The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Model details →Meta: Llama 3.3 70B Instruct vs Qwen: Qwen3 8B
Meta: Llama 3.3 70B Instruct wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...
Model details →Side-by-side comparison
| Capability | Meta: Llama 3.3 70B Instruct | Qwen: Qwen3 8B | 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. | $0.10 | $0.12 | 🏆 Meta: Llama 3.3 70B Instruct |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.32 | $0.46 | 🏆 Meta: Llama 3.3 70B 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. | — | Yes | 🏆 Qwen: Qwen3 8B |
Frequently asked questions
Is Meta: Llama 3.3 70B Instruct better than Qwen: Qwen3 8B?
Meta: Llama 3.3 70B Instruct wins on 2 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Meta: Llama 3.3 70B Instruct and Qwen: Qwen3 8B?
Input: $0.10 vs $0.12 per 1M tokens. Output: $0.32 vs $0.46 per 1M tokens.
What context windows do Meta: Llama 3.3 70B Instruct and Qwen: Qwen3 8B support?
Meta: Llama 3.3 70B Instruct supports up to 131K tokens. Qwen: Qwen3 8B supports up to 131K tokens.
Do both Meta: Llama 3.3 70B Instruct and Qwen: Qwen3 8B support tool calling?
Meta: Llama 3.3 70B Instruct: yes. Qwen: Qwen3 8B: yes.