Llama 4 Scout 17B vs Qwen3.5-9B
Llama 4 Scout 17B (2025) and Qwen3.5-9B (2026) are general-purpose language models from AI at Meta and Alibaba. Llama 4 Scout 17B ships a 10m-token context window, while Qwen3.5-9B ships a 262k-token context window. On pricing, Qwen3.5-9B costs $0.10/1M input tokens versus $0.17/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-9B is ~70% cheaper at $0.10/1M; pay for Llama 4 Scout 17B only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Llama 4 Scout 17B | Qwen3.5-9B |
|---|---|---|
| Best for | multimodal apps and long-context analysis | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | RAG, Long context, and Vision | RAG, Agents, and Long context |
| Context window | 10m | 262k |
| Cheapest output | $0.66/1M tokens | $0.15/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 4 Scout 17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Llama 4 Scout 17B for RAG, Long context, and Vision.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Vision, Function calling, and Tool use in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 4 Scout 17B
$301
Cheapest tracked route/tier: AWS Bedrock
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $184. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Llama 4 Scout 17B and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-9B is $0.51/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Function calling, and Tool use in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-9B and Llama 4 Scout 17B; plan for SDK, billing, or endpoint changes.
- Llama 4 Scout 17B is $0.51/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-10-01 | 2026-03-02 |
| Context window | 10m | 262k |
| Parameters | 17 | 9B |
| Architecture | - | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama 4 Scout 17B | Qwen3.5-9B |
|---|---|---|
| Input price | $0.17/1M tokens | $0.10/1M tokens |
| Output price | $0.66/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Llama 4 Scout 17B | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. Both models share multimodal input and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 4 Scout 17B lists $0.17/1M input and $0.66/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $0.20 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.
Choose Llama 4 Scout 17B when long-context analysis and larger context windows are central to the workload. Choose Qwen3.5-9B when vision-heavy evaluation, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Llama 4 Scout 17B or Qwen3.5-9B?
Llama 4 Scout 17B supports 10m tokens, while Qwen3.5-9B supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 4 Scout 17B or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Llama 4 Scout 17B costs $0.17/1M input and $0.66/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 4 Scout 17B or Qwen3.5-9B open source?
Llama 4 Scout 17B is listed under Open Source. Qwen3.5-9B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Llama 4 Scout 17B or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Llama 4 Scout 17B or Qwen3.5-9B?
Both Llama 4 Scout 17B and Qwen3.5-9B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 4 Scout 17B and Qwen3.5-9B?
Llama 4 Scout 17B is available on AWS Bedrock. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.