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Llama 3.2 11B Vision vs Qwen3.5-397B-A17B

Llama 3.2 11B Vision (2024) and Qwen3.5-397B-A17B (2026) are frontier reasoning models from AI at Meta and Alibaba. Llama 3.2 11B Vision ships a 128K-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 41.4 pts. On pricing, Llama 3.2 11B Vision costs $0.2/1M input tokens versus $0.39/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama 3.2 11B Vision is ~95% cheaper at $0.2/1M; pay for Qwen3.5-397B-A17B only for reasoning depth.

Decision scorecard

Local evidence first
SignalLlama 3.2 11B VisionQwen3.5-397B-A17B
Decision fitRAG, Long context, and VisionCoding, RAG, and Agents
Context window128K262K
Cheapest output$0.27/1M tokens$2.34/1M tokens
Provider routes1 tracked3 tracked
Shared benchmarks2 rowsMMLU PRO leader

Decision tradeoffs

Choose Llama 3.2 11B Vision when...
  • Llama 3.2 11B Vision has the lower cheapest tracked output price at $0.27/1M tokens.
  • Llama 3.2 11B Vision uniquely exposes Vision in local model data.
  • Local decision data tags Llama 3.2 11B Vision for RAG, Long context, and Vision.
Choose Qwen3.5-397B-A17B when...
  • Qwen3.5-397B-A17B leads the largest shared benchmark signal on MMLU PRO by 41.4 points.
  • Qwen3.5-397B-A17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-397B-A17B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.5-397B-A17B uniquely exposes Multimodal, Reasoning, and Function calling in local model data.
  • Local decision data tags Qwen3.5-397B-A17B for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Llama 3.2 11B Vision

Llama 3.2 11B Vision

$228

Cheapest tracked route: AWS Bedrock

Qwen3.5-397B-A17B

$897

Cheapest tracked route: OpenRouter

Estimated monthly gap: $670. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Llama 3.2 11B Vision -> Qwen3.5-397B-A17B
  • No overlapping tracked provider route is sourced for Llama 3.2 11B Vision and Qwen3.5-397B-A17B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-397B-A17B is $2.07/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Vision before moving production traffic.
  • Qwen3.5-397B-A17B adds Multimodal, Reasoning, and Function calling in local capability data.
Qwen3.5-397B-A17B -> Llama 3.2 11B Vision
  • No overlapping tracked provider route is sourced for Qwen3.5-397B-A17B and Llama 3.2 11B Vision; plan for SDK, billing, or endpoint changes.
  • Llama 3.2 11B Vision is $2.07/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Multimodal, Reasoning, and Function calling before moving production traffic.
  • Llama 3.2 11B Vision adds Vision in local capability data.

Specs

Specification
Released2024-09-252026-02-16
Context window128K262K
Parameters10.6B397B
Architecturedecoder onlyMoE
LicenseOpen SourceApache 2.0
Knowledge cutoff2024-03-

Pricing and availability

Pricing attributeLlama 3.2 11B VisionQwen3.5-397B-A17B
Input price$0.2/1M tokens$0.39/1M tokens
Output price$0.27/1M tokens$2.34/1M tokens
Providers

Capabilities

CapabilityLlama 3.2 11B VisionQwen3.5-397B-A17B
VisionYesNo
MultimodalNoYes
ReasoningNoYes
Function callingNoYes
Tool useNoYes
Structured outputsYesYes
Code executionNoNo

Benchmarks

BenchmarkLlama 3.2 11B VisionQwen3.5-397B-A17B
MMLU PRO46.487.8
Massive Multi-discipline Multimodal Understanding50.785.0

Deep dive

On shared benchmark coverage, MMLU PRO has Llama 3.2 11B Vision at 46.4 and Qwen3.5-397B-A17B at 87.8, with Qwen3.5-397B-A17B ahead by 41.4 points; Massive Multi-discipline Multimodal Understanding has Llama 3.2 11B Vision at 50.7 and Qwen3.5-397B-A17B at 85, with Qwen3.5-397B-A17B ahead by 34.3 points. The largest visible gap is 41.4 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.

The capability footprint differs most on vision: Llama 3.2 11B Vision, multimodal input: Qwen3.5-397B-A17B, reasoning mode: Qwen3.5-397B-A17B, function calling: Qwen3.5-397B-A17B, and tool use: Qwen3.5-397B-A17B. 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 Vision lists $0.2/1M input and $0.27/1M output tokens, while Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 11B Vision lower by about $0.75 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.

Choose Llama 3.2 11B Vision when vision-heavy evaluation and lower input-token cost are central to the workload. Choose Qwen3.5-397B-A17B when reasoning depth, larger context windows, 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.

FAQ

Which has a larger context window, Llama 3.2 11B Vision or Qwen3.5-397B-A17B?

Qwen3.5-397B-A17B supports 262K tokens, while Llama 3.2 11B Vision 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 3.2 11B Vision or Qwen3.5-397B-A17B?

Llama 3.2 11B Vision is cheaper on tracked token pricing. Llama 3.2 11B Vision costs $0.2/1M input and $0.27/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama 3.2 11B Vision or Qwen3.5-397B-A17B open source?

Llama 3.2 11B Vision is listed under Open Source. Qwen3.5-397B-A17B 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 Vision or Qwen3.5-397B-A17B?

Llama 3.2 11B Vision 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 Vision or Qwen3.5-397B-A17B?

Qwen3.5-397B-A17B 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 3.2 11B Vision and Qwen3.5-397B-A17B?

Llama 3.2 11B Vision is available on AWS Bedrock. Qwen3.5-397B-A17B is available on OpenRouter, Together AI, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.