ModelRefs / Llama 4 Scout vs Qwen2.5-VL 72B
Llama 4 Scout vs Qwen2.5-VL 72B
Llama 4 Scout vs Qwen2.5-VL 72B: 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.
Qwen2.5-VL 72B: Qwen2.5-VL 72B Instruct is the largest vision-language model in Alibaba's Qwen2.5-VL line, accepting images and video alongside text. Qwen highlights comprehension of videos over an hour long, structured extraction from documents such as invoices, forms and tables, visual grounding returned as bounding boxes or points, and agentic computer and phone use. The published config sets a 32,768-token context, and Qwen advises against YaRN extension here because it degrades temporal and spatial localisation.
Context window: Llama 4 Scout accepts up to 10,000,000 tokens, Qwen2.5-VL 72B up to 128,000. Confirm the limit for your specific deployment channel before relying on it.
Llama 4 Scout vs Qwen2.5-VL 72B at a glance
| Attribute | Llama 4 Scout | Qwen2.5-VL 72B |
|---|---|---|
| Provider | Meta | Alibaba |
| Released | 2025-04-01 | 2025-01-26 |
| Context window | 10,000,000 tokens | 128,000 tokens |
| Input price | $0.11/M tokens | Free / self-hosted |
| Output price | $0.34/M tokens | Free / self-hosted |
| Licence | Llama-4-Community | Qwen License |
| Self-hostable | Yes, open weights | Yes, open weights |
| Modalities | text, vision | text, vision |
Benchmarks reported for both
| Benchmark | Llama 4 Scout | Qwen2.5-VL 72B | Reported |
|---|---|---|---|
| DocVQA (anls) | 94.4 | 96.4 | 2025-04-01 / 2025-01-26 |
| MathVista (accuracy) | 73.7 | 74.8 | 2025-04-01 / 2025-02-19 |
| MMMU (accuracy) | 73.4 | 70.2 | 2025-04-01 / 2025-01-26 |
Each row compares the same benchmark, the same reported metric, and the same task set. Scores are as published by their cited sources on the dates shown. Different runs still use different harnesses and prompts, so treat these as directional evidence rather than a head-to-head result.
Where they differ most
- Reasoning: Llama 4 Scout 62%, Qwen2.5-VL 72B 75%. Qwen2.5-VL 72B leads on this dimension.
- Cost Efficiency: Llama 4 Scout 94%, Qwen2.5-VL 72B 100%. Qwen2.5-VL 72B leads on this dimension.
- Multimodal: Llama 4 Scout 74%, Qwen2.5-VL 72B 75%. Qwen2.5-VL 72B leads on this dimension.
- OCR: Llama 4 Scout 87%, Qwen2.5-VL 72B 87%. 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 Qwen2.5-VL 72B.
Frequently asked questions
Which is better, Llama 4 Scout or Qwen2.5-VL 72B?
Llama 4 Scout and Qwen2.5-VL 72B target different workloads — see the benchmark and pricing tables for a side-by-side answer.
Is Llama 4 Scout cheaper than Qwen2.5-VL 72B?
Compare $0.00011 vs $0.00000 on this page.