prabanta-dev / janas
git clone https://github.com/prabanta-dev/janas.git
v2026.10.18 · 2d ago
37 tok/s from Qwen3-Next-80B (48 GB) on a 32 GB laptop, 24 without drafts vs 2.8 for llama.cpp; reading 62 vs 16 tok/s. Faster than llama.cpp on all 13 models compared in Q4_K_M. LLMs bigger than your RAM, pure C, CPU or GPU.
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Star history starts 2026-10-20; the chart appears after the second daily snapshot.
LanguageC
LicenseGPL-3.0
Created2026-09-20 (1mo ago)
Last push2d ago
Watchers4
OwnerOrganization
GitHub topics
avx2ccpu-inferenceggufinference-enginelinuxllmlocal-llmmixture-of-expertsmoenvmequantizationqwen3simdspeculative-decodingvulkan
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README excerpt
# Janas **37 tok/s from Qwen3-Next-80B (a 48 GB model) on a laptop with 32 GB of memory, 24 without drafts, where llama.cpp manages 2.8; reading a prompt, 62 tok/s against 16.** Janas-LLM was faster than llama.cpp on every model compared on the same laptop (Debian 13 Linux, Intel Core Ultra 9 185H, its integrated Arc GPU, 32 GB, an NVMe SSD; 9-12 October 2026; the whole machine below): | Model | reading 1,024 tokens: Janas-LLM | llama.cpp | writing: Janas-LLM | llama.cpp | |---|---:|---:|---:|---:| | Qwen3-Next-80B-A3B (48.4 GB, more than the memory) | 62 tok/s | 16 tok/s | 24 tok/s | 2.8 tok/s | | Qwen3-Coder-Next (48.4 GB, more than the memory) | 66 tok/s | 14 tok/s | 22 tok/s | 2.2 tok/s | | Qwen3.6-35B-A3B | 104 tok/s | 79 tok/s | 19 tok/s | 12 tok/s | | Qwen3-30B-A3B | 135 tok/s | 122 tok/s | 32 tok/s | 15 tok/s | | Gemma-4-26B-A4B-it | 84 tok/s | 76 tok/s | 18 tok/s | 12 tok/s | | Qwen3.8-27B (dense, 17.6 GB) | 30.6 tok/s | 25.6 tok/s | 4.4 tok/s | 2.1 tok/s | | Gemma-4-12B-it | 65 tok/s | 46 tok/s | 9.9 tok/s | 7.1 tok/s | | Qwen3.5-9B | 111 tok/s | 78 tok/s | 14 tok/s | 8.7 tok/s | | Gemma-4-E4B-it | 122 tok/s | 109 tok/s | 20 tok/s | 15 tok/s | | Qwen3-4B | 193 tok/s | 164 tok/s | 27 tok/s | 18 tok/s | | Gemma-4-E2B-it | 191 tok/s | 150 tok/s | 38 tok/s | 19 tok/s | | Qwen3.5-2B | 441 tok/s | 323 tok/s | 52 tok/s | 28 tok/s | | Qwen3.5-0.8B | 799 tok/s | 519 tok/s | 109 tok/s | 32 tok/s | | Qwen3-0.6B | 939 tok/s | 670 tok/s | 130 tok/s | 45 tok/s | The same models from other hands, in the catalog beside them: | Model | reading 1,024 tokens: Janas-LLM | llama.cpp | writing: Janas-LLM | llama.cpp | |---|---:|---:|---:|---:| | Qwen3-30B-A3B, bartowski's Q4_K_M (importance matrix) | 131 tok/s | 122 tok/s | 32 tok/s | 16 tok/s | | Qwen3-30B-A3B, unsloth's UD-Q3_K_XL (3 bits) | 100 tok/s | **112 tok/s** | 36 tok/s | 11 tok/s | | Qwen3-4B, bartowski's Q4_K_M (importance matrix) | 191 tok/s | 160 tok/s | 26 tok/s | 18 tok/s | Qwen3.8-27B: llama.cpp measured on 12 October 2026 (`llama-bench -r 2`), Janas-LLM on 13 October (`janas-bench --prompt 1024 --gen 16`, two rounds), once its prompt went whole to the GPU in one submission: 30.6 tok/s, where it read 26.4 the day before and 18.7 before the GPU's tiles for the IQ4_XS, IQ3_S and IQ4_NL weights of unsloth's UD mix. One exception: the 3-bit Qwen3-30B reads a prompt slower than llama.cpp, since its Q3_K weights do not go to the GPU's fast prompt yet; it writes three times as fast. How they were measured, and the speeds with the drafts: What works now. On another machine the figures will be other ones: `janas-bench` measures yours. **Try it** on Linux x86-64 (Ubuntu 22.04, Debian 12 and later): [code] **Or on Windows** 10 (1903 or later) and 11, x86-64: download janas-windows-x86_64.zip, unpack it, and in a terminal in its `janas` folder run `.\janas-chat`. On the same laptop under Windows 11 (12 October 2026) Janas-LLM wrote as fast as on Linux (Qwen3-4B 25.6 tok/s, Qwen3-30B-A3B 34.2) and read