Table of Contents
Quick Verdict
When your enterprise chatbot serves offices in Shanghai, Munich, and New York, the model’s ability to maintain quality across languages is not optional. Qwen 72B scores 7.9 on multilingual evaluation versus LLaMA 3 70B’s 7.7, with particularly strong Chinese performance (22 tok/s versus 23 tok/s — nearly matching LLaMA’s English-to-Chinese throughput ratio). On a dedicated GPU server, Qwen 72B is the more balanced multilingual choice.
LLaMA 3 70B generates English tokens faster (32 tok/s versus 27 tok/s), making it the better option for English-dominant deployments with occasional multilingual needs.
Full data below. More at the GPU comparisons hub.
Specs Comparison
Qwen 72B’s 128K context window is valuable for multilingual conversations, which tend to consume more tokens due to varying tokenisation efficiency across scripts and languages.
| Specification | LLaMA 3 70B | Qwen 72B |
|---|---|---|
| Parameters | 70B | 72B |
| Architecture | Dense Transformer | Dense Transformer |
| Context Length | 8K | 128K |
| VRAM (FP16) | 140 GB | 145 GB |
| VRAM (INT4) | 40 GB | 42 GB |
| Licence | Meta Community | Qwen |
Guides: LLaMA 3 70B VRAM requirements and Qwen 72B VRAM requirements.
Multilingual Chat Benchmark
Tested on an NVIDIA RTX 3090 with vLLM, INT4 quantisation, and continuous batching across English, Chinese, German, Spanish, and French. See our tokens-per-second benchmark.
| Model (INT4) | EN tok/s | ZH tok/s | Multi-lang Score | VRAM Used |
|---|---|---|---|---|
| LLaMA 3 70B | 32 | 23 | 7.7 | 40 GB |
| Qwen 72B | 27 | 22 | 7.9 | 42 GB |
LLaMA 3 70B’s English throughput advantage (19% faster) diminishes to just 5% in Chinese, reflecting its English-centric training distribution. Qwen’s training balanced more evenly across languages. See our best GPU for LLM inference guide.
See also: LLaMA 3 70B vs Qwen 72B for Chatbot / Conversational AI for a related comparison.
See also: Mistral 7B vs Qwen 2.5 7B for Document Processing / RAG for a related comparison.
Cost Analysis
Near-identical VRAM and hardware requirements mean cost is driven by throughput, which favours LLaMA 3 for English-heavy workloads and Qwen for balanced multilingual traffic.
| Cost Factor | LLaMA 3 70B | Qwen 72B |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 40 GB | 42 GB |
| Est. Monthly Server Cost | £96 | £145 |
| Throughput Advantage | 11% faster | 6% cheaper/tok |
See our cost-per-million-tokens calculator.
Recommendation
Choose Qwen 72B if your chatbot serves a genuinely multilingual audience, particularly one with significant Chinese, Japanese, or Korean traffic. Its more balanced training data and 128K context window make it the stronger foundation for international deployments.
Choose LLaMA 3 70B if English is the dominant language (80%+ of conversations) and you want the fastest possible English throughput with adequate multilingual fallback capability.
Deploy on dedicated GPU servers for consistent multilingual performance.
Deploy the Winner
Run LLaMA 3 70B or Qwen 72B on bare-metal GPU servers with full root access, no shared resources, and no token limits.
Browse GPU Servers
