Table of Contents
Quick Verdict
A ROUGE-L of 41.2 versus 32.4 is not a subtle difference — it means LLaMA 3 70B captures roughly 27% more of the source document’s key content in each summary. For a legal team summarising 200 contracts per day, that coverage gap is the difference between catching a buried indemnity clause and missing it entirely. On a dedicated GPU server, LLaMA 3 70B is the definitive choice for factual summarisation.
LLaMA 3 70B also generates summaries faster (35/min versus 26/min), making it both higher quality and higher throughput. Mixtral’s only advantage is VRAM efficiency and slightly tighter output length.
Full data below. More at the GPU comparisons hub.
Specs Comparison
Mixtral’s 32K context window handles longer input documents than LLaMA 3 70B’s 8K, which is relevant for summarising lengthy reports without chunking.
| Specification | LLaMA 3 70B | Mixtral 8x7B |
|---|---|---|
| Parameters | 70B | 46.7B (12.9B active) |
| Architecture | Dense Transformer | Mixture of Experts |
| Context Length | 8K | 32K |
| VRAM (FP16) | 140 GB | 93 GB |
| VRAM (INT4) | 40 GB | 26 GB |
| Licence | Meta Community | Apache 2.0 |
Guides: LLaMA 3 70B VRAM requirements and Mixtral 8x7B VRAM requirements.
Text Summarisation Benchmark
Tested on an NVIDIA RTX 3090 with vLLM, INT4 quantisation, and continuous batching. Documents included news articles, research papers, and business reports. See our tokens-per-second benchmark.
| Model (INT4) | ROUGE-L | Summaries/min | Avg Length | VRAM Used |
|---|---|---|---|---|
| LLaMA 3 70B | 41.2 | 35 | 87 tokens | 40 GB |
| Mixtral 8x7B | 32.4 | 26 | 96 tokens | 26 GB |
Mixtral’s longer average output (96 versus 87 tokens) with a lower ROUGE-L score indicates it pads summaries with less relevant content. LLaMA 3 70B is more precise: shorter summaries that capture more of what matters. See our best GPU for LLM inference guide.
See also: LLaMA 3 70B vs Mixtral 8x7B for Chatbot / Conversational AI for a related comparison.
See also: LLaMA 3 70B vs Mixtral 8x7B for Code Generation for a related comparison.
Cost Analysis
LLaMA 3 70B’s higher throughput means it processes the same volume of summaries at a lower total cost, despite its higher VRAM footprint.
| Cost Factor | LLaMA 3 70B | Mixtral 8x7B |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 40 GB | 26 GB |
| Est. Monthly Server Cost | £126 | £99 |
| Throughput Advantage | 12% faster | 8% cheaper/tok |
See our cost-per-million-tokens calculator.
Recommendation
Choose LLaMA 3 70B for any summarisation pipeline where factual coverage matters. Its 27% ROUGE-L advantage and 35% throughput lead make it superior on both quality and speed. The only scenario where it falls short is documents exceeding 8K tokens, which require chunking.
Choose Mixtral 8x7B if your source documents regularly exceed 8K tokens and you need native long-context support, or if your deployment must fit within a 26 GB VRAM envelope.
Self-host on dedicated GPU servers for predictable summarisation throughput.
Deploy the Winner
Run LLaMA 3 70B or Mixtral 8x7B on bare-metal GPU servers with full root access, no shared resources, and no token limits.
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