Qwen2

Qwen2

by Alibaba Group (Qwen/QwenLM team)

Open-weights multilingual LLMs for self-hosting.

Reviewed September 2026by CBAI Editorial Team
7.0/10

Score

3.5 out of 5 · our score
Compare

Our verdict

Qwen2 remains a valuable open-weights release for developers who need multilingual, coding-capable models they can run locally or via Alibaba Cloud’s DashScope. The lineup spans 0.5B to 72B with a notable 57B‑A14B MoE checkpoint, Group Query Attention for efficient inference, and instruct variants with up to 128K context via YARN. The biggest caveats are licensing and currency: only the 0.5B/1.5B/7B/57B‑A14B models are Apache‑2.0, while the flagship 72B uses the Qianwen/Tongyi license, and the family itself is now two generations behind Qwen3.x. There are no subscription tiers—self‑hosting is free (subject to license), and hosted use is metered per token on DashScope with region‑specific pricing. It’s excellent for experimentation, on‑prem pilots, and China‑region access, but organizations needing SLAs or state‑of‑the‑art quality should look at Qwen3.x or other current leaders.

Overview

Qwen2 is an open-weights large language model family from Alibaba Group’s Qwen (QwenLM) team, released June 7, 2024, in base and instruct variants across 0.5B, 1.5B, 7B, 57B-A14B (MoE, 14B active), and 72B sizes. It improves coding, math, and multilingual performance over Qwen1.5, supports common OSS runtimes (Transformers, vLLM, llama.cpp, Ollama, SGLang), and can be called via Alibaba Cloud Model Studio (DashScope). Licensing is split: 0.5B/1.5B/7B/57B-A14B under Apache-2.0…

Score breakdown

Overall score

7.0/10
Output quality7.5/10
Ease of use7.0/10
Value for money9.5/10
Features & tools7.0/10
API & integrations5.5/10
Support & docs5.0/10

Scores are editorial assessments by the Compare Best AI team on a 0–10 scale.

Expert review

C

CBAI Editorial Team

Compare Best AI · Editorial Team

## Overview

How we tested

Days tested

7 days

Tasks evaluated

  • ·Local inference on 7B and 57B‑A14B via vLLM/llama.cpp
  • ·Multilingual chat evaluation (EN/ZH + 2 European languages)
  • ·Coding/math prompts against Base vs Instruct variants
  • ·Long‑context RAG with 64K and 128K (YARN) windows

Method

Compared against Meta Llama 3.1 70B Instruct and Mistral Mixtral 8x22B using identical inputs

Reviewer

CBAI Editorial Team

Plans & pricing

Most Popular

Self-host (Open Weights)

$0/month

Researchers and engineers deploying locally or on-prem

  • Download on Hugging Face/ModelScope
  • Apache-2.0 for 0.5B/1.5B/7B/57B-A14B
  • Qianwen/Tongyi licence for 72B
  • Runs on Transformers, vLLM, llama.cpp, Ollama
  • No vendor SLA or managed hosting included

Hosted API (DashScope)

Metered/month

Teams needing managed inference and China-region access

  • Per-token billing; input/output priced separately
  • Rates vary by model size and region (Beijing vs Singapore)
  • No permanent free tier; trial quotas may be time-limited
  • Model availability subject to deprecation/retirement notices

Pricing may vary by region. Always verify on the vendor's website.

Feature comparison

FeatureQwen2Meta Llama 3.1 70B InstructMistral Mixtral 8x22B
Openness
Open weights available
Licensing
Apache-2.0 license across all sizes
Architecture
MoE variant available
Context
128K context option
Deployment
Runs on Ollama
Regions
Chinese Mainland hosted API available
Scale
72B-class dense model
Commercial use
Commercial use without extra terms
Included Partial / add-on Not included

Is it right for you?

Good fit for

Self-hosting developers

They get free, capable models to run locally with popular OSS stacks like Transformers, vLLM, and llama.cpp.

Multilingual app teams

Qwen2’s multilingual coverage suits apps serving English, Chinese, and additional languages without relying on closed APIs.

China-region deployments

Alibaba Cloud Model Studio offers region-specific endpoints aligned to Chinese Mainland requirements.

MoE experimentation

57B‑A14B offers an MoE design with only ~14B active per token, useful for efficiency research.

Less suited for

Enterprises needing SLAs

There’s no vendor SLA or support for self-hosting; hosted endpoints may be deprecated over time.

SOTA seekers

Qwen2 has been superseded by Qwen2.5/3/3.x; not the latest for cutting-edge quality.

User reviews

3.5

Editorial score

5
42%
4
25%
3
9%
2
6%
1
2%

Distribution is estimated from our editorial score. Verified user reviews coming soon.

Use cases

Typical ways teams rely on this tool — from everyday tasks to specialized workflows.

  • On‑prem LLM deployment
  • Multilingual chatbots and agents
  • Code assistants and pair programming
  • Long‑context RAG pilots
  • China‑region compliant inference
  • Education and research

Integrations

Reported connectors

Apps and services commonly connected out of the box or via official connectors.

  • Hugging Face
  • ModelScope
  • Ollama

Details

Category

Developer

Price

  • Self-host: $0 download (Apache-2.0 for 0.5B/1.5B/7B/57B-A14B
  • Qianwen/Tongyi licence for 72B)
  • Hosted API: metered per-token via Alibaba Cloud Model Studio/DashScope (rates vary by model and region)

Free version

No

Best for

  • On-prem or air‑gapped LLM deployments
  • Multilingual chat/coding assistants
  • China‑mainland API access via Alibaba Cloud
  • Experimenting with MoE inference efficiently

Frequently asked questions

Qwen2

Qwen2

Developer

Ready to get started?

Visit the Qwen2 website to explore plans and pricing.

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