Llama 3 8B Instruct vs Qwen2.5-72B-Instruct
Llama 3 8B Instruct (2024) and Qwen2.5-72B-Instruct (2024) are compact production models from AI at Meta and Alibaba. Llama 3 8B Instruct ships a 8K-token context window, while Qwen2.5-72B-Instruct ships a 128K-token context window. On Google-Proof Q&A, Qwen2.5-72B-Instruct leads by 20.6 pts. On pricing, Llama 3 8B Instruct costs $0.03/1M input tokens versus $0.12/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3 8B Instruct is ~300% cheaper at $0.03/1M; pay for Qwen2.5-72B-Instruct only for long-context analysis.
Specs
| Released | 2024-04-18 | 2024-06-07 |
| Context window | 8K | 128K |
| Parameters | 8B | 72.7B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Llama 3 8B Instruct | Qwen2.5-72B-Instruct | |
|---|---|---|
| Input price | $0.03/1M tokens | $0.12/1M tokens |
| Output price | $0.04/1M tokens | $0.39/1M tokens |
| Providers |
Capabilities
| Llama 3 8B Instruct | Qwen2.5-72B-Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3 8B Instruct | Qwen2.5-72B-Instruct |
|---|---|---|
| Google-Proof Q&A | 44.8 | 65.4 |
| HumanEval | 68.2 | 92.7 |
| Massive Multitask Language Understanding | 76.9 | 88.2 |
| HellaSwag | 91.1 | 95.6 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 3 8B Instruct at 44.8 and Qwen2.5-72B-Instruct at 65.4, with Qwen2.5-72B-Instruct ahead by 20.6 points; HumanEval has Llama 3 8B Instruct at 68.2 and Qwen2.5-72B-Instruct at 92.7, with Qwen2.5-72B-Instruct ahead by 24.5 points; Massive Multitask Language Understanding has Llama 3 8B Instruct at 76.9 and Qwen2.5-72B-Instruct at 88.2, with Qwen2.5-72B-Instruct ahead by 11.3 points. The largest visible gap is 24.5 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 Qwen2.5-72B-Instruct lists $0.12/1M input and $0.39/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 8B Instruct lower by about $0.17 per million blended tokens. Availability is 17 providers versus 7, 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 Qwen2.5-72B-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 Qwen2.5-72B-Instruct?
Qwen2.5-72B-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 Qwen2.5-72B-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. Qwen2.5-72B-Instruct costs $0.12/1M input and $0.39/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3 8B Instruct or Qwen2.5-72B-Instruct open source?
Llama 3 8B Instruct is listed under Open Source. Qwen2.5-72B-Instruct 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 structured outputs, Llama 3 8B Instruct or Qwen2.5-72B-Instruct?
Both Llama 3 8B Instruct and Qwen2.5-72B-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 Qwen2.5-72B-Instruct?
Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3 8B Instruct over Qwen2.5-72B-Instruct?
Llama 3 8B Instruct is ~300% cheaper at $0.03/1M; pay for Qwen2.5-72B-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 Qwen2.5-72B-Instruct.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.