Llama 3.2 11B Instruct vs Qwen3-Next-80B-A3B
Llama 3.2 11B Instruct (2025) and Qwen3-Next-80B-A3B (2025) are compact production models from AI at Meta and Alibaba. Llama 3.2 11B Instruct ships a 128k-token context window, while Qwen3-Next-80B-A3B ships a not-yet-sourced context window. On pricing, Qwen3-Next-80B-A3B costs $0.10/1M input tokens versus $0.20/1M 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.
Qwen3-Next-80B-A3B is ~105% cheaper at $0.10/1M; pay for Llama 3.2 11B Instruct only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Llama 3.2 11B Instruct | Qwen3-Next-80B-A3B |
|---|---|---|
| Best for | multimodal apps | provider-routed production |
| Decision fit | RAG, Long context, and Vision | Classification and JSON / Tool use |
| Context window | 128k | — |
| Cheapest output | $0.27/1M tokens | $0.78/1M tokens |
| Provider routes | 1 tracked | 4 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Llama 3.2 11B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Llama 3.2 11B Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Llama 3.2 11B Instruct for RAG, Long context, and Vision.
- Qwen3-Next-80B-A3B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Qwen3-Next-80B-A3B for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.2 11B Instruct
$228
Cheapest tracked route/tier: AWS Bedrock
Qwen3-Next-80B-A3B
$273
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $45.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Qwen3-Next-80B-A3B is $0.51/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.2 11B Instruct is $0.51/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Llama 3.2 11B Instruct adds Vision and Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2025-12-01 |
| Context window | 128k | — |
| Parameters | 11B | 80B (3B active) |
| Architecture | - | - |
| License | Llama 3 Community | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Unknown | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.2 11B Instruct | Qwen3-Next-80B-A3B |
|---|---|---|
| Input price | $0.20/1M tokens | $0.10/1M tokens |
| Output price | $0.27/1M tokens | $0.78/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.2 11B Instruct | Qwen3-Next-80B-A3B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | 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: Llama 3.2 11B Instruct and multimodal input: Llama 3.2 11B Instruct. 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 3.2 11B Instruct lists $0.20/1M input and $0.27/1M output tokens on the cheapest tracked provider, while Qwen3-Next-80B-A3B lists $0.10/1M input and $0.78/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 11B Instruct lower by about $0.08 per million blended tokens. Availability is 1 providers versus 4, so concentration risk also matters.
Choose Llama 3.2 11B Instruct when vision-heavy evaluation are central to the workload. Choose Qwen3-Next-80B-A3B when provider fit, 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 is cheaper, Llama 3.2 11B Instruct or Qwen3-Next-80B-A3B?
Llama 3.2 11B Instruct is cheaper on tracked token pricing. Llama 3.2 11B Instruct costs $0.20/1M input and $0.27/1M output tokens. Qwen3-Next-80B-A3B costs $0.10/1M input and $0.78/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.2 11B Instruct or Qwen3-Next-80B-A3B open source?
Llama 3.2 11B Instruct is listed under Llama 3 Community. Qwen3-Next-80B-A3B 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 3.2 11B Instruct or Qwen3-Next-80B-A3B?
Llama 3.2 11B Instruct 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.
Which is better for multimodal input, Llama 3.2 11B Instruct or Qwen3-Next-80B-A3B?
Llama 3.2 11B Instruct 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.
Which is better for structured outputs, Llama 3.2 11B Instruct or Qwen3-Next-80B-A3B?
Both Llama 3.2 11B Instruct and Qwen3-Next-80B-A3B 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 Qwen3-Next-80B-A3B?
Llama 3.2 11B Instruct is available on AWS Bedrock. Qwen3-Next-80B-A3B is available on AWS Bedrock, OpenRouter, Venice AI, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Popular comparisons for Llama 3.2 11B Instruct
Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.