Best Local & Open-Weight LLMs (2026)
Open-weight and self-hostable large language models. Chinese and American labs compared — Qwen, DeepSeek, GLM, Kimi, Llama, Gemma, Mistral, Nemotron, MiniMax, Falcon. Benchmarks, pricing, and hardware requirements (min/mid/max) for running each model locally.
21 tools ranked S through F.
Tier rankings
A
B
Full ranking
Sorted by overall score. Click any tool for the full review.
| # | Tool | Tier | Overall | Ease | Output | Value | Features |
|---|---|---|---|---|---|---|---|
| 1 | Qwen (Alibaba) Alibaba's open-weights + API family -- Qwen3.8-Max flagship previewed at WAIC (Jul 19 2026: 2.4T sparse-MoE multimodal, closed preview, 'second only to Fable 5'), Qwen 3.7 Max GA (SWE-Bench Pro 60.6%, Terminal-Bench 69.7%, $2.50/$7.50 per 1M), Qwen3.6-27B dense Apache 2.0 (beats the 397B MoE on coding from one consumer GPU) | A | 8.8 | 7 | 9 | 10 | 9 |
| 2 | MiniMax M3 MiniMax's coding/agent flagship -- M3 (June 1 2026): 1M-token context, MSA sparse attention (>15x decoding speedup at long context), SWE-Bench Pro 59.0%, Terminal-Bench 66.0%. OPEN WEIGHTS LIVE on HuggingFace since June 12 (~428B total / ~23B active, native multimodal, minimax-community license) | A | 8.4 | 6.5 | 9 | 9.5 | 8.5 |
| 3 | Gemma 4 (Google) Google DeepMind's open-weights model family -- multimodal, 256K context, runs on edge devices | A | 8.3 | 7 | 8 | 10 | 8 |
| 4 | IBM Granite 4.0 IBM's enterprise-focused open-weight family -- Granite 4.0 hybrid Mamba-2 + transformer architecture (70-80% memory reduction vs pure transformer), 3B to 32B sizes, Apache 2.0. First open model family to secure ISO 42001 certification. Nano 350M runs on CPU with 8-16GB RAM. 3B Vision variant landed 2026-04-01 | A | 8.2 | 7 | 8 | 9.5 | 8.5 |
| 5 | Kimi K3 (Moonshot) Moonshot's 2.8T-parameter Kimi K3 (launched 2026-07-16/17) is the largest open-weight model ever announced -- 1M context, multimodal, $3/$15 per 1M via API, ranked best-available on Arena.AI at launch. Weights promised late July (press cites 7/27); K2.6/K2.7-Code remain the shipped-weights line | A | 8.1 | 6 | 9 | 8.5 | 9 |
| 6 | gpt-oss (OpenAI) OpenAI's FIRST open-weight models -- gpt-oss-120b (single 80GB GPU, near parity with o4-mini on reasoning) and gpt-oss-20b (runs on 16GB edge devices). Apache 2.0. Launched 2025-08-05. gpt-oss-safeguard ships in 2026 as the safety-tuned variant | A | 8.1 | 7 | 8.5 | 10 | 7 |
| 7 | Arcee Trinity-Large-Thinking Arcee AI's US-made open-weight frontier reasoning model -- launched 2026-04-01. 398B total params, ~13B active. Sparse MoE (256 experts, 4 active = 1.56% routing). Apache 2.0, trained from scratch. #2 on PinchBench trailing only Claude 3.5 Opus. ~96% cheaper than Opus-4.6 on agentic tasks | A | 8.1 | 6 | 9 | 9.5 | 8 |
| 8 | DeepSeek DeepSeek V4 shipped 2026-04-24: V4-Pro (1.6T/49B active MoE) + V4-Flash (284B/13B active), 1M native context, Hybrid Attention Architecture, open-source on HF. Trails only Gemini 3.1 Pro on world knowledge | A | 8.0 | 7.5 | 8 | 9.5 | 7 |
| 9 | GLM / Z.ai (Zhipu AI) Zhipu AI's open-weights flagship -- GLM-5.2 (launched 2026-06-13) is a ~753B-parameter MoE with a 1M-token context and the new IndexShare sparse-attention architecture (~2.9x lower per-token FLOPs at 1M context), MIT licensed. Vendor benchmarks put SWE-Bench Pro at 62.1 (up from GLM-5.1's 58.4) and it tops the Artificial Analysis open-weights Intelligence Index; VentureBeat reports it beats GPT-5.5 on several long-horizon coding benchmarks at roughly 1/6 the cost. Drop-in for Claude Code / Cline / OpenCode. Still trained outside the Nvidia stack on Huawei Ascend silicon | A | 8.0 | 6.5 | 8.5 | 9 | 8 |
