Home/Compare/MiniMax-M1 vs Qwen

Comparison

MiniMax-M1 vs Qwen

Verdict

Coexists - Both models serve to advance the field of open-weight large scale reasoning models.

Markdown twin · MiniMax-M1 alternatives · Qwen alternatives

GraphCanon updated 5d

MiniMax-M1 logo

MiniMax-M1

MiniMax-AI/MiniMax-M1

3.2kpushed Jul 7, 2025
vs
Qwen logo

Qwen

QwenLM/Qwen

22kpushed Mar 5, 2026

Trust & integrity

SignalMiniMax-M1Qwen
Maintenance
Dormant (406d since push)
As of 5d · github_public_v1
Slowing (164d since push)
As of 6d · github_public_v1
Provenance
Not a fork · Organization account
As of 5d · github_public_v1
Not a fork · Organization account
As of 6d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
Published findings
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

MiniMax-M1
Open-weight large-scale hybrid-attention reasoning model
Qwen
Official repo of Qwen, a large language model by Alibaba Cloud

Stars

MiniMax-M1
3.2k
Qwen
22k

Forks

MiniMax-M1
283
Qwen
1.9k

Open issues

MiniMax-M1
31
Qwen
44

Language

MiniMax-M1
Python
Qwen
Python

Adopt for

MiniMax-M1
MiniMax-M1 stands out for its open-access nature and hybrid-attention mechanisms that promise efficient inference capabilities.
Qwen
Qwen is a large language model by Alibaba Cloud with support for Chinese and advanced features like flash-attention.

Persona

MiniMax-M1
-
Qwen
-

Runtime

MiniMax-M1
-
Qwen
-

License

MiniMax-M1
Apache-2.0
Qwen
Apache-2.0

Last pushed

MiniMax-M1
Jul 7, 2025
Qwen
Mar 5, 2026

Categories

MiniMax-M1
Inference & Serving, LLM Frameworks
Qwen
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

MiniMax-M1
Dormant (18%)
Qwen
Slowing (36%)

Days since push

MiniMax-M1
406d
Qwen
164d

Open issues (now)

MiniMax-M1
31
Qwen
44

Stars delta

MiniMax-M1
+12 (30d)
Qwen
+153 (30d)

Open issues delta

MiniMax-M1
0 (30d)
Qwen
+1 (30d)

OSV dependency advisories

MiniMax-M1
No lockfile (source not queried)
Qwen
Published findings

Full report

MiniMax-M1
Trust report

Typed relationship

MiniMax-M1 successor QwenBoth MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other.Coexists - Both models serve to advance the field of open-weight large scale reasoning models.

Choose MiniMax-M1 if…

  • Pricing: Free to use under Apache-2.0 license, cost considerations will mainly stem from computing resources when deploying..
  • Requirements: Min 64 GB RAM; Requires Docker; Deployment is recommended using vLLM for optimal performance and efficient processing.; Transformers can also be used directly for deployment, offering an alternative way to integrate MiniMax-M1..
  • Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other.
  • Tags unique to MiniMax-M1: minimax-m1, reasoning-models.
  • When your project requires an open-weight model with flexible access to weights, allowing you to customize the model without any restrictions.

When NOT to use MiniMax-M1

  • In scenarios where strict proprietary controls over model weights are necessary, as MiniMax-M1's open-access nature might not comply with such stringent requirements.
  • If your project focuses on lightweight inference without the need for large-scale hybrid-attention mechanisms; smaller models might offer more efficient deployment options.

Choose Qwen if…

  • Requirements: Python 3.8+; PyTorch 1.12+; Transformers 4.32+; CUDA 11.4+ (GPU users).
  • Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other.
  • Tags unique to Qwen: chinese, flash-attention, natural-language-processing, pretrained-models.
  • If you are working with extensive Chinese text data, Qwen offers specialized capabilities that might not be found in other generic LLMs.

When NOT to use Qwen

  • If your project strictly requires a specific type of licensing, Qwen operates under the Apache-2.0 License with additional license agreements that may differ from general expectations and could pose a

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: MiniMax-M1 3.2k · Qwen 22k (synced Aug 18, 2026).

Common questions

What is the difference between MiniMax-M1 and Qwen?
MiniMax-M1: Open-weight large-scale hybrid-attention reasoning model. Qwen: Official repo of Qwen, a large language model by Alibaba Cloud. See the comparison table for live GitHub stats and shared categories.
When should I choose MiniMax-M1 over Qwen?
Choose MiniMax-M1 over Qwen when Pricing: Free to use under Apache-2.0 license, cost considerations will mainly stem from computing resources when deploying.; Requirements: Min 64 GB RAM; Requires Docker; Deployment is recommended using vLLM for optimal performance and efficient processing.; Transformers can also be used directly for deployment, offering an alternative way to integrate MiniMax-M1.; Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other; Tags unique to MiniMax-M1: minimax-m1, reasoning-models; When your project requires an open-weight model with flexible access to weights, allowing you to customize the model without any restrictions.
When should I choose Qwen over MiniMax-M1?
Choose Qwen over MiniMax-M1 when Requirements: Python 3.8+; PyTorch 1.12+; Transformers 4.32+; CUDA 11.4+ (GPU users); Both MiniMax-M1 and Qwen are large language models with Chinese focus, but as newer developments in AI, they may build on or compete with each other; Tags unique to Qwen: chinese, flash-attention, natural-language-processing, pretrained-models; If you are working with extensive Chinese text data, Qwen offers specialized capabilities that might not be found in other generic LLMs.
When should I avoid MiniMax-M1?
In scenarios where strict proprietary controls over model weights are necessary, as MiniMax-M1's open-access nature might not comply with such stringent requirements. If your project focuses on lightweight inference without the need for large-scale hybrid-attention mechanisms; smaller models might offer more efficient deployment options.
When should I avoid Qwen?
If your project strictly requires a specific type of licensing, Qwen operates under the Apache-2.0 License with additional license agreements that may differ from general expectations and could pose a
Is MiniMax-M1 or Qwen more popular on GitHub?
Qwen has more GitHub stars (21,595 vs 3,172). Stars measure visibility, not whether either tool fits your constraints.
Are MiniMax-M1 and Qwen open source?
Yes - both are open-source projects on GitHub (MiniMax-M1: Apache-2.0, Qwen: Apache-2.0).
Where can I find alternatives to MiniMax-M1 or Qwen?
GraphCanon lists graph-backed alternatives at MiniMax-M1 alternatives and Qwen alternatives (MiniMax-M1 markdown twin, Qwen markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, MiniMax-M1 or Qwen?
MiniMax-M1: Dormant. Qwen: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for MiniMax-M1 and Qwen?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: MiniMax-M1 trust report; Qwen trust report.

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