Llama Guard 2 8B vs Qwen3.5-4B
Llama Guard 2 8B (2024) and Qwen3.5-4B (2026) are compact production models from AI at Meta and Alibaba. Llama Guard 2 8B ships a 8k-token context window, while Qwen3.5-4B ships a 262k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-4B fits 33x more tokens; pick it for long-context work and Llama Guard 2 8B for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama Guard 2 8B | Qwen3.5-4B |
|---|---|---|
| Best for | provider-routed production | multimodal apps |
| Decision fit | Classification | Coding, Agents, and Long context |
| Context window | 8k | 262k |
| Cheapest output | $0.25/1M tokens | - |
| Provider routes | 3 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama Guard 2 8B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama Guard 2 8B for Classification.
- Qwen3.5-4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-4B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-4B for Coding, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama Guard 2 8B
$103
Cheapest tracked route/tier: Replicate API
Qwen3.5-4B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama Guard 2 8B and Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-4B adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-4B and Llama Guard 2 8B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2026-03-02 |
| Context window | 8k | 262k |
| Parameters | 8B | 4B |
| Architecture | decoder only | - |
| License | Llama 2 Community | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2023-03 | - |
Pricing and availability
| Pricing attribute | Llama Guard 2 8B | Qwen3.5-4B |
|---|---|---|
| Input price | $0.05/1M tokens | - |
| Output price | $0.25/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Llama Guard 2 8B | Qwen3.5-4B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qwen3.5-4B and multimodal input: Qwen3.5-4B. 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.
Pricing coverage is uneven: Llama Guard 2 8B has $0.05/1M input tokens and Qwen3.5-4B has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama Guard 2 8B when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-4B 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. 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 Guard 2 8B or Qwen3.5-4B?
Qwen3.5-4B 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.
Is Llama Guard 2 8B or Qwen3.5-4B open source?
Llama Guard 2 8B is listed under Llama 2 Community. Qwen3.5-4B 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 Qwen3.5-4B?
Qwen3.5-4B 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 Qwen3.5-4B?
Qwen3.5-4B 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 Qwen3.5-4B?
Llama Guard 2 8B is available on Fireworks AI, OctoAI API (Deprecated), and Replicate API. Qwen3.5-4B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama Guard 2 8B over Qwen3.5-4B?
Qwen3.5-4B fits 33x more tokens; pick it for long-context work and Llama Guard 2 8B for tighter calls. If your workload also depends on provider fit, start with Llama Guard 2 8B; if it depends on long-context analysis, run the same evaluation with Qwen3.5-4B.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.