Downloadable models · Side by side

Qwen3 8B vs Llama 3.1 8B Instruct

Compare two similarly sized text models with different release terms and context configurations. Select the exact checkpoint before checking local memory or hosted deployment options.

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Qwen

Qwen3-8B

Reported parameters: 8.19B
Release license: apache-2.0

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meta-llama

Llama-3.1-8B-Instruct

Reported parameters: 8.03B
Release license: llama3.1

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The short answer

Qwen3 offers thinking and non-thinking modes; Llama 3.1 Instruct uses its own instruction-tuned chat format.
Qwen3 has an Apache 2.0 license. Llama uses its own community license and access conditions.
Qwen3 describes 32,768 native context tokens with YaRN extension; Llama 3.1 describes 128K context. Longer context also increases runtime memory.

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Compare context, supported inputs and usage costs. Highlighted rows show a difference.

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Qwen3 8B vs Llama 3.1 8B Instruct specifications
Feature	Qwen3-8B	Llama-3.1-8B-Instruct
Input formats	text	text
Output formats	text	text
Context / position limit	32,768	131,072
Parameter count	8,190,735,360	8,030,261,248
Release license	apache-2.0	llama3.1
Model identifier	Qwen/Qwen3-8B	meta-llama/Llama-3.1-8B-Instruct

API pricing

Prices are in USD per million tokens. Input is what you send; output is what the model generates. Claude and ChatGPT subscriptions are billed separately.

Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.

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Choosing for your project

Start with the formats you need to send, then compare the context allowance and the cost examples. For an existing application, check tool calls and response formats before changing its model. A higher context limit or a lower token price does not, on its own, tell you which answer will be more useful.

Planning to run it yourself?

Weight size is only part of memory use. Context, concurrency, quantization and runtime overhead matter too. A larger context setting needs separate checks.

What can my computer run?