AI model comparison
Qwen3 30B A3B Instruct 2507 vs Llama 4 Scout
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference.
- Input / 1M
- $0.10
- Output / 1M
- $0.30
- Context
- 262K
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
Tie
Same price for a typical chat
Higher intelligence score
Llama 4 Scout
8.1 vs 7.5 on Artificial Analysis
Larger context window
Llama 4 Scout
1.31M vs 262K tokens
Newer release
Qwen3 30B A3B Instruct 2507
Released July 29, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3 30B A3B Instruct 25077.5Coding index
Qwen3 30B A3B Instruct 2507Not availableAgentic index
Qwen3 30B A3B Instruct 2507Not availablePricing
Qwen3 30B A3B Instruct 2507 vs Llama 4 Scout API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3 30B A3B Instruct 2507 | |
|---|---|---|
| Input tokensPer 1M tokens | $0.10 | $0.10 |
| Output tokensPer 1M tokens | $0.30 | $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 30B A3B Instruct 2507$0.35Coding task
30K in, 4K out
Qwen3 30B A3B Instruct 2507$4.20Long document summary
150K in, 2K out
Qwen3 30B A3B Instruct 2507$15.60Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3 30B A3B Instruct 2507 | |
|---|---|---|
| Context window | 262K tokens | 1.31M tokens |
| Max output | 236K 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 | July 29, 2025 | April 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | Qwen3 30B A3B Instruct 2507 | |
|---|---|---|
| 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.
Qwen3 30B A3B Instruct 2507View full model details- Qwen3 30B A3B Instruct 2507 vs Gemini 2.5 Flash Lite
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- Qwen3 30B A3B Instruct 2507 vs Qwen3 Coder 30B A3B Instruct
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- Qwen3 30B A3B Instruct 2507 vs Nemotron 3 Nano 30B A3B
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- Qwen3 30B A3B Instruct 2507 vs Qwen3 30B A3B
- Qwen3 30B A3B Instruct 2507 vs Solar Pro 3
- Qwen3 30B A3B Instruct 2507 vs Llama 3.1 70B Instruct
- Qwen3 30B A3B Instruct 2507 vs Qwen2.5 Coder 32B Instruct
- Qwen3 30B A3B Instruct 2507 vs Reka Flash 3
- Qwen3 30B A3B Instruct 2507 vs Llama 3.2 3B Instruct
- Llama 4 Scout vs Gemini 2.5 Flash Lite
- Llama 4 Scout vs Llama 3.1 8B Instruct
- 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 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 scores higher on the Artificial Analysis Intelligence Index (8.1 vs 7.5). Llama 4 Scout has the larger context window (1.31M vs 262K 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 30B A3B Instruct 2507 or Llama 4 Scout cheaper?
Qwen3 30B A3B Instruct 2507 and Llama 4 Scout cost the same for a typical chat (2K input tokens and 500 output tokens). Qwen3 30B A3B Instruct 2507 costs $0.10 per 1M input tokens and $0.30 per 1M output tokens, and Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens.
Which has a bigger context window, Qwen3 30B A3B Instruct 2507 or Llama 4 Scout?
Llama 4 Scout supports up to 1.31M tokens of context, compared with 262K for Qwen3 30B A3B Instruct 2507.
Is Qwen3 30B A3B Instruct 2507 smarter than Llama 4 Scout?
On the Artificial Analysis Intelligence Index, Qwen3 30B A3B Instruct 2507 scores 7.5 and Llama 4 Scout scores 8.1, putting Llama 4 Scout ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Qwen3 30B A3B Instruct 2507 and Llama 4 Scout at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 30B A3B Instruct 2507 and Llama 4 Scout answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Qwen3 30B A3B Instruct 2507 and Llama 4 Scout at the same time. Compare the answers side by side and keep the best one.