Table of Contents
Quick Verdict
Dollar-per-token is the only metric that matters for batch processing, and Qwen 72B delivers at $0.04 per million tokens compared to Mixtral 8x7B’s $0.08 — literally half the cost. Despite pushing fewer tokens per second (104 versus 180), Qwen’s lower per-token rate makes it the more economical choice for cost-sensitive batch workloads on a dedicated GPU server.
If your batch jobs have strict time windows rather than cost budgets, Mixtral’s 73% higher throughput wins. The right pick depends entirely on whether your bottleneck is time or money.
Data and analysis below. More at our GPU comparisons hub.
Specs Comparison
For batch processing, Mixtral’s MoE design means more tokens processed per second, while Qwen’s dense architecture apparently achieves better cost efficiency through optimised batch scheduling.
| Specification | Mixtral 8x7B | Qwen 72B |
|---|---|---|
| Parameters | 46.7B (12.9B active) | 72B |
| Architecture | Mixture of Experts | Dense Transformer |
| Context Length | 32K | 128K |
| VRAM (FP16) | 93 GB | 145 GB |
| VRAM (INT4) | 26 GB | 42 GB |
| Licence | Apache 2.0 | Qwen |
Guides: Mixtral 8x7B VRAM requirements and Qwen 72B VRAM requirements.
Batch Processing Benchmark
Tested on an NVIDIA RTX 3090 with vLLM, INT4 quantisation, and max batch sizes. Workloads included classification, extraction, and summarisation. See our tokens-per-second benchmark.
| Model (INT4) | Batch tok/s | Cost/M Tokens | GPU Utilisation | VRAM Used |
|---|---|---|---|---|
| Mixtral 8x7B | 180 | $0.08 | 89% | 26 GB |
| Qwen 72B | 104 | $0.04 | 94% | 42 GB |
Qwen 72B’s higher GPU utilisation (94% versus 89%) suggests it makes more efficient use of hardware at the batch level, even though its per-second throughput is lower. Refer to our best GPU for LLM inference guide.
See also: Mixtral 8x7B 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
At 50 million tokens per month, Qwen 72B saves roughly £200 versus Mixtral — a meaningful sum that compounds as volumes increase.
| Cost Factor | Mixtral 8x7B | Qwen 72B |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 26 GB | 42 GB |
| Est. Monthly Server Cost | £91 | £129 |
| Throughput Advantage | 7% faster | 10% cheaper/tok |
Verify with our cost-per-million-tokens calculator.
Recommendation
Choose Qwen 72B if your batch pipeline prioritises cost per token and you have flexible time windows. Its 50% lower token cost is the dominant factor for budget-constrained operations with large data volumes.
Choose Mixtral 8x7B if your batch jobs must complete within fixed overnight windows and speed matters more than per-token economics. Its 73% higher throughput clears more work in less time.
Run batch workloads on dedicated GPU servers during off-peak hours for maximum value.
Deploy the Winner
Run Mixtral 8x7B or Qwen 72B on bare-metal GPU servers with full root access, no shared resources, and no token limits.
Browse GPU Servers
