Llama 3.2 11B Instruct vs Llama 3.1 405B Instruct
Llama 3.2 11B Instruct (2025) and Llama 3.1 405B Instruct (2024) are compact production models from AI at Meta. Llama 3.2 11B Instruct ships a not-yet-sourced context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, Llama 3.2 11B Instruct costs $0.2/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.2 11B Instruct is ~1100% cheaper at $0.2/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3.2 11B Instruct | Llama 3.1 405B Instruct |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | RAG, Long context, and Classification |
| Context window | — | 128K |
| Cheapest output | $0.27/1M tokens | $2.4/1M tokens |
| Provider routes | 1 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Local decision data tags Llama 3.2 11B Instruct for Classification and JSON / Tool use.
- Llama 3.1 405B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.2 11B Instruct
$228
Cheapest tracked route: AWS Bedrock
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $2,293. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $2.13/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.2 11B Instruct is $2.13/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2024-07-23 |
| Context window | — | 128K |
| Parameters | — | 405B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Llama 3.2 11B Instruct | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.2/1M tokens | $2.4/1M tokens |
| Output price | $0.27/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.2 11B Instruct | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Llama 3.2 11B Instruct lists $0.2/1M input and $0.27/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 11B Instruct lower by about $2.18 per million blended tokens. Availability is 1 providers versus 11, so concentration risk also matters.
Choose Llama 3.2 11B Instruct when provider fit and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when provider fit 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 is cheaper, Llama 3.2 11B Instruct or Llama 3.1 405B Instruct?
Llama 3.2 11B Instruct is cheaper on tracked token pricing. Llama 3.2 11B Instruct costs $0.2/1M input and $0.27/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.2 11B Instruct or Llama 3.1 405B Instruct open source?
Llama 3.2 11B Instruct is listed under Proprietary. Llama 3.1 405B Instruct is listed under Open Source. 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 structured outputs, Llama 3.2 11B Instruct or Llama 3.1 405B Instruct?
Both Llama 3.2 11B Instruct and Llama 3.1 405B Instruct 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 3.2 11B Instruct and Llama 3.1 405B Instruct?
Llama 3.2 11B Instruct is available on AWS Bedrock. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.2 11B Instruct over Llama 3.1 405B Instruct?
Llama 3.2 11B Instruct is ~1100% cheaper at $0.2/1M; pay for Llama 3.1 405B Instruct only for provider fit. If your workload also depends on provider fit, start with Llama 3.2 11B Instruct; if it depends on provider fit, run the same evaluation with Llama 3.1 405B Instruct.
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Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.