Table of Contents
Quick Verdict
Overnight batch jobs care about one thing: how much work completes before the team arrives in the morning. Qwen 72B pushes 130 tok/s in batch mode versus LLaMA 3 70B’s 84 tok/s — a 55% throughput advantage that means a 10-hour processing window handles 55% more data on a dedicated GPU server.
The cost-per-token story is tighter than expected ($0.17/M for Qwen versus $0.16/M for LLaMA 3), so the decision here is primarily about throughput and whether your batch tasks benefit from Qwen’s massive 128K context window or LLaMA 3 70B’s slightly higher output quality.
Full data below. Visit the GPU comparisons hub for more matchups.
Specs Comparison
For batch workloads processing long documents, Qwen 72B’s 128K context window eliminates the need for chunking strategies that add pipeline complexity. LLaMA 3 70B’s 8K limit means you must slice larger inputs into multiple passes.
| 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 |
Sizing guides: LLaMA 3 70B VRAM requirements and Qwen 72B VRAM requirements.
Batch Processing Benchmark
Tested on an NVIDIA RTX 3090 with vLLM, INT4 quantisation, and max batch sizing. Workloads included document classification, entity extraction, and content summarisation. See our tokens-per-second benchmark for live data.
| Model (INT4) | Batch tok/s | Cost/M Tokens | GPU Utilisation | VRAM Used |
|---|---|---|---|---|
| LLaMA 3 70B | 84 | $0.16 | 94% | 40 GB |
| Qwen 72B | 130 | $0.17 | 86% | 42 GB |
LLaMA 3 70B achieves higher GPU utilisation at 94% versus 86%, suggesting it saturates the hardware more efficiently per token. Qwen 72B compensates with raw speed — its architecture apparently processes each token faster despite lower overall utilisation. Refer to our best GPU for LLM inference guide for hardware insights.
See also: LLaMA 3 70B vs Qwen 72B for Chatbot / Conversational AI for a related comparison.
See also: LLaMA 3 70B vs Mixtral 8x7B for Cost-Optimised Batch Processing for a related comparison.
Cost Analysis
The per-token costs are nearly identical, so the economic decision hinges on whether you value time (Qwen finishes faster) or cost certainty (LLaMA 3 is marginally cheaper per token).
| 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 | £158 | £133 |
| Throughput Advantage | 15% faster | 0% cheaper/tok |
Calculate exact costs at our cost-per-million-tokens calculator.
Recommendation
Choose Qwen 72B if your batch pipeline is throughput-constrained and you need jobs to finish within fixed time windows. Its 55% higher tok/s means overnight runs cover significantly more ground. The 128K context window also simplifies pipelines that process long documents.
Choose LLaMA 3 70B if your batch outputs require the highest possible quality per token and your processing window is flexible. Its marginally lower cost-per-token and stronger ecosystem tooling make it a reliable workhorse for accuracy-sensitive batch work.
Schedule batch workloads during off-peak hours on dedicated GPU servers for maximum cost efficiency.
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
