Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
Model details →Meta: Llama 3.1 70B Instruct vs Qwen: Qwen3 14B
Qwen: Qwen3 14B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
Model details →Side-by-side comparison
| Capability | Meta: Llama 3.1 70B Instruct | Qwen: Qwen3 14B | 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. | $0.40 | $0.12 | 🏆 Qwen: Qwen3 14B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.40 | $0.24 | 🏆 Qwen: Qwen3 14B |
| 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. | — | Yes | 🏆 Qwen: Qwen3 14B |
Frequently asked questions
Is Meta: Llama 3.1 70B Instruct better than Qwen: Qwen3 14B?
Qwen: Qwen3 14B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Meta: Llama 3.1 70B Instruct and Qwen: Qwen3 14B?
Input: $0.40 vs $0.12 per 1M tokens. Output: $0.40 vs $0.24 per 1M tokens.
What context windows do Meta: Llama 3.1 70B Instruct and Qwen: Qwen3 14B support?
Meta: Llama 3.1 70B Instruct supports up to 131K tokens. Qwen: Qwen3 14B supports up to 131K tokens.
Do both Meta: Llama 3.1 70B Instruct and Qwen: Qwen3 14B support tool calling?
Meta: Llama 3.1 70B Instruct: yes. Qwen: Qwen3 14B: yes.