Llama 2 13B Chat vs Qwen3.5-397B-A17B
Llama 2 13B Chat (2023) and Qwen3.5-397B-A17B (2026) are compact production models from AI at Meta and Alibaba. Llama 2 13B Chat ships a 4K-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On Google-Proof Q&A, Qwen3.5-397B-A17B leads by 47.5 pts. On pricing, Llama 2 13B Chat costs $0.1/1M input tokens versus $0.39/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 2 13B Chat is ~290% cheaper at $0.1/1M; pay for Qwen3.5-397B-A17B only for long-context analysis.
Specs
| Released | 2023-07-18 | 2026-02-16 |
| Context window | 4K | 262K |
| Parameters | 13B | 397B |
| Architecture | decoder only | MoE |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 2 13B Chat | Qwen3.5-397B-A17B | |
|---|---|---|
| Input price | $0.1/1M tokens | $0.39/1M tokens |
| Output price | $0.5/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Llama 2 13B Chat | Qwen3.5-397B-A17B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 2 13B Chat | Qwen3.5-397B-A17B |
|---|---|---|
| Google-Proof Q&A | 41.8 | 89.3 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 2 13B Chat at 41.8 and Qwen3.5-397B-A17B at 89.3, with Qwen3.5-397B-A17B ahead by 47.5 points. The largest visible gap is 47.5 points on Google-Proof Q&A, 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 multimodal input: 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 2 13B Chat lists $0.1/1M input and $0.5/1M 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 2 13B Chat lower by about $0.75 per million blended tokens. Availability is 12 providers versus 1, so concentration risk also matters.
Choose Llama 2 13B Chat when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B 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.
FAQ
Which has a larger context window, Llama 2 13B Chat or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262K tokens, while Llama 2 13B Chat supports 4K 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 2 13B Chat or Qwen3.5-397B-A17B?
Llama 2 13B Chat is cheaper on tracked token pricing. Llama 2 13B Chat costs $0.1/1M input and $0.5/1M 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 2 13B Chat or Qwen3.5-397B-A17B open source?
Llama 2 13B Chat 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 multimodal input, Llama 2 13B Chat 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.
Which is better for structured outputs, Llama 2 13B Chat or Qwen3.5-397B-A17B?
Both Llama 2 13B Chat and Qwen3.5-397B-A17B 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 2 13B Chat and Qwen3.5-397B-A17B?
Llama 2 13B Chat is available on Alibaba Cloud PAI-EAS, AWS Bedrock, Microsoft Foundry, GCP Vertex AI, and Cloudflare Workers AI. Qwen3.5-397B-A17B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.