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.
19 tools reviewed
Tier Rankings
Detailed Comparison
| # | Tool | Score | Best For | Price | Free Tier | |
|---|---|---|---|---|---|---|
| 1 |  Qwen (Alibaba) | 8.8 | Developers who want frontier-tier open weights with Apache 2... | Free / $0.12 | Yes | Review |
| 2 |  MiniMax M3 | 8.4 | Agentic coding and tool-use workflows on a budget. Best pric... | Free / $0.30 | Yes | Review |
| 3 |  Gemma 4 (Google) | 8.3 | Developers and businesses who need a permissively licensed m... | Free / $0.14-0.40 | Yes | Review |
| 4 |  IBM Granite 4.0 | 8.2 | Regulated-industry enterprises (healthcare, finance, governm... | Free / Usage-based | Yes | Review |
| 5 |  Kimi K2.6 (Moonshot) | 8.1 | Agentic coding workflows, tool-use agents, and teams willing... | Free / $0.60 | Yes | Review |
| 6 |  gpt-oss (OpenAI) | 8.1 | Developers who want OpenAI-brand open-weight reasoning model... | Free / $0.15 | Yes | Review |
| 7 |  Arcee Trinity-Large-Thinking | 8.1 | Teams that need a US-made, Apache 2.0, frontier-tier open-we... | Free / $0.90 | Yes | Review |
| 8 |  DeepSeek | 8.0 | Developers and teams who need strong reasoning and coding ca... | Free / $0.14/$0.28 | Yes | Review |
| 9 |  GLM / Z.ai (Zhipu AI) | 8.0 | Teams that need genuine MIT-licensed frontier open weights w... | Free / $0.60+ | Yes | Review |
| 10 |  AI21 Jamba2 | 8.0 | Developers building long-context RAG systems (256K context w... | Free / Usage-based | Yes | Review |
| 11 |  Llama 4 (Meta) | 7.9 | Developers and teams who need a permissively-licensed open-w... | Free / $3-8 | Yes | Review |
| 12 |  Olmo 3 (AI2) | 7.9 | AI researchers doing reproducibility work, training-data stu... | Free / Usage-based | Yes | Review |
| 13 |  LongCat-2.0 (Meituan) | 7.9 | Teams that want frontier-class open weights for audit, fine-... | Free / $0.75 / $2.95 | Yes | Review |
| 14 |  Nemotron (Nvidia) | 7.8 | Teams running on Nvidia hardware (TensorRT-LLM, NIM) who nee... | Free / varies | Yes | Review |
| 15 |  StepFun Step 3.7 Flash | 7.8 | Teams building agent systems on Chinese open-weight foundati... | Free / Usage-based | Yes | Review |
| 16 |  Mistral AI | 7.5 | Developers who want cheap, high-quality API access. Also str... | Free / $0.20 | Yes | Review |
| 17 |  Cohere Command A | 7.5 | Mid-size to large enterprises needing a multilingual open-we... | Free / Usage-based | Yes | Review |
| 18 |  Falcon (TII) | 7.1 | Developers who need a genuinely Apache-2.0 small model for o... | Free / varies | Yes | Review |
| 19 | DiffusionGemma (Google) | 6.8 | Developers who need fast local text generation -- autocomple... | Free / undefined | Yes | Review |
All Local & Open-Weight LLMs Reviews
Qwen (Alibaba)
Alibaba's open-weights + API family -- Qwen 3.7 Max flagship GA (May 20 2026: SWE-Bench Pro 60.6%, Terminal-Bench 69.7%, GPQA 92.4%, $2.50/$7.50 per 1M with 50% promo until 6/22), Qwen3.7-Plus multimodal API (Jun 2), Qwen3.6-27B dense Apache 2.0 (beats the 397B MoE on coding from one consumer GPU)
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)
Gemma 4 (Google)
Google DeepMind's open-weights model family -- multimodal, 256K context, runs on edge devices
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
Kimi K2.6 (Moonshot)
Moonshot's 1T-parameter MoE open-weights flagship -- Kimi K2.6 (GA 2026-04-20) is #1 open-weights on Artificial Analysis Intelligence Index v4.0 (score 54, ranked #4 overall). Native video input, 256K context, Modified MIT license
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
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
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
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
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
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
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
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
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
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
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
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
Falcon (TII)
UAE's Technology Innovation Institute open-weights family -- Falcon 3 optimized for efficient sub-10B deployment on consumer hardware
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