AI model comparison
Qwen3 14B vs Llama 4 Scout
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen
Qwen3 14B
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue.
- Input / 1M
- $0.12
- Output / 1M
- $0.24
- Context
- 41K
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
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Llama 4 Scout
1.0x cheaper for a typical chat
Higher intelligence score
Qwen3 14B
8.2 vs 8.1 on Artificial Analysis
Larger context window
Llama 4 Scout
1.31M vs 41K tokens
Newer release
Qwen3 14B
Released April 28, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 14B8.2Coding index
Qwen3 14B13.8Agentic index
Qwen3 14B0.9Pricing
Qwen3 14B vs Llama 4 Scout API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 14B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.12 | $0.10 |
| Output tokensPer 1M tokens | $0.24 | $0.30 |
| 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
Qwen3 14B$0.36Coding task
30K in, 4K out
Qwen3 14B$4.56Long document summary
150K in, 2K out
Qwen3 14B$18.48Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3 14B | |
|---|---|---|
| Context window | 41K tokens | 1.31M tokens |
| Max output | 16K tokens | 16K tokens |
| Input types | Text | Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | April 28, 2025 | April 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 14B | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | 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.
Qwen3 14BView full model details- Qwen3 14B vs Gemini 2.5 Flash Lite
- Qwen3 14B vs Qwen3 30B A3B Instruct 2507
- Qwen3 14B vs Qwen3 Coder Next
- Qwen3 14B vs Qwen3 Coder 30B A3B Instruct
- Qwen3 14B vs Qwen3 32B
- Qwen3 14B vs Nemotron 3 Nano 30B A3B
- Qwen3 14B vs Qwen3 VL 30B A3B Instruct
- Qwen3 14B vs Qwen2.5 72B Instruct
- Qwen3 14B vs Qwen3 30B A3B
- Qwen3 14B vs Nova Lite 1.0
- Qwen3 14B vs Reka Flash 3
- 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 Qwen2.5 72B Instruct
- 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
Our take
Llama 4 Scout is 1.0x cheaper for a typical chat. Qwen3 14B scores higher on the Artificial Analysis Intelligence Index (8.2 vs 8.1). Llama 4 Scout has the larger context window (1.31M vs 41K 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 Qwen3 14B or Llama 4 Scout 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 Qwen3 14B costs $0.12 per 1M input tokens and $0.24 per 1M output tokens.
Which has a bigger context window, Qwen3 14B or Llama 4 Scout?
Llama 4 Scout supports up to 1.31M tokens of context, compared with 41K for Qwen3 14B.
Is Qwen3 14B smarter than Llama 4 Scout?
On the Artificial Analysis Intelligence Index, Qwen3 14B scores 8.2 and Llama 4 Scout scores 8.1, putting Qwen3 14B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3 14B and Llama 4 Scout at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 14B and Llama 4 Scout answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3 14B and Llama 4 Scout at the same time. Compare the answers side by side and keep the best one.