# Gitmore vs Qwen 4 (Alibaba Qwen4)

Gitmore records 1,021 monthly visits with -62.4% month-over-month growth and Freemium pricing. Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% growth and Freemium pricing.

| Metric | [Gitmore](https://openaitools.app/tool/gitmore) | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) |
| :--- | :--- | :--- |
| Website URL | https://gitmore.io | https://qwen.ai |
| Categories | AI Report Generator, AI GitHub, AI Developer Tools, AI Agent | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 1,021 | 35,101,353 |
| MoM Growth Rate | -62.4% | -6.2% |
| Primary Market | United States | Russia |
| Direct Visits | 401 | 25,020,350 |
| Review Score | 4.1 | 4.7 |
| Saved Count | 0 | 1,180 |
| Supported Platforms | Website | Website, API, Open Source |

## Gitmore

Gitmore connects to your repositories through OAuth or a manual webhook and only reads event metadata such as titles, messages, authors and timestamps — it never reads your source code. From that stream it assembles reports: what merged, who contributed, which pull requests are stalling, and which tasks from Notion, Linear, Jira, Asana, ClickUp or Trello actually shipped. Reports can be delivered on a schedule to Slack or email in 11 languages.

A distinctive feature is the AI agent ledger. Every pull request and commit is attributed to a human or to an agent such as Claude Code, GitHub Copilot, Cursor, Codex, Devin or Jules, using co-authored-by trailers, bot accounts and branch prefixes. Teams can then see AI share of merged work, merge rates per agent, and pull requests generated by agents that are still waiting on a human reviewer.

Beyond reports, Gitmore offers password-protected client portals with your branding, public changelogs and embeddable widgets, proactive alerts for stale or unreviewed pull requests, plus an MCP server and API. Setup takes a couple of minutes, no YAML or configuration files required, and connecting a new repository imports the previous 30 days of activity so the first report is not empty.

**Pricing & Plans:** Freemium with no per-seat pricing. The Free plan is free forever and includes unlimited repositories, unlimited automations and 2 AI credits per month. Pro is $8.99/month with 100 AI credits, a Slack AI agent and priority support; Enterprise is $30/month with 500 AI credits, custom-prompt reports and custom integrations. Annual billing saves roughly 17%. One AI credit equals one chat answer, scheduled report, report preview or client-portal summary.

- **Scheduled AI reports:** Daily, weekly or monthly summaries of merged work and in-flight pull requests, generated by AI and delivered to Slack or email on your schedule and in your timezone.
- **AI agent ledger:** Attributes each commit and pull request to a person or to an agent like Claude Code, Copilot, Cursor or Codex, so you can track AI share, merge rates and agent PRs waiting on review.
- **Client portals and changelogs:** Branded, password-protected update pages written in plain language for clients, investors and executives, plus a public changelog and embeddable widget built from merged work.
- **Planned vs shipped task matching:** Links tasks from Notion, Linear, Jira, Asana, ClickUp and Trello to the pull requests that implement them, flagging work that merged while the task stayed open.
- **Proactive alerts and metadata-only access:** Notifies you about stale PRs, merges without reviewers, AI-share spikes and dormant repositories, while reading only event metadata rather than your source code.

**Strengths:** Setup takes about two minutes with OAuth or a manual webhook, and no configuration files; Reads only event metadata, never source code, and supports self-hosted GitLab; Aggregates GitHub, GitLab and Bitbucket into one consistent reporting view; No per-seat pricing, so reporting cost does not grow with team size

**Limitations:** AI-dependent features are metered by credits, which can run out on busy teams; Some advanced capabilities such as custom-prompt reports are locked to the Enterprise tier; Best value requires adopting Slack or email delivery as part of your workflow

[Profile (Markdown)](https://openaitools.app/tool/gitmore.md)

## Qwen 4 (Alibaba Qwen4)

Qwen 4 (also known as Qwen4 or Tongyi Qianwen 4) is Alibaba Cloud's fourth-generation foundation model family and multimodal AI assistant platform accessible at qwen.ai and chat.qwen.ai. Formally unveiled in training at the Hangzhou Apsara Conference on September 22, 2026 and detailed on stage at Apsara Amsterdam on October 29, 2026, Qwen 4 spearheads Alibaba's full-stack AI roadmap that scales toward 5 to 10 trillion parameters in the upcoming Qwen 4.5 and Qwen 5 generations.

