Llama 2 13B Chat vs Llama 3 8B Instruct
Llama 2 13B Chat (2023) and Llama 3 8B Instruct (2024) are compact production models from AI at Meta. Llama 2 13B Chat ships a 4K-token context window, while Llama 3 8B Instruct ships a 8K-token context window. On Google-Proof Q&A, Llama 3 8B Instruct leads by 3 pts. On pricing, Llama 3 8B Instruct costs $0.03/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 8B Instruct is ~233% cheaper at $0.03/1M; pay for Llama 2 13B Chat only for provider fit.
Specs
| Released | 2023-07-18 | 2024-04-18 |
| Context window | 4K | 8K |
| Parameters | 13B | 8B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 2 13B Chat | Llama 3 8B Instruct | |
|---|---|---|
| Input price | $0.1/1M tokens | $0.03/1M tokens |
| Output price | $0.5/1M tokens | $0.04/1M tokens |
| Providers |
Capabilities
| Llama 2 13B Chat | Llama 3 8B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 2 13B Chat | Llama 3 8B Instruct |
|---|---|---|
| Google-Proof Q&A | 41.8 | 44.8 |
| HumanEval | 59.3 | 68.2 |
| Massive Multitask Language Understanding | 71.2 | 76.9 |
| HellaSwag | 88.5 | 91.1 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 2 13B Chat at 41.8 and Llama 3 8B Instruct at 44.8, with Llama 3 8B Instruct ahead by 3 points; HumanEval has Llama 2 13B Chat at 59.3 and Llama 3 8B Instruct at 68.2, with Llama 3 8B Instruct ahead by 8.9 points; Massive Multitask Language Understanding has Llama 2 13B Chat at 71.2 and Llama 3 8B Instruct at 76.9, with Llama 3 8B Instruct ahead by 5.7 points. The largest visible gap is 8.9 points on HumanEval, 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 is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Llama 2 13B Chat lists $0.1/1M input and $0.5/1M output tokens, while Llama 3 8B Instruct lists $0.03/1M input and $0.04/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.19 per million blended tokens. Availability is 12 providers versus 17, so concentration risk also matters.
Choose Llama 2 13B Chat when provider fit are central to the workload. Choose Llama 3 8B Instruct when long-context analysis, larger context windows, and lower input-token cost 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 Llama 3 8B Instruct?
Llama 3 8B Instruct supports 8K 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 Llama 3 8B Instruct?
Llama 3 8B Instruct is cheaper on tracked token pricing. Llama 2 13B Chat costs $0.1/1M input and $0.5/1M output tokens. Llama 3 8B Instruct costs $0.03/1M input and $0.04/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 2 13B Chat or Llama 3 8B Instruct open source?
Llama 2 13B Chat is listed under Open Source. Llama 3 8B Instruct is listed under Open Source. 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 structured outputs, Llama 2 13B Chat or Llama 3 8B Instruct?
Both Llama 2 13B Chat and Llama 3 8B Instruct 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 Llama 3 8B Instruct?
Llama 2 13B Chat is available on Alibaba Cloud PAI-EAS, AWS Bedrock, Microsoft Foundry, GCP Vertex AI, and Cloudflare Workers AI. Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 2 13B Chat over Llama 3 8B Instruct?
Llama 3 8B Instruct is ~233% cheaper at $0.03/1M; pay for Llama 2 13B Chat only for provider fit. If your workload also depends on provider fit, start with Llama 2 13B Chat; if it depends on long-context analysis, run the same evaluation with Llama 3 8B Instruct.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.