Llama 3.1 405B Instruct vs Qwen-Max
Llama 3.1 405B Instruct (2024) and Qwen-Max (2024) are compact production models from AI at Meta and Alibaba. Llama 3.1 405B Instruct ships a 128k-token context window, while Qwen-Max ships a 128k-token context window. On pricing, Qwen-Max costs $1.04/1M input tokens versus $2.40/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Qwen-Max is ~131% cheaper at $1.04/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B Instruct | Qwen-Max |
|---|---|---|
| Best for | provider-routed production | multimodal apps |
| Decision fit | RAG, Long context, and Classification | RAG, Long context, and Vision |
| Context window | 128k | 128k |
| Cheapest output | $2.40/1M tokens | $4.16/1M tokens |
| Provider routes | 11 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Llama 3.1 405B Instruct has the lower cheapest tracked output price at $2.40/1M tokens.
- 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.
- Qwen-Max uniquely exposes Vision 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 route or tier on this page.
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route/tier: AWS Bedrock
Qwen-Max
$1,872
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $648. 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 3.1 405B Instruct and Qwen-Max; plan for SDK, billing, or endpoint changes.
- Qwen-Max is $1.76/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen-Max adds Vision in local capability data.
- No overlapping tracked provider route is sourced for Qwen-Max and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.1 405B Instruct is $1.76/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision 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 | Llama 3 Community | Qianwen(needs verification) |
| Openness | Open weights | Open weights |
| Weights | Available | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.1 405B Instruct | Qwen-Max |
|---|---|---|
| Input price | $2.40/1M tokens | $1.04/1M tokens |
| Output price | $2.40/1M tokens | $4.16/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.1 405B Instruct | Qwen-Max |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: Qwen-Max. 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 $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider, while Qwen-Max lists $1.04/1M input and $4.16/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen-Max lower by about $0.42 per million blended tokens. Availability is 11 providers versus 1, so concentration risk also matters.
Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are central to the workload. Choose Qwen-Max when vision-heavy evaluation 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. 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 Instruct or Qwen-Max?
Llama 3.1 405B Instruct 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.
Which is cheaper, Llama 3.1 405B Instruct or Qwen-Max?
Qwen-Max is cheaper on tracked token pricing. Llama 3.1 405B Instruct costs $2.40/1M input and $2.40/1M output tokens. Qwen-Max costs $1.04/1M input and $4.16/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.1 405B Instruct or Qwen-Max open source?
Llama 3.1 405B Instruct is listed under Llama 3 Community. Qwen-Max is listed under Qianwen. 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 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 Instruct or Qwen-Max?
Both Llama 3.1 405B Instruct and Qwen-Max expose structured outputs. 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 3.1 405B Instruct and Qwen-Max?
Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Qwen-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.