Llama 3 8B Instruct vs Llama 3.1 70B Instruct
Llama 3 8B Instruct (2024) and Llama 3.1 70B Instruct (2024) are compact production models from AI at Meta. Llama 3 8B Instruct ships a 8K-token context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On HumanEval, Llama 3.1 70B Instruct leads by 15.9 pts. On pricing, Llama 3 8B Instruct costs $0.03/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 8B Instruct is ~1233% cheaper at $0.03/1M; pay for Llama 3.1 70B Instruct only for long-context analysis.
Specs
| Released | 2024-04-18 | 2024-07-23 |
| Context window | 8K | 128K |
| Parameters | 8B | 70B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 3 8B Instruct | Llama 3.1 70B Instruct | |
|---|---|---|
| Input price | $0.03/1M tokens | $0.4/1M tokens |
| Output price | $0.04/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| Llama 3 8B Instruct | Llama 3.1 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 8B Instruct | Llama 3.1 70B Instruct |
|---|---|---|
| HumanEval | 68.2 | 84.1 |
| Massive Multitask Language Understanding | 76.9 | 86.0 |
| HellaSwag | 91.1 | 94.2 |
Deep dive
On shared benchmark coverage, HumanEval has Llama 3 8B Instruct at 68.2 and Llama 3.1 70B Instruct at 84.1, with Llama 3.1 70B Instruct ahead by 15.9 points; Massive Multitask Language Understanding has Llama 3 8B Instruct at 76.9 and Llama 3.1 70B Instruct at 86, with Llama 3.1 70B Instruct ahead by 9.1 points; HellaSwag has Llama 3 8B Instruct at 91.1 and Llama 3.1 70B Instruct at 94.2, with Llama 3.1 70B Instruct ahead by 3.1 points. The largest visible gap is 15.9 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 3 8B Instruct lists $0.03/1M input and $0.04/1M output tokens, while Llama 3.1 70B Instruct lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.37 per million blended tokens. Availability is 17 providers versus 11, so concentration risk also matters.
Choose Llama 3 8B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Llama 3.1 70B Instruct 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 3 8B Instruct or Llama 3.1 70B Instruct?
Llama 3.1 70B Instruct supports 128K tokens, while Llama 3 8B Instruct 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 3 8B Instruct or Llama 3.1 70B Instruct?
Llama 3 8B Instruct is cheaper on tracked token pricing. Llama 3 8B Instruct costs $0.03/1M input and $0.04/1M output tokens. Llama 3.1 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 8B Instruct or Llama 3.1 70B Instruct open source?
Llama 3 8B Instruct is listed under Open Source. Llama 3.1 70B 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 3 8B Instruct or Llama 3.1 70B Instruct?
Both Llama 3 8B Instruct and Llama 3.1 70B 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 3 8B Instruct and Llama 3.1 70B Instruct?
Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Llama 3.1 70B Instruct is available on OctoAI API, Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3 8B Instruct over Llama 3.1 70B Instruct?
Llama 3 8B Instruct is ~1233% cheaper at $0.03/1M; pay for Llama 3.1 70B Instruct only for long-context analysis. If your workload also depends on provider fit, start with Llama 3 8B Instruct; if it depends on long-context analysis, run the same evaluation with Llama 3.1 70B Instruct.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.