Introduction: The two heavyweights of 2026
Qwen 3 (Alibaba Cloud) and Llama 3.3 (Meta) dominate the open-source LLM landscape in 2026. These two model families, available in 8B, 14B/15B, 32B and 70B parameter versions, represent the pinnacle of what can be run locally.
But which one to choose? Our comparison relies on standardized benchmarks, real tests, and thousands of user feedback to give you the definitive answer.
Specification comparison table
| Criteria | Qwen 3 | Llama 3.3 | Winner |
|---|---|---|---|
| Architecture | Transformer with RoPE, SwiGLU | Transformer with GQA, RoPE | Tie |
| Available sizes | 0.5B, 1.5B, 3B, 7B, 14B, 32B, 72B | 3B, 8B, 70B (Instruct) | Qwen 3 (+ granularity) |
| Context window | 128K tokens (32K native) | 128K tokens | Tie |
| Supported languages | 29+ languages (excellent French) | 8 languages (English dominant) | Qwen 3 |
| License | Apache 2.0 (open) | Meta License (commercial restrictions) | Qwen 3 |
| Multimodal | Qwen-VL available | Llama 3.2 Vision (separate) | Tie |
Benchmark results
We tested the 8B Instruct versions on a standard configuration (RTX 3060 12GB, 32GB RAM) with the recommended Q5_K_M quantization.
| Benchmark | Qwen 3 8B | Llama 3.3 8B | Comment |
|---|---|---|---|
| MMLU (knowledge) | 79.5% | 77.4% | Qwen slightly superior |
| HumanEval (code) | 61.0% | 72.6% | Llama excellent at programming |
| GSM8K (math) | 83.2% | 78.5% | Qwen better at math reasoning |
| MT-Bench (conversation) | 8.28 | 7.85 | Qwen more natural in dialogue |
| BoolQ (comprehension) | 87.5% | 88.9% | Llama very slightly better |
Analysis by use case
📝 General chat and personal assistant
Winner: Qwen 3
- More natural in long conversations
- Better understanding of nuances and implications
- Excellent French mastery (crucial for French-speaking users)
- Fewer unjustified refusals on "sensitive" topics
💻 Programming and development
Winner: Llama 3.3 (with CodeLlama)
- CodeLlama 7B/13B/34B offers superior coding performance
- Better inline code completion
- More precise technical documentation
- Fewer hallucinations on specific APIs
🧮 Reasoning and mathematics
Winner: Qwen 3
- More coherent step-by-step reasoning
- Fewer calculation errors in arithmetic
- Qwen 32B rivals GPT-4 on complex problems
🌍 Multilingual and international content
Winner: Qwen 3 (overwhelming)
- Support for 29 languages vs 8 for Llama
- French, German, Spanish, Japanese, Chinese of native quality
- More faithful and natural translation
Consumption and hardware performance
On identical hardware (MacBook Pro M3 36GB), here are the real measurements:
| Metric | Qwen 3 8B Q5 | Llama 3.3 8B Q5 |
|---|---|---|
| GGUF file size | 5.4 GB | 5.7 GB |
| RAM used (idle) | ~6.2 GB | ~6.5 GB |
| Tokens/second (M3 Pro) | ~45 tok/s | ~42 tok/s |
| Generation time (500 tokens) | ~11 seconds | ~12 seconds |
| Energy consumption | Equivalent | Equivalent |
Verdict: Qwen 3 is slightly more efficient in terms of size and speed, probably thanks to a more optimized architecture.
Strengths and weaknesses
🌐 Qwen 3 — Strengths
- ✅ Exceptional versatility
- ✅ Unparalleled multilingual support
- ✅ Excellent granularity of sizes
- ✅ Apache 2.0 license (100% open)
- ✅ Superior mathematical reasoning
- ✅ Natural and nuanced dialogue
🦙 Llama 3.3 — Strengths
- ✅ Excellence in programming (with CodeLlama)
- ✅ Very active Meta ecosystem
- ✅ Better documented fine-tuning
- ✅ Compatible with more cloud tools
- ✅ Sharp technical knowledge
- ✅ Excellent English-language benchmarks
Final verdict: Which one to choose?
🏆 Our recommendation by profile:
- French-speaking user → Qwen 3: The quality of French is incomparable. For discussions, writing, translation, it's the obvious choice.
- Developer → CodeLlama (Llama-based): If your main usage is code, prioritize CodeLlama 13B/34B based on the Llama architecture.
- Versatile general use → Qwen 3: Better quality/size ratio, more languages, more open license.
- Enterprise/Compliance → Check Meta license: Llama 3.3 has commercial restrictions for very large enterprises.
- Limited hardware (8GB) → Qwen 3 7B: Lighter and more performant than equivalent Llama 3.3 8B.
Conclusion
Qwen 3 emerges as the best generalist choice in 2026, particularly for non-English speakers. Its versatility, multilingual excellence and open license make it the reference local LLM.
Llama 3.3 remains excellent for development and has a very rich ecosystem. It is particularly relevant if you work primarily in English and do a lot of programming.
Fortunately, with LocalClaw, you don't have to choose in advance: test our personalized recommendations and download both to compare directly on your own use cases!