Model comparison
Llama 4 Scout vs Qwen2.5-Max
- Input
- $0.18
- Output
- $0.59
- Context
- 10M
- Released
- 2025-04-05
- Input
- $1.60 / 1M tokens
- Output
- $6.40 / 1M tokens
- Context
- ~32K tokens
- Released
- 2025-01-29
Qwen2.5-Max scores higher on 3 of the 3 benchmarks both models report; Llama 4 Scout is cheaper on input tokens ($0.2 vs $1.6 per 1M, 8.9×); Llama 4 Scout has the larger context window (10M vs 32K); Llama 4 Scout ships open weights while Qwen2.5-Max is API-only.
Specs and pricing side by side
| Spec | Llama 4 Scout | Qwen2.5-Max |
|---|---|---|
| Maker | Meta | Alibaba (Qwen) |
| Released | 2025-04-05 | 2025-01-29 |
| Context window | 10M | ~32K tokens |
| Max output | not published | Not officially disclosed |
| Input price | $0.18 | $1.60 / 1M tokens |
| Output price | $0.59 | $6.40 / 1M tokens |
| Parameters | 109B total · 17B active (16 experts) | Not disclosed (Mixture-of-Experts; total parameter count never published by Alibaba) |
| License | Llama 4 Community License Agreement | Proprietary (closed weights). Unlike the smaller Apache-2.0 open-weight Qwen2.5 models, the Max tier is API-only. |
| Weights | Open weights | API only |
| Modalities | Text, Vision | text input, text output |
| Knowledge cutoff | 2024-08 | Not officially disclosed |
Benchmarks both models report
| Benchmark | Llama 4 Scout | Qwen2.5-Max |
|---|---|---|
| MMLU Pro | 74.3% | 76.1% |
| GPQA Diamond | 57.2% | 60.1% |
| LiveCodeBench | 32.8% | 38.7% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Llama 4 Scout if…
- Cost matters: input tokens cost 8.9× less ($0.2 vs $1.6 per 1M).
- You need the longer context (10M vs 32K).
- You want to self-host or fine-tune (open weights, Llama 4 Community License Agreement).
- You need Text / Vision input, which Qwen2.5-Max lacks.
- Your use case is: long-document and large-codebase analysis at up to 10M-token context.
Pick Qwen2.5-Max if…
- You care about MMLU Pro, GPQA Diamond, LiveCodeBench (it scores higher on 3 shared benchmarks).
- You need text input / text output input, which Llama 4 Scout lacks.
- Your use case is: general-purpose chat assistants and Q&A in English and Chinese.
FAQ
Which is better, Llama 4 Scout or Qwen2.5-Max?
Qwen2.5-Max scores higher on 3 of the 3 benchmarks both models report; Llama 4 Scout is cheaper on input tokens ($0.2 vs $1.6 per 1M, 8.9×); Llama 4 Scout has the larger context window (10M vs 32K); Llama 4 Scout ships open weights while Qwen2.5-Max is API-only. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Llama 4 Scout?
Llama 4 Scout: $0.18 input, $0.59 output. Qwen2.5-Max: $1.60 / 1M tokens input, $6.40 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Llama 4 Scout and Qwen2.5-Max?
Llama 4 Scout offers 10M; Qwen2.5-Max offers ~32K tokens with up to Not officially disclosed output.
Is Llama 4 Scout newer than Qwen2.5-Max?
Llama 4 Scout was released 2025-04-05; Qwen2.5-Max was released 2025-01-29.