Llama 5 vs Qwen 3.5: Which Open-Source LLM Wins (2026)
Llama 5 vs Qwen 3.5: Open-Source LLM Comparison
Meta’s Llama 5 (April 8, 2026) and Alibaba’s Qwen 3.5 (late 2025) are the two most important open-weight model families of spring 2026. They solve very different problems.
Last verified: April 11, 2026
Quick Comparison
| Feature | Llama 5 | Qwen 3.5 |
|---|---|---|
| Released | April 8, 2026 | November 2025 |
| Largest model | 600B+ MoE | 72B dense |
| Smallest model | 8B dense | 1B dense |
| Context window | 5M tokens | 128K tokens |
| License | Llama Community License | Apache 2.0 |
| Best for | Frontier quality | Local / edge |
Benchmark Showdown
| Benchmark | Llama 5 600B | Qwen 3.5 72B |
|---|---|---|
| MMLU-Pro | ~82% | ~74% |
| SWE-bench Verified | ~74% | ~51% |
| GPQA Diamond | ~78% | ~63% |
| Aider Polyglot | ~72% | ~58% |
| MATH-500 | ~94% | ~88% |
Llama 5 wins every benchmark — but at ~8x the parameter count. On a per-parameter basis, Qwen 3.5 is arguably more efficient.
License Matters
- Llama 5: Free for most, but large companies (over 700M MAU) need a separate agreement. Training data and pipeline are not public.
- Qwen 3.5: Apache 2.0. Fully permissive. Use in any product, redistribute, fine-tune, no strings attached.
For startups that plan to become large companies, Qwen 3.5 has a cleaner license story.
Hardware Requirements
Llama 5 flagship (600B MoE):
- Self-host: 8x H100 (80GB) or 1x M3 Ultra 512GB
- Estimated cost: $180K+ for the H100 rig
- Q4 quantized: still needs ~350GB VRAM/unified memory
Qwen 3.5 72B:
- Self-host: 1x A100 80GB or 2x RTX 4090
- Estimated cost: $15K or less
- Q4 quantized: fits on a single 24GB RTX 4090
Qwen 3.5 9B:
- Runs on any 16GB Mac or 12GB+ GPU
- ~6.6GB RAM at Q4
- The sweet spot for laptop-local AI
When to Pick Llama 5
- You need frontier-tier quality and don’t want to pay OpenAI/Anthropic
- You need 5M+ token context for entire monorepo ingestion
- You have GPU budget for a proper serving rig
- You’re building agentic systems that need top-tier reasoning
When to Pick Qwen 3.5
- You want a model you can run on a laptop
- Apache 2.0 license is a hard requirement
- You’re building edge/on-device AI
- Your use case is narrow enough that 72B is plenty
- You need very cheap hosted inference ($0.90/M tokens)
The Right Answer: Use Both
The pros use Llama 5 for hard problems (planning, complex coding, long-context research) and Qwen 3.5 for high-volume simple tasks (classification, extraction, routing, summarization). This hybrid approach can cut inference costs by 5-10x versus running everything through the flagship.
Last verified: April 11, 2026