Llama 4 (Meta) vs Qwen (Alibaba)

Which one should you pick? Here's the full breakdown.

Llama 4 (Meta)

B
7.9/10

Meta's open-weights flagship family -- Scout (10M context), Maverick (multimodal 400B MoE), Behemoth in preview

Our Pick

Qwen (Alibaba)

A
8.8/10

Alibaba's open-weights family -- Qwen3.5, Qwen3-Coder-Next, Qwen3-VL, Qwen3-Max. Apache 2.0 flagship sizes.

CategoryLlama 4 (Meta)Qwen (Alibaba)
Ease of Use5.07.0
Output Quality8.59.0
Value9.010.0
Features9.09.0
Overall7.98.8

Pricing Comparison

FeatureLlama 4 (Meta)Qwen (Alibaba)
Free TierYesYes
Starting Price$0$0

Benchmark Head-to-Head

Llama 4 Maverick (17B/400B MoE) vs Qwen3.5-397B MoE

BenchmarkLlama 4 (Meta)Qwen (Alibaba)
MMLU-Pro80.5%83.5%
GPQA Diamond69.8%78.2%
HumanEval88%92.5%

Which Should You Pick?

Pick Llama 4 (Meta) if...

Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (Scout), or multimodal (Maverick). Safe default choice given the ecosystem.

Visit Llama 4 (Meta)

Pick Qwen (Alibaba) if...

  • Easier to use (7 vs 5)
  • Better value for money (10/10)
  • Stronger on graduate-level science questions (+8.4% on GPQA Diamond)

Developers who want frontier-tier open weights with Apache 2.0 licensing. Qwen3-Coder-Next is arguably the best local coding model; Qwen3.5-397B is a top-3 open generalist.

Visit Qwen (Alibaba)

Our Verdict

Qwen (Alibaba) edges out Llama 4 (Meta) with a 8.8 vs 7.9 overall score. Both are solid picks, but Qwen (Alibaba) has the advantage in output quality.