Self-host, fine-tune, and deploy without restrictions. Open source models now match proprietary alternatives—hitting 90% on LiveCodeBench and 97% on AIME 2025.
Keep all data on your infrastructure. No API calls to third parties. Critical for healthcare, legal, and enterprise applications.
Fine-tune for your specific use case. Modify behavior, remove guardrails, or train on proprietary data. No terms of service limitations.
At high volumes, self-hosting becomes dramatically cheaper. No per-token fees—just infrastructure costs.
| Rank | Model | Quality | LiveCodeBench | AIME 2025 | MMLU-Pro |
|---|---|---|---|---|---|
| 1 | GLM-4.7 (Thinking) Z AI | 41.7 | 89% | 95% | 86% |
| 2 | DeepSeek V3.2 DeepSeek | 41.2 | 86% | 92% | 86% |
| 3 | Kimi K2 Thinking Kimi | 40.3 | 85% | 95% | 85% |
| 4 | MiniMax-M2.1 MiniMax | 39.3 | 81% | 83% | 88% |
| 5 | MiMo-V2-Flash Xiaomi | 39 | 87% | 96% | 84% |
| 6 | Llama Nemotron Ultra NVIDIA | 38 | 64% | 64% | 83% |
| 7 | MiniMax-M2 MiniMax | 35.7 | 83% | 78% | 82% |
| 8 | DeepSeek V3.2 Speciale DeepSeek | 34.1 | 90% | 97% | 86% |
| 9 | DeepSeek V3.1 Terminus DeepSeek | 33.4 | 80% | 90% | 85% |
| 10 | gpt-oss-120B (high) OpenAI | 32.9 | 88% | 93% | 81% |
| 11 | GLM-4.6 Z AI | 32.2 | 56% | 44% | 78% |
| 12 | Qwen3 235B A22B 2507 Alibaba | 29.3 | 79% | 91% | 84% |
The verdict: For coding tasks, open source models like GLM-4.7 (Thinking) now match or exceed proprietary alternatives. The gap has effectively closed for most practical applications.
Use hosted APIs for open models. Get the benefits of open source with the ease of SaaS.
Together.ai — Competitive pricing, great selection
Fireworks.ai — Fast inference, good for production
Groq — Fastest inference available
Run models on your own infrastructure for maximum control and privacy.
Ollama — Easiest local setup, great for development
vLLM — Production-grade serving, excellent throughput
Text Generation Inference — HuggingFace's production server
Use our interactive tool to compare benchmarks, parameters, and provider pricing for all 12 open source models.
As of January 2026, GLM-4.7 (Thinking) leads our open source rankings with exceptional performance across coding (89%) and reasoning (95%) benchmarks. It's completely free to download and use.
Yes, for many tasks. GLM-4.7 (Thinking) achieves 89% on LiveCodeBench, matching or exceeding GPT-5 on coding tasks. The gap has closed dramatically in 2025-2026, with open models now competitive on most benchmarks.
It depends on the model size. 7B-13B models run on consumer GPUs (16GB+ VRAM).70B+ models need enterprise GPUs (A100/H100) or multi-GPU setups. For cost-effective deployment, consider quantized versions (GGUF, AWQ) which reduce memory requirements by 50-75% with minimal quality loss.
Open weights means you can download and use the model, but may have license restrictions on commercial use.Fully open source (like Llama 3.1 or Qwen 2.5) includes training code, data information, and permissive licenses. All models in our ranking allow commercial use—check specific licenses for fine-tuning and redistribution terms.