| 10 | AI21 Jamba2 AI21 Labs' hybrid SSM-Transformer (Mamba-style) open-weight family -- Jamba2 launched 2026-01-08. Two sizes: 3B dense (runs on phones / laptops) and Jamba2 Mini MoE (12B active / 52B total). Apache 2.0, 256K context, mid-trained on 500B tokens | A | 8.0 | 6.5 | 8 | 9 | 8.5 |
| 11 | Inkling (Thinking Machines Lab) Mira Murati's $12B lab ships its first model (2026-07-15): a 975B/41B-active open-weights MoE that reasons natively over text, images, and audio with a 1M-token context -- positioned not as the strongest model, but as the best starting point for fine-tuning via Tinker | A | 8.0 | 6 | 8 | 8.5 | 8.5 |
| 12 | Llama 4 (Meta) Meta's open-weights family -- Scout (10M context), Maverick (multimodal 400B MoE). NOTE: Meta's frontier work moved to the proprietary Muse Spark line in April 2026; Llama remains downloadable and supported but is effectively in maintenance mode | B | 7.9 | 5 | 8.5 | 9 | 9 |
| 13 | Olmo 3 (AI2) Allen Institute for AI's fully-open frontier reasoning models -- Olmo 3 family (2025-11-20) includes 7B and 32B sizes, four variants (Base, Think, Instruct, RLZero). Apache 2.0 with fully open data + checkpoints + training logs. Olmo 3-Think 32B matches Qwen3-32B-Thinking at 6x fewer training tokens | B | 7.9 | 6 | 8 | 9.5 | 8 |
| 14 | LongCat-2.0 (Meituan) Meituan's open-source 1.6T-parameter MoE (~48B active) with native 1M-token context, MIT license -- trained entirely on domestic Chinese AI ASICs and revealed as the stealth 'Owl Alpha' model that had been topping OpenRouter | B | 7.9 | 6 | 8.5 | 9 | 8 |
| 15 | Bonsai 27B (PrismML) The first 27B-class model that runs on a phone (2026-07-14) -- ternary and 1-bit quantizations of Qwen3.6 27B squeeze a multimodal, tool-calling, 262K-context model into 3.9-5.9GB under Apache 2.0 | B | 7.9 | 8 | 7 | 9.5 | 7.5 |
| 16 | Nemotron (Nvidia) Nvidia's open-weights family -- hybrid Mamba-Transformer MoE architecture, optimized for efficient reasoning on Nvidia hardware. Nemotron 3 Ultra (550B total / 55B active) shipped 2026-06-04 as the family flagship, joining Super (120B/12B, March) and Nano | B | 7.8 | 6.5 | 8 | 8 | 8.5 |
| 17 | StepFun Step 3.7 Flash StepFun's (China) agent-focused open-weight family -- Step 3.7 Flash (May 28 2026): 198B sparse MoE vision-language model, ~11B active, 256K context, Apache 2.0, ~400 tok/s, SWE-Bench Pro 56.3. Supersedes Step 3.5 Flash (Feb 2026) as the flagship | B | 7.8 | 6 | 8 | 9 | 8 |
| 18 | Mistral AI European AI lab with open and commercial models -- Le Chat is now **Vibe** (May 28 2026): one agent across Work Mode + Code Mode with a VS Code extension and CLI, powered by Mistral Medium 3.5 (128B dense, 256k context, 77.6% SWE-Bench Verified). Earlier 2026 line: Small 4 (119B MoE Apache 2.0), Medium 3, Voxtral TTS | B | 7.5 | 6 | 8 | 9 | 7 |
| 19 | Cohere Command A Cohere's enterprise-multilingual flagship -- 111B params, 256K context, runs on 2x H100. 23 languages. CC-BY-NC 4.0 on weights (research / non-commercial), commercial requires Cohere enterprise contract. Follow-ups: Command A Reasoning + Command A Vision | B | 7.5 | 6.5 | 8.5 | 7 | 8 |
| 20 | Falcon (TII) UAE's Technology Innovation Institute open-weights family -- Falcon 3 optimized for efficient sub-10B deployment on consumer hardware | B | 7.1 | 7 | 6.5 | 9 | 6 |
| 21 | DiffusionGemma (Google) Google DeepMind's experimental open-weights TEXT-DIFFUSION model (June 10, 2026) -- 26B MoE (3.8B active), Apache 2.0, generates 256-token blocks in parallel with bidirectional attention for up to 4x faster output (1,000+ tok/s on H100). Trades some quality vs Gemma 4 for raw speed | C | 6.8 | 6 | 6.5 | 9 | 6 |