AI model comparison
Llama 4 Scout vs Qwen2.5 72B Instruct
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Meta
Llama 4 Scout
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B.
- Input / 1M
- $0.10
- Output / 1M
- $0.30
- Context
- 1.31M
Qwen2.5 72B is the latest series of Qwen large language models.
- Input / 1M
- $0.36
- Output / 1M
- $0.40
- Context
- 33K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Llama 4 Scout
2.6x cheaper for a typical chat
Higher intelligence score
Llama 4 Scout
8.1 vs 7.7 on Artificial Analysis
Larger context window
Llama 4 Scout
1.31M vs 33K tokens
Newer release
Llama 4 Scout
Released April 5, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen2.5 72B Instruct7.7Coding index
Qwen2.5 72B InstructNot availableAgentic index
Qwen2.5 72B InstructNot availablePricing
Llama 4 Scout vs Qwen2.5 72B Instruct API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen2.5 72B Instruct | |
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.36 |
| Output tokensPer 1M tokens | $0.30 | $0.40 |
| Cached input (read)Per 1M tokens | Not available | Not available |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen2.5 72B Instruct$0.92Coding task
30K in, 4K out
Qwen2.5 72B Instruct$12.40Long document summary
150K in, 2K out
Qwen2.5 72B Instruct$54.80Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen2.5 72B Instruct | |
|---|---|---|
| Context window | 1.31M tokens | 33K tokens |
| Max output | 16K tokens | 16K tokens |
| Input types | Image, Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 5, 2025 | September 19, 2024 |
Features
Supported features
API features available for each model.
| Metric | Qwen2.5 72B Instruct | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Not supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- Llama 4 Scout vs Gemini 2.5 Flash Lite
- Llama 4 Scout vs Llama 3.1 8B Instruct
- Llama 4 Scout vs Qwen3 30B A3B Instruct 2507
- Llama 4 Scout vs Llama 3.3 70B Instruct
- Llama 4 Scout vs GPT-4.1 Nano
- Llama 4 Scout vs Llama 4 Maverick
- Llama 4 Scout vs Qwen3 32B
- Llama 4 Scout vs Nemotron 3 Nano 30B A3B
- Llama 4 Scout vs Qwen3 14B
- Llama 4 Scout vs Nova Lite 1.0
- Llama 4 Scout vs Llama 3.1 70B Instruct
- Llama 4 Scout vs Llama 3.2 3B Instruct
- Llama 4 Scout vs Llama 3.2 1B Instruct
Qwen2.5 72B InstructView full model details- Qwen2.5 72B Instruct vs Gemini 2.5 Flash Lite
- Qwen2.5 72B Instruct vs Gemma 3 27B
- Qwen2.5 72B Instruct vs Qwen3 30B A3B Instruct 2507
- Qwen2.5 72B Instruct vs Llama 3.3 70B Instruct
- Qwen2.5 72B Instruct vs Qwen3 Coder 30B A3B Instruct
- Qwen2.5 72B Instruct vs Qwen3 32B
- Qwen2.5 72B Instruct vs Qwen3 14B
- Qwen2.5 72B Instruct vs GPT-4.1 Nano
- Qwen2.5 72B Instruct vs Qwen3 VL 30B A3B Instruct
- Qwen2.5 72B Instruct vs Solar Pro 3
- Qwen2.5 72B Instruct vs Qwen3 30B A3B
- Qwen2.5 72B Instruct vs Qwen3 VL 8B Instruct
- Qwen2.5 72B Instruct vs Qwen2.5 Coder 32B Instruct
- Qwen2.5 72B Instruct vs Llama 3.1 70B Instruct
Our take
Llama 4 Scout is 2.6x cheaper for a typical chat. Llama 4 Scout scores higher on the Artificial Analysis Intelligence Index (8.1 vs 7.7). Llama 4 Scout has the larger context window (1.31M vs 33K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Llama 4 Scout or Qwen2.5 72B Instruct cheaper?
Llama 4 Scout is cheaper for a typical chat (2K input tokens and 500 output tokens). Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens, while Qwen2.5 72B Instruct costs $0.36 per 1M input tokens and $0.40 per 1M output tokens.
Which has a bigger context window, Llama 4 Scout or Qwen2.5 72B Instruct?
Llama 4 Scout supports up to 1.31M tokens of context, compared with 33K for Qwen2.5 72B Instruct.
Is Llama 4 Scout smarter than Qwen2.5 72B Instruct?
On the Artificial Analysis Intelligence Index, Llama 4 Scout scores 8.1 and Qwen2.5 72B Instruct scores 7.7, putting Llama 4 Scout ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Llama 4 Scout and Qwen2.5 72B Instruct at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Llama 4 Scout and Qwen2.5 72B Instruct answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Llama 4 Scout and Qwen2.5 72B Instruct at the same time. Compare the answers side by side and keep the best one.