Llama 3.1 405B vs Qwen-Max
Llama 3.1 405B (2024) and Qwen-Max (2024) are compact production models from AI at Meta and Alibaba. Llama 3.1 405B ships a 128K-token context window, while Qwen-Max ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Llama 3.1 405B is safer overall; choose Qwen-Max when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B | Qwen-Max |
|---|---|---|
| Decision fit | Coding, Long context, and Classification | RAG, Long context, and Vision |
| Context window | 128K | 128K |
| Cheapest output | - | $4.16/1M tokens |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.1 405B for Coding, Long context, and Classification.
- Qwen-Max has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen-Max uniquely exposes Vision and Structured outputs in local model data.
- Local decision data tags Qwen-Max for RAG, Long context, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.1 405B
Unavailable
No complete token price in local provider data
Qwen-Max
$1,872
Cheapest tracked route: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3.1 405B and Qwen-Max; plan for SDK, billing, or endpoint changes.
- Qwen-Max adds Vision and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Qwen-Max and Llama 3.1 405B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2024-05-11 |
| Context window | 128K | 128K |
| Parameters | 405B | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.1 405B | Qwen-Max |
|---|---|---|
| Input price | - | $1.04/1M tokens |
| Output price | - | $4.16/1M tokens |
| Providers | - |
Capabilities
| Capability | Llama 3.1 405B | Qwen-Max |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | 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: Qwen-Max and structured outputs: Qwen-Max. Both models share the core language-model surface, 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.
Pricing coverage is uneven: Llama 3.1 405B has no token price sourced yet and Qwen-Max has $1.04/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 405B when provider fit are central to the workload. Choose Qwen-Max when vision-heavy evaluation 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Llama 3.1 405B or Qwen-Max?
Llama 3.1 405B supports 128K tokens, while Qwen-Max supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3.1 405B or Qwen-Max open source?
Llama 3.1 405B is listed under Open Source. Qwen-Max 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 or Qwen-Max?
Qwen-Max 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 structured outputs, Llama 3.1 405B or Qwen-Max?
Qwen-Max has the clearer documented structured outputs signal in this comparison. If structured outputs 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 and Qwen-Max?
Llama 3.1 405B is available on the tracked providers still being sourced. Qwen-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Llama 3.1 405B over Qwen-Max?
Llama 3.1 405B is safer overall; choose Qwen-Max when vision-heavy evaluation matters. If your workload also depends on provider fit, start with Llama 3.1 405B; if it depends on vision-heavy evaluation, run the same evaluation with Qwen-Max.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.