A head-to-head comparison of three flagship open-weights models on coding benchmarks, context windows, and value-for-money.
Why this comparison matters
If you're picking an open-source AI model for coding, three names come up: DeepSeek V4 Pro, Llama 4 405B, and Qwen 3.8 Max. All are flagship-tier with open weights. We compare them head-to-head.
DeepSeek V4 Pro — the coding specialist
1M context window, Mixture-of-Experts architecture, best-in-class coding benchmarks. The 1M context is the killer feature — enough to fit an entire mid-sized codebase in a single prompt.
Llama 4 405B — the general-purpose flagship
Meta's largest open-weights dense model. Solid at coding, reasoning, and general chat. The Llama 4 license is the most permissive for commercial use.
Qwen 3.8 Max — the multilingual contender
Alibaba's flagship with 1M context. Best-in-class multilingual support (CJK + Arabic). Roughly tied with DeepSeek on English coding tasks.
Our recommendation
For most developers: DeepSeek V4 Pro. The 1M context + MoE efficiency is hard to beat. For consistent latency: Llama 4 405B. For multilingual codebases: Qwen 3.8 Max.
Browse all three on we64.com. Free Trial Keys available — ask on WhatsApp.