Qwen3.5-Flash vs Llama 4 Scout
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Qwen3.5-Flash | Llama 4 Scout |
|---|---|---|
| Provider | Alibaba | Meta |
| Input Price (1M) | $0.10 | $0.10 |
| Output Price (1M) | $0.40 | $0.30 |
| Context Window | 1,000,000 | 10,000,000 |
Verdict
Qwen3.5-Flash costs $0.10 per 1M input tokens and $0.40 per 1M output tokens. Llama 4 Scout costs $0.10 per 1M input tokens and $0.30 per 1M output tokens. Qwen3.5-Flash and Llama 4 Scout have identical input token pricing. For output tokens, Llama 4 Scout is the more affordable option at $0.30/1M vs $0.40.
On context window, Llama 4 Scout supports 10,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Qwen3.5-Flash
- ✓ You are already integrated with Alibaba
When to choose Llama 4 Scout
- ✓ Your workload is output-heavy — Llama 4 Scout generates text cheaper
- ✓ You need a larger context window (10,000,000 tokens)
- ✓ You are already integrated with Meta
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Qwen3.5-Flash cheaper than Llama 4 Scout? ▼
Qwen3.5-Flash and Llama 4 Scout have identical input token pricing at $0.10/1M tokens.
What is the context window of Qwen3.5-Flash vs Llama 4 Scout? ▼
Qwen3.5-Flash has a 1,000,000-token context window. Llama 4 Scout has a 10,000,000-token context window. Llama 4 Scout supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Qwen3.5-Flash or Llama 4 Scout? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Qwen3.5-Flash is the cheaper option. For maximum context length, Llama 4 Scout supports 10,000,000 tokens. Use the comparison table above to find the right fit for your workload.