unchanged
draft/head-ranked.u32 Pulsar's guesser token list Pulsar
vision/ bf16 vision encoder Inco AI's Splash package, unchanged
tokenizer/ tokenizer and chat template Inco AI's Splash package, unchanged
manifest.json size and SHA-256 of every package file Inco AI's, plus one record for the list
layout.json map of every packed file Inco AI's Splash package, unchanged
LICENSE Apache-2.0 Inco AI's, unchanged
NOTICE credits and what Pulsar changed Pulsar
provenance.json source repos, revisions and licenses Pulsar
SHA256SUMS SHA-256 of every file here Pulsar
The Splash package files are byte-for-byte copies of
incoai/Qwen3.6-35B-A3B-Splash at revision
0f4714b2db37b5f3c42a10de07281e74f88e4adc; manifest.json adds one record for the guesser list. Check every file with
shasum -a 256 -c SHA256SUMS.
Credits
- Qwen3.6-35B-A3B by the Qwen team, Apache-2.0.
- 4-bit conversion by mlx-community: mlx-community/Qwen3.6-35B-A3B-4bit, Apache-2.0.
- Splash and the DFlash 2 draft model by Inco AI: incoai/Qwen3.6-35B-A3B-Splash, incoai/Qwen3.6-35B-A3B-DFlash2 and the Splash engine, Apache-2.0. Thank you to the Splash team at Inco AI for the engine and the model packages Pulsar stands on.
- Pulsar and its guesser token list, Apache-2.0: github.com/loopai-hq/pulsar.
License
Apache-2.0, like every component above.