Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
Model details →meta-llama/Llama-3.1-8B-Instruct vs Qwen: Qwen-Turbo
meta-llama/Llama-3.1-8B-Instruct and Qwen: Qwen-Turbo are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.
Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.
Model details →Side-by-side comparison
| Capability | meta-llama/Llama-3.1-8B-Instruct | Qwen: Qwen-Turbo | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | 131K | Tie |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.05 | $0.03 | 🏆 Qwen: Qwen-Turbo |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.08 | $0.13 | 🏆 meta-llama/Llama-3.1-8B-Instruct |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is meta-llama/Llama-3.1-8B-Instruct better than Qwen: Qwen-Turbo?
meta-llama/Llama-3.1-8B-Instruct and Qwen: Qwen-Turbo are evenly matched on 6 axes — pick the one whose provider, latency, or licensing fits your stack.
What's the price difference between meta-llama/Llama-3.1-8B-Instruct and Qwen: Qwen-Turbo?
Input: $0.05 vs $0.03 per 1M tokens. Output: $0.08 vs $0.13 per 1M tokens.
What context windows do meta-llama/Llama-3.1-8B-Instruct and Qwen: Qwen-Turbo support?
meta-llama/Llama-3.1-8B-Instruct supports up to 131K tokens. Qwen: Qwen-Turbo supports up to 131K tokens.
Do both meta-llama/Llama-3.1-8B-Instruct and Qwen: Qwen-Turbo support tool calling?
meta-llama/Llama-3.1-8B-Instruct: yes. Qwen: Qwen-Turbo: yes.