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Qwen-1.8B

Foundation modelQwen

Qwen-1.8B

Release date: 2023-11-30Updated: 2023-11-30 16:37:40.975663
Parameters
1.8B
Context length
8K
Chinese support
Supported
Reasoning ability

Qwen-1.8B is an AI model published by Alibaba, released on 2023-11-30, for Foundation model, with 1.8B parameters, and 8K context length, requiring about 3.6GB storage, with a 45.30 score on MMLU.

Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology

Qwen-1.8B

Model basics

Reasoning traces
Not supported
Thinking modes
Thinking modes not supported
Context length
8K tokens
Max output length
No data
Model type
Foundation model
Modality (in / out)
No data
Release date
2023-11-30
Model file size
3.6GB
MoE architecture
No
Total params / Active params
1.8B / N/A
Knowledge cutoff
No data
Qwen-1.8B

Open source & experience

Code license
Weights license
- Commercial use permitted
Live demo
No live demo
Qwen-1.8B

Official resources

Paper
DataLearnerAI blog
No blog post yet
Qwen-1.8B

API details

API speed
No data
No public API pricing yet.
Qwen-1.8B

Benchmark Results

Qwen-1.8B currently shows benchmark results led by GSM8K (55 / 70, score 32.30), MMLU (112 / 124, score 45.30), HumanEval (97 / 101, score 15.20). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.

Thinking

General Knowledge

1 evaluations
Benchmark / mode
Score
Rank/total
MMLU
Standard Mode
45.30
112 / 124

Math and Reasoning

1 evaluations
Benchmark / mode
Score
Rank/total
GSM8K
Standard Mode
32.30
55 / 70

Coding and Software Engineer

1 evaluations
Benchmark / mode
Score
Rank/total
HumanEval
Standard Mode
15.20
97 / 101

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Qwen-1.8B

Publisher

Qwen-1.8B

Model Overview

Qwen-1.8B is an AI model published by Alibaba, released on 2023-11-30, for Foundation model, with 1.8B parameters, and 8K context length, requiring about 3.6GB storage, with a 45.30 score on MMLU.

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