Llama 3.2 1B Instruct vs Llama 3 8B Instruct
Llama 3.2 1B Instruct (2024) and Llama 3 8B Instruct (2024) are compact production models from AI at Meta. Llama 3.2 1B Instruct ships a 128K-token context window, while Llama 3 8B Instruct ships a 8K-token context window. On MMLU PRO, Llama 3 8B Instruct leads by 20.5 pts. On pricing, Llama 3.2 1B Instruct costs $0.03/1M input tokens versus $0.03/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Pick Llama 3 8B Instruct for general evaluation; Llama 3.2 1B Instruct is better when long-context analysis matters more.
Specs
| Released | 2024-09-25 | 2024-04-18 |
| Context window | 128K | 8K |
| Parameters | 1.23B | 8B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Llama 3.2 1B Instruct | Llama 3 8B Instruct | |
|---|---|---|
| Input price | $0.03/1M tokens | $0.03/1M tokens |
| Output price | $0.2/1M tokens | $0.04/1M tokens |
| Providers |
Capabilities
| Llama 3.2 1B Instruct | Llama 3 8B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3.2 1B Instruct | Llama 3 8B Instruct |
|---|---|---|
| MMLU PRO | 20.0 | 40.5 |
| Google-Proof Q&A | 25.6 | 44.8 |
| HumanEval | 28.1 | 68.2 |
| Massive Multitask Language Understanding | 49.3 | 76.9 |
| HellaSwag | 78.9 | 91.1 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3.2 1B Instruct at 20 and Llama 3 8B Instruct at 40.5, with Llama 3 8B Instruct ahead by 20.5 points; Google-Proof Q&A has Llama 3.2 1B Instruct at 25.6 and Llama 3 8B Instruct at 44.8, with Llama 3 8B Instruct ahead by 19.2 points; HumanEval has Llama 3.2 1B Instruct at 28.1 and Llama 3 8B Instruct at 68.2, with Llama 3 8B Instruct ahead by 40.1 points. The largest visible gap is 40.1 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 3.2 1B Instruct lists $0.03/1M input and $0.2/1M 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 $0.05 per million blended tokens. Availability is 5 providers versus 17, so concentration risk also matters.
Choose Llama 3.2 1B Instruct when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3 8B Instruct when provider fit and broader provider choice 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 3.2 1B Instruct or Llama 3 8B Instruct?
Llama 3.2 1B 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 3.2 1B Instruct or Llama 3 8B Instruct?
Llama 3.2 1B Instruct is cheaper on tracked token pricing. Llama 3.2 1B Instruct costs $0.03/1M input and $0.2/1M 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 3.2 1B Instruct or Llama 3 8B Instruct open source?
Llama 3.2 1B Instruct 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 3.2 1B Instruct or Llama 3 8B Instruct?
Both Llama 3.2 1B Instruct 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 3.2 1B Instruct and Llama 3 8B Instruct?
Llama 3.2 1B Instruct is available on OpenRouter, Fireworks AI, NVIDIA NIM, Bitdeer AI, and AWS Bedrock. 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 3.2 1B Instruct over Llama 3 8B Instruct?
Pick Llama 3 8B Instruct for general evaluation; Llama 3.2 1B Instruct is better when long-context analysis matters more. If your workload also depends on long-context analysis, start with Llama 3.2 1B Instruct; if it depends on provider fit, run the same evaluation with Llama 3 8B Instruct.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.