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Life & fun · alternatives · 2026

24 alternatives to Capy-flash – a 125B MoE model on two 16 GB consumer GPUs

Qwen3.8-Flash-Next (MoE, NVFP4) and Qwen3.8-27B on two 16 GB consumer GPUs: two-GPU tensor parallel, experts offloaded to CPU. Formerly ninfer-tp2. - ValerioDolci/capy-flash

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.

  1. 1
    Qwen3.8-Flash-Nextfree tier▲108

    The open-weight preview of Qwen4

    Aug 2026 · qwen.ai · its alternatives →

  2. 2

    Contribute to Mega4alik/ollm development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  3. 3

    I built slotstream, a way to run Qwen3.8-Flash-Next 4-bit on a low-memory mac starting from 16GB, a 125B parameter model that would need 100GB+ memory/RAM, thanks to expert-offloading/ssd-streaming. Easy to install/update, and mac-native using MLX and Swift. It ships with auto-mode, which makes a good tradeoff between memory usage and speed. I'll be implementing and porting the MTP module for speculative decoding next Local models really are the future of computing!

    Sep 2026 · github.com · its alternatives →

  4. 4

    Ultra-fast 309B MoE model for coding & agents

    Dec 2025 · mimo.xiaomi.com · its alternatives →

  5. 5

    Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…

    2023 · github.com · its alternatives →

  6. 6

    Last week was big for open source LLMs. We got: - Qwen 2.5 VL (72b and 32b) - Gemma-3 (27b) - DeepSeek-v3-0324 And a couple weeks ago we got the new mistral-ocr model. We updated our OCR benchmark to include the new models. We evaluated 1,000 documents for JSON extraction accuracy. Major takeaways: - Qwen 2.5 VL (72b and 32b) are by far the most impressive. Both landed right around 75% accuracy (equivalent to GPT-4o’s performance). Qwen 72b was only 0.4% above 32b. Within the margin of error. - Both Qwen models passed mistral-ocr (72.2%), which is specifically trained for OCR. - Gemma-3…

    2025 · github.com · its alternatives →

  7. 7

    I found that duplicating a specific block of 7 middle layers in Qwen2-72B, without modifying any weights, improved performance across all Open LLM Leaderboard benchmarks and took #1. As of 2026, the top 4 models on that leaderboard are still descendants. The weird finding: single-layer duplication does nothing. Too few layers, nothing. Too many, it gets worse. Only circuit-sized blocks of ~7 layers work. This suggests pretraining carves out discrete functional circuits in the layer stack that only work when preserved whole. The whole thing was developed on 2x RTX 4090s in my basement. I'm…

    Mar 2026 · dnhkng.github.io · its alternatives →

  8. 8
    Wan 2.2▲208

    The first open MoE model for AI video generation

    2025 · wan.video · its alternatives →

  9. 9MP
  10. 10

    Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. - MakazhanAlpamys/Soup

    Aug 2026 · github.com · its alternatives →

  11. 11

    Powers faster, efficient reasoning for long-running agents

    Jun 2026 · developer.nvidia.com · its alternatives →

  12. 12

    The open sparse MoE model for agentic coding

    Apr 2026 · qwen.ai · its alternatives →

  13. 13

    1.6T MoE trained entirely on AI ASICs

    Jul 2026 · longcat.chat · its alternatives →

  14. 14

    Pick hardware and a model, and feel the real speed of a local LLM before you buy. Simulates tokens/sec and time-to-first-token from verified benchmarks for GPUs, Macs, and more.

    7d ago · llmspeed.dev · its alternatives →

  15. 15

    Metal-first MoE inference for Apple Silicon with bounded SSD expert streaming and local OpenAI Chat, Responses, and Anthropic Messages endpoints. - hebrus-labs/hebrus

    Jul 2026 · github.com · its alternatives →

  16. 16

    Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month

    2023 · netmind.ai · its alternatives →

  17. 17

    The end-to-end model powering multimodal chat

    2025 · github.com · its alternatives →

  18. 18

    Insights on GPU and AI infrastructure from Arc Compute. Read hardware deep-dives, deployment playbooks, and analysis of where the AI compute market is heading.

    2021 · arccompute.com · its alternatives →

  19. 19TC

    Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…

    2022 · tensordock.com · its alternatives →

  20. 20
    Unsloth▲241

    Finetune LLMs 2x faster, 80% less memory

    2025 · unsloth.ai · its alternatives →

  21. 21

    Hey HN, we wanted to share our repo where we fine-tuned Llama 3.1 on Google TPUs. We’re building AI infra to fine-tune and serve LLMs on non-NVIDIA GPUs (TPUs, Trainium, AMD GPUs). The problem: Right now, 90% of LLM workloads run on NVIDIA GPUs, but there are equally powerful and more cost-effective alternatives out there. For example, training and serving Llama 3.1 on Google TPUs is about 30% cheaper than NVIDIA GPUs. But developer tooling for non-NVIDIA chipsets is lacking. We felt this pain ourselves. We initially tried using PyTorch XLA to train Llama 3.1 on TPUs, but it was rough: xla…

    2024 · github.com · its alternatives →

  22. 22

    Highly efficient mixture-of-expert (MoE) model from Alibaba

    2024 · huggingface.co · its alternatives →

  23. 23

    Large language model series developed by Alibaba Cloud

    2025 · qwenlm.github.io · its alternatives →

  24. 24
    Soup CLI▲107

    Fine-tune an 8B LLM on a 4 GB laptop GPU

    Aug 2026 · trysoup.dev · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →