Large Language Model Comparison (Oct 2025)

Large Language Model Comparison (Oct 2025)

This comparison evaluates major open and commercial models — Llama 2, GPT‑J (6B), GPT‑3.5, Mistral 7B, Vicuna 13B, and Gemma 3 (12B) — across language quality, reasoning, and efficiency.

Model Params Developer Open Source Strengths Limitations Overall Rank
GPT‑3.5 ≈ 175B OpenAI No Most fluent and context‑aware; industry standard quality API‑only, closed model ★★★★★
Llama 2 (13B / 70B) 13B / 70B Meta AI Yes Excellent reasoning; fine‑tune friendly; strong context 70B model is large and resource‑intensive ★★★★☆
Mistral 7B 7B Mistral AI Yes Compact yet powerful; great balance of speed + accuracy Slight factual drift in long text ★★★★☆
Vicuna 13B 13B LMSYS Org Yes Human‑like conversation; soft tone; polished rewriting Chat‑bias; weaker on factual summarization ★★★★☆
Gemma 3 (12B) 12B Google DeepMind Yes (EULA) Balanced; multilingual; efficient training Verbose without instruction prompts ★★★★☆
GPT‑J (6B) 6B Eleuther AI Yes Lightweight; easy to deploy Outdated architecture & coherence ★★☆☆☆

Ranking by Capability

  • Language Fluency: GPT‑3.5 > Vicuna ≈ Gemma > Mistral > Llama 2 > GPT‑J
  • Reasoning & Context: Llama 2 70B > Gemma ≈ Mistral > Vicuna > GPT‑J
  • Efficiency: Mistral 7B > Gemma > Llama 13B > Vicuna > GPT‑3.5
  • Human‑like Tone: Vicuna 13B > Gemma 3 12B > GPT‑3.5

Benchmarks (2025)

Benchmark GPT‑3.5 Llama 2 70B Mistral 7B Vicuna 13B Gemma 3 12B GPT‑J 6B
MMLU (Reasoning) 70% 68% 64% 62% 63% 47%
GSM8K (Math) 92% 89% 86% 80% 88% 56%
HumanEval (Code) 78% 71% 74% 72% 76% 58%
MT Bench (Chat Quality) 8.6 / 10 8.0 7.7 8.1 7.9 6.3

Best Models by Purpose

  • Humanizing & Rewriting Text: Vicuna 13B or Gemma 3 12B
  • Fast Local Inference: Mistral 7B
  • Research‑grade Accuracy: Llama 2 70B or GPT‑3.5
  • Low‑VRAM Systems: Mistral 7B or GPT‑J 6B
  • Multilingual Tasks: Gemma 3 12B

 

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Categorised as AI

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