The Qwen 4 series is organized into four core deployment tiers—Qwen4-Max (flagship frontier reasoning model), Qwen4-Plus (balanced enterprise API workhorse), Qwen4-Flash (low-latency, high-throughput model), and Qwen4-27B (a 27-billion-parameter open-weight model engineered to run locally on consumer PCs and single-GPU workstations)—alongside specialized variants spotted in official Qwen Code repositories such as qwen4-coder-plus and qwen4-omni-120b-think. Architecturally, Qwen 4 builds on the foundation previewed in August 2026's Qwen3.8-Flash-Next: a hybrid Gated DeltaNet + Gated Attention sparse Mixture-of-Experts (MoE) design (125B total parameters with just 6B active per token and a 51B n-gram embedding lookup layer) paired with a 1-million-token context window and Recursive Self-Improvement (RSI) post-training.

For developers, enterprises, and everyday users, the Qwen platform offers a completely free web and mobile workspace at chat.qwen.ai featuring Deep Research, Web Dev Artifacts, live search, and native image/video/audio generation (Qwen-Image 3.1 and Qwen-Audio 3.1), while open-weight checkpoints are distributed on Hugging Face, ModelScope, and Ollama alongside commercial API hosting on Alibaba Cloud Model Studio.

**Pricing & Plans:** Free multimodal web & mobile chat at chat.qwen.ai; Apache 2.0 open-weight local models (Qwen4-27B & Qwen3.8-Flash-Next architecture preview) free on Hugging Face and Ollama; commercial API on Alibaba Cloud Model Studio (~$0.15 / $0.47 per 1M tokens on Flash tiers and ~$2.00 / $6.00 per 1M tokens on Max tiers).

- **Four-Tier Qwen 4 Model Lineup (Max, Plus, Flash & 27B):** Covers every compute envelope from the multi-trillion-scale Qwen4-Max flagship and Qwen4-Plus/Flash APIs to the local PC-friendly Qwen4-27B open-weight checkpoint, plus qwen4-coder-plus and qwen4-omni-120b-think.
- **Hybrid Gated DeltaNet + Sparse MoE & N-Gram Memory:** Pioneered in the Qwen3.8-Flash-Next architecture preview, combining ultra-lean active parameter routing (6B active out of 125B) with a 51B n-gram embedding layer that trades compute for instant memorized lookup.
- **1-Million-Token Context Window Across Modalities:** Sizes the Qwen 4 generation at a full 1M-token context window across text, code, images, audio, and video for repository-wide coding and cross-document reasoning.
- **Recursive Self-Improvement (RSI) & Agentic Tool Use:** Trained via multi-cycle automated Recursive Self-Improvement across coding, math, and hardware EDA workflows—demonstrating 10,000+ autonomous tool calls in chip design and software engineering.
- **Free Qwen Chat Workspace & Open-Weight Ecosystem:** Provides free access at chat.qwen.ai with Web Dev Artifacts, Deep Research, Qwen-Image 3.1, and Qwen-Audio 3.1, plus one-command local deployment via Ollama, vLLM, and Hugging Face.

**Strengths:** Complete 4-tier ecosystem spanning cloud flagships (Qwen4-Max/Plus/Flash) and consumer-GPU open weights (Qwen4-27B); Breakthrough Gated DeltaNet + 51B n-gram memory MoE architecture delivers frontier quality at a fraction of active inference compute; 1-million-token context window and native multimodal support across text, code, vision, audio, and video; Free full-featured web assistant at chat.qwen.ai with no mandatory subscription wall for everyday research and coding

**Limitations:** Staged late-2026 rollout following Apsara Hangzhou (Sept 22) and Amsterdam (Oct 29) means flagship Qwen4-Max weights and APIs release progressively after the Qwen3.8-Flash-Next architecture preview; Largest Qwen4-Max and upcoming 5–10T parameter Qwen 4.5/5 models require cloud APIs or multi-node enterprise GPU clusters; Brand split between international Qwen (qwen.ai / Model Studio) and domestic Tongyi Qianwen can confuse first-time API adopters

[Profile (Markdown)](https://openaitools.app/tool/qwen-4.md)

## Frequently Asked Questions

### How do Gitmore and Qwen 4 (Alibaba Qwen4) compare in monthly traffic?

Gitmore has 1,021 monthly visits, while Qwen 4 (Alibaba Qwen4) has 35,101,353. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Gitmore has a month-over-month growth rate of -62.4%; Qwen 4 (Alibaba Qwen4) has -6.2%.

### How does pricing compare?

Gitmore: Freemium. Freemium with no per-seat pricing. The Free plan is free forever and includes unlimited repositories, unlimited automations and 2 AI credits per month. Pro is $8.99/month with 100 AI credits, a Slack AI agent and priority support; Enterprise is $30/month with 500 AI credits, custom-prompt reports and custom integrations. Annual billing saves roughly 17%. One AI credit equals one chat answer, scheduled report, report preview or client-portal summary. Qwen 4 (Alibaba Qwen4): Freemium. Free multimodal web & mobile chat at chat.qwen.ai; Apache 2.0 open-weight local models (Qwen4-27B & Qwen3