Llama 3.1 405B Instruct vs Qwen3.5-9B
Llama 3.1 405B Instruct (2024) and Qwen3.5-9B (2026) are compact production models from AI at Meta and Alibaba. Llama 3.1 405B Instruct ships a 128K-token context window, while Qwen3.5-9B ships a 262K-token context window. On pricing, Qwen3.5-9B costs $0.1/1M input tokens versus $2.4/1M 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 ~2300% cheaper at $0.1/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B Instruct | Qwen3.5-9B |
|---|---|---|
| Decision fit | RAG, Long context, and Classification | RAG, Agents, and Long context |
| Context window | 128K | 262K |
| Cheapest output | $2.4/1M tokens | $0.15/1M tokens |
| Provider routes | 11 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling 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 prices on this page.
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route: AWS Bedrock
Qwen3.5-9B
$118
Cheapest tracked route: Together AI
Estimated monthly gap: $2,403. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Qwen3.5-9B is $2.25/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $2.25/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2026-03-02 |
| Context window | 128K | 262K |
| Parameters | 405B | 9B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Llama 3.1 405B Instruct | Qwen3.5-9B |
|---|---|---|
| Input price | $2.4/1M tokens | $0.1/1M tokens |
| Output price | $2.4/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 405B Instruct | Qwen3.5-9B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | 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, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. Both models share 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 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens, while Qwen3.5-9B lists $0.1/1M 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 $2.29 per million blended tokens. Availability is 11 providers versus 3, so concentration risk also matters.
Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-9B when long-context analysis, larger context windows, and lower input-token cost 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 3.1 405B Instruct or Qwen3.5-9B?
Qwen3.5-9B supports 262K tokens, while Llama 3.1 405B Instruct supports 128K 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 3.1 405B Instruct or Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Qwen3.5-9B costs $0.1/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.1 405B Instruct or Qwen3.5-9B open source?
Llama 3.1 405B Instruct 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 3.1 405B Instruct 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 3.1 405B Instruct or Qwen3.5-9B?
Qwen3.5-9B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.1 405B Instruct and Qwen3.5-9B?
Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. 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: 2026-05-16. Data sourced from public model cards and provider documentation.