Compare / Qwen3-Next 80B-A3B Thinking vs Llama 3.3 70B
Qwen3-Next 80B-A3B Thinking vs Llama 3.3 70B
Updated November 2026
Verdict
Qwen3-Next 80B-A3B Thinking scores higher on the Small LM Index: 63.3 vs 40.8. On the 2 benchmarks both labs report, Qwen3-Next 80B-A3B Thinking wins 2 and Llama 3.3 70B wins 0. Llama 3.3 70B is smaller: it needs about 47.4 GB of memory at 4-bit, against 50.8 GB for Qwen3-Next 80B-A3B Thinking. Only Llama 3.3 70B has a hosted API on OpenRouter ($0.15 per million tokens); the other has to be self-hosted.
Pick Qwen3-Next 80B-A3B Thinking if…
- you want the strongest model overall
- you work with long documents
- you need a permissive license (Apache-2.0)
Pick Llama 3.3 70B if…
- you have limited memory (about 47.4 GB at 4-bit)
- you want a hosted API rather than running it yourself
- you want the more widely used model (more quantized builds and community support)
Specifications
| Qwen3-Next 80B-A3B Thinking | Llama 3.3 70B | |
|---|---|---|
| Small LM Index | 63.3 (likely 59–67) | 40.8 (likely 31–51) |
| Lab | Alibaba (Qwen) · China | Meta · United States |
| Released | 2025-09-11 | 2024-12-06 |
| Parameters | 80B (3B active, MoE) | 70.6B (dense) |
| Memory at 4-bit | ~50.8 GB | ~47.4 GB |
| Context window | 262K tokens | 128K tokens |
| Input | text | text |
| Reasoning | Always thinks | No thinking |
| License | Apache-2.0 | Llama 3.3 Community |
| API price / 1M tokens | Self-host only | $0.15 ($0.10 in, $0.32 out) |
| Hugging Face downloads (30 days) | 43.8K | 363.3K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Qwen3-Next 80B-A3B Thinking | Llama 3.3 70B |
|---|---|---|
| MMLU-Pro Knowledge | 82.7 | 68.9 |
| GPQA Diamond Knowledge | 77.2 | 50.5 |
| AIME Math | 87.8 | ≈ 54 |
| LiveCodeBench Coding | 68.7 | ≈ 45 |
| IFBench Instruction following | 61.5 | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Qwen3-Next 80B-A3B Thinking or Llama 3.3 70B?
Qwen3-Next 80B-A3B Thinking scores higher on the Small LM Index: 63.3 vs 40.8. On the 2 benchmarks both labs report, Qwen3-Next 80B-A3B Thinking wins 2 and Llama 3.3 70B wins 0.
Which is cheaper to run?
Only Llama 3.3 70B has a hosted API on OpenRouter ($0.15 per million tokens); the other has to be self-hosted. Llama 3.3 70B is smaller: it needs about 47.4 GB of memory at 4-bit, against 50.8 GB for Qwen3-Next 80B-A3B Thinking.
Which has the longer context window?
Qwen3-Next 80B-A3B Thinking has the longer context window: 262K tokens against 128K.
Can I use Qwen3-Next 80B-A3B Thinking and Llama 3.3 70B commercially?
Qwen3-Next 80B-A3B Thinking is released under Apache-2.0 and Llama 3.3 70B under Llama 3.3 Community. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.
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