ModelRefs / Llama 4 Scout vs QwQ 32B
Llama 4 Scout vs QwQ 32B
Llama 4 Scout vs QwQ 32B: side-by-side benchmarks, pricing, context windows, coding ability and deployment. Pick the right model for your stack.
Overview
Llama 4 Scout: Llama 4 Scout is Meta's efficiency-focused open-weights model with an exceptionally large 10M-token context window and vision support. It is optimized for long-document retrieval and low-cost inference at scale.
QwQ 32B: QwQ 32B is the reasoning model of Alibaba's Qwen series, a 32.5-billion-parameter causal language model (31.0 billion excluding embeddings) with 64 layers and grouped-query attention using 40 query and 8 key-value heads. It is built to work through a problem before answering rather than responding directly. The full context length is 131,072 tokens, though Qwen notes that prompts beyond 8,192 tokens require YaRN to be enabled. Released under Apache 2.0.
Context window: Llama 4 Scout accepts up to 10,000,000 tokens, QwQ 32B up to 131,072. Confirm the limit for your specific deployment channel before relying on it.
Llama 4 Scout vs QwQ 32B at a glance
| Attribute | Llama 4 Scout | QwQ 32B |
|---|---|---|
| Provider | Meta | Alibaba |
| Released | 2025-04-01 | 2025-03-06 |
| Context window | 10,000,000 tokens | 131,072 tokens |
| Input price | $0.11/M tokens | $0.15/M tokens |
| Output price | $0.34/M tokens | $0.6/M tokens |
| Licence | Llama-4-Community | Apache-2.0 |
| Self-hostable | Yes, open weights | Yes, open weights |
| Modalities | text, vision | text |
Reported on different variants
Both models are measured on these benchmarks, but not on the same variant of them, so the two numbers are not a like-for-like comparison. Each side is shown with the variant it was measured on.
| Benchmark | Llama 4 Scout | QwQ 32B | Reported |
|---|---|---|---|
| LiveCodeBench | 32.8 (accuracy) | 63.4 (avg@8) | 2025-04-01 |
A different task set or a different reported metric can move a score by more than the gap between two models. Use these as two separate findings, not as a ranking.
Where they differ most
- Coding: Llama 4 Scout 33%, QwQ 32B 63%. QwQ 32B leads on this dimension.
- Cost Efficiency: Llama 4 Scout 94%, QwQ 32B 91%. Llama 4 Scout leads on this dimension.
Capability scores are ModelRefs' own derived signals, not vendor claims or benchmark results. Validate against your own workload before relying on them.
Continue your research
Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Llama 4 Scout vs QwQ 32B.
Frequently asked questions
Which is better, Llama 4 Scout or QwQ 32B?
Llama 4 Scout and QwQ 32B target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is Llama 4 Scout cheaper than QwQ 32B?
Compare $0.00011 vs $0.00015 on this page.