--- title: Open-Weight Models | The Agentic AI Hub — daily.dev description: The models you can download, self-host, and fine-tune. As of July 2026. Two things to know: (1) "open weight" ≠ open source. canonical: https://daily.dev/agentic-ai-hub/open-weight-models/ og:type: article og:url: https://daily.dev/agentic-ai-hub/open-weight-models/ og:title: Open-Weight Models | The Agentic AI Hub — daily.dev og:description: The models you can download, self-host, and fine-tune. As of July 2026. Two things to know: (1) "open weight" ≠ open source. og:image: https://daily.dev/assets/og/agentic-ai-hub.png?v=40e6ff69 og:site_name: daily.dev og:locale: en_US article:modified_time: 2026-07-22 twitter:card: summary_large_image twitter:site: @dailydotdev twitter:creator: @dailydotdev twitter:title: Open-Weight Models | The Agentic AI Hub — daily.dev twitter:description: The models you can download, self-host, and fine-tune. As of July 2026. Two things to know: (1) "open weight" ≠ open source. twitter:image: https://daily.dev/assets/og/agentic-ai-hub.png?v=40e6ff69 --- [Skip to main content ](#main-content) [   ](https://daily.dev/) [ Agentic AI Hub ](/agentic-ai-hub/) [   ](https://daily.dev/) / [ Agentic AI Hub ](/agentic-ai-hub/) [Get the app ](https://api.daily.dev/get?ref=docs-topbar) # Open-Weight Models Too busy to read? Get an AI summary * Copy page Copy page Copy page as Markdown for LLMs [ View as Markdown View this page as plain text ](https://daily.dev/agentic-ai-hub/open-weight-models.md/) > The models you can download, self-host, and fine-tune. **As of July 2026.** Two things to know: (1) _"open weight" ≠ open source_. Some ship under permissive licenses (Apache-2.0 / MIT), others under custom, use-restricted ones, so the **License** column matters. Check it before you build on a model. (2) The open frontier is now **led by Chinese labs** (DeepSeek, Qwen, Kimi, GLM), while Meta has pivoted toward closed models. | Model (latest open) | Released | Params (total / active) | License | Context | Best at | Run with | | ----------------------------- | -------- | ----------------------------- | -------------------- | ---------------- | ------------------------------------ | ---------------------- | | **DeepSeek V4** (Pro / Flash) | Apr 2026 | Pro 1.6T/49B · Flash 284B/13B | MIT ✅ | 1M | Reasoning, coding, cheap inference | vLLM, SGLang | | **Qwen3.6** (35B-A3B) | Apr 2026 | 35B / 3B active | Apache-2.0 ✅ | 262K (\~1M YaRN) | Agentic coding, repo-level reasoning | Ollama, vLLM, SGLang | | **Kimi K3** (Moonshot) | Jul 2026 | 2.8T / \~50B active | Modified MIT ✅ | 1M | Coding/agentic, near-Opus-4.8 | vLLM, SGLang | | **GLM-5.2** (Zhipu / Z.ai) | 2026 | \~744B / 40B active | MIT ✅ | \~1M | Coding/agentic/reasoning | vLLM, SGLang | | **Llama 4 Scout** (Meta) | Apr 2025 | 109B / 17B active | Llama 4 Community ⚠️ | 10M | Very long context, single-GPU | Ollama, vLLM | | **Llama 4 Maverick** (Meta) | Apr 2025 | 400B / 17B active | Llama 4 Community ⚠️ | 1M | Multimodal, general chat | vLLM | | **Mistral Large 3** | Dec 2025 | 675B / 41B active | Apache-2.0 ✅ | Large | Multimodal, multilingual | vLLM | | **Ministral 3** (3/8/14B) | Dec 2025 | dense | Apache-2.0 ✅ | n/a | Best small cost/perf, edge | Ollama, llama.cpp | | **Gemma 4** (Google) | Apr 2026 | 12B (+ MoE 26B-A4B) | Apache-2.0 ✅ | 256K | On-device → server, multimodal | Ollama, llama.cpp, MLX | | **Qwen3** (0.6B-235B) | 2025 | dense + MoE | Apache-2.0 ✅ | 32K-128K+ | Widest size range, 119 languages | Ollama, vLLM | | **Phi-4** family (Microsoft) | 2024-26 | 3.8B-\~15B | MIT ✅ | 16K-128K | Reasoning-per-parameter, on-device | Ollama, llama.cpp | ✅ permissive · ⚠️ source-available with use restrictions (check the model card). Rough VRAM rule of thumb: a dense model needs \~(params × bytes-per-param) of VRAM, e.g. a 27B model at 4-bit quantization ≈ 16 GB. MoE models load all experts into memory but only compute the active set, so they're fast but still memory-hungry. Sources: [Qwen](https://huggingface.co/Qwen) · [DeepSeek](https://github.com/deepseek-ai/deepseek-v3) · [Mistral](https://mistral.ai/news/mistral-3/) · [Gemma](https://ai.google.dev/gemma/docs/releases) · [Kimi](https://huggingface.co/moonshotai) · [GLM](https://huggingface.co/zai-org/GLM-5) · [Llama](https://ai.meta.com/blog/). **Track open models live:** [Hugging Face trending](https://huggingface.co/models) (the canonical release feed; the original Open LLM Leaderboard was archived in 2025), [LMArena](https://lmarena.ai/) (includes open models), [llm-stats.com](https://llm-stats.com/llm-updates). Share this page Copy link [ Previous Frontier Model Comparison ](/agentic-ai-hub/frontier-model-comparison/) [ Next Specialized Models ](/agentic-ai-hub/specialized-models/) [ Previous ](#) [ Next ](#) Link copied!