--- title: MiniMax 2.5 vs Llama 3.1 vs DeepSeek: Local Coding Model... description: A hands-on benchmark comparing MiniMax 2.5, Llama 3.1 (70B and 405B), DeepSeek-R1, and Qwen2.5-Coder 32B on four coding tasks—function generation, bug... canonical: https://daily.dev/posts/minimax-2-5-vs-llama-3-1-vs-deepseek-local-coding-model-benchmark-2026-5pxrq2zot twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: MiniMax 2.5 vs Llama 3.1 vs DeepSeek: Local Coding Model Benchmark 2026 | daily.dev og:description: A hands-on benchmark comparing MiniMax 2.5, Llama 3.1 (70B and 405B), DeepSeek-R1, and Qwen2.5-Coder 32B on four coding tasks—function generation, bug... og:url: https://daily.dev/posts/minimax-2-5-vs-llama-3-1-vs-deepseek-local-coding-model-benchmark-2026-5pxrq2zot og:image: https://api.daily.dev/og/posts/5pxrQ2zoT.png og:image:alt: MiniMax 2.5 vs Llama 3.1 vs DeepSeek: Local Coding Model Benchmark 2026 og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # MiniMax 2.5 vs Llama 3.1 vs DeepSeek: Local Coding Model Benchmark 2026 **[SitePoint](https://daily.dev/sources/sitepoint)** · 19 min read · 1 upvotes · 0 comments ## Summary A hands-on benchmark comparing MiniMax 2.5, Llama 3.1 (70B and 405B), DeepSeek-R1, and Qwen2.5-Coder 32B on four coding tasks—function generation, bug detection, refactoring, and multi-file context understanding—run locally on dual RTX 3090 GPUs using llama.cpp. Key findings: MiniMax 2.5 is the best all-rounder (1st or 2nd on 3 of 4 tasks, ~17.5 tok/s), Llama 3.1 405B produces the highest code quality but is too slow for interactive use (~7.8 tok/s), DeepSeek-R1 excels at debugging via chain-of-thought but is the slowest (~9.8 tok/s), and Qwen2.5-Coder 32B is the only single-GPU option with the fastest throughput (~36.8 tok/s) at lower quality. Llama 3.1 70B failed two of four tasks, making its quality drop from 405B larger than expected. Detailed VRAM requirements, scoring methodology, and actual model outputs are included. ## Full article daily.dev links to this article rather than hosting it. 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