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Llama Guard 2 8B vs Qwen3.5-9B

Llama Guard 2 8B (2024) and Qwen3.5-9B (2026) are compact production models from AI at Meta and Alibaba. Llama Guard 2 8B ships a 8K-token context window, while Qwen3.5-9B ships a 262K-token context window. On pricing, Llama Guard 2 8B costs $0.05/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama Guard 2 8B is ~100% cheaper at $0.05/1M; pay for Qwen3.5-9B only for long-context analysis.

Decision scorecard

Local evidence first
SignalLlama Guard 2 8BQwen3.5-9B
Decision fitGeneralRAG, Agents, and Long context
Context window8K262K
Cheapest output$0.25/1M tokens$0.15/1M tokens
Provider routes3 tracked3 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama Guard 2 8B when...
  • Use Llama Guard 2 8B when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Choose Qwen3.5-9B when...
  • Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
  • Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.

Monthly cost at traffic

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

Lower estimate Llama Guard 2 8B

Llama Guard 2 8B

$103

Cheapest tracked route: Replicate API

Qwen3.5-9B

$118

Cheapest tracked route: Together AI

Estimated monthly gap: $15.00. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Llama Guard 2 8B -> Qwen3.5-9B
  • No overlapping tracked provider route is sourced for Llama Guard 2 8B and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-9B is $0.1/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
Qwen3.5-9B -> Llama Guard 2 8B
  • No overlapping tracked provider route is sourced for Qwen3.5-9B and Llama Guard 2 8B; plan for SDK, billing, or endpoint changes.
  • Llama Guard 2 8B is $0.1/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification
Released2024-04-182026-03-02
Context window8K262K
Parameters8B9B
Architecturedecoder onlydecoder only
LicenseOpen SourceApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeLlama Guard 2 8BQwen3.5-9B
Input price$0.05/1M tokens$0.1/1M tokens
Output price$0.25/1M tokens$0.15/1M tokens
Providers

Capabilities

CapabilityLlama Guard 2 8BQwen3.5-9B
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, tool use: Qwen3.5-9B, and structured outputs: Qwen3.5-9B. 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.

For cost, Llama Guard 2 8B lists $0.05/1M input and $0.25/1M output tokens, while Qwen3.5-9B lists $0.1/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama Guard 2 8B lower by about $0.01 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.

Choose Llama Guard 2 8B when provider fit and lower input-token cost are central to the workload. Choose Qwen3.5-9B when long-context analysis and larger context windows 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 has a larger context window, Llama Guard 2 8B or Qwen3.5-9B?

Qwen3.5-9B supports 262K tokens, while Llama Guard 2 8B supports 8K 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 Guard 2 8B or Qwen3.5-9B?

Llama Guard 2 8B is cheaper on tracked token pricing. Llama Guard 2 8B costs $0.05/1M input and $0.25/1M output tokens. Qwen3.5-9B costs $0.1/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama Guard 2 8B or Qwen3.5-9B open source?

Llama Guard 2 8B is listed under Open Source. Qwen3.5-9B 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 Guard 2 8B or Qwen3.5-9B?

Qwen3.5-9B 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 multimodal input, Llama Guard 2 8B or Qwen3.5-9B?

Qwen3.5-9B 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 Guard 2 8B and Qwen3.5-9B?

Llama Guard 2 8B is available on Fireworks AI, OctoAI API (Deprecated), and Replicate API. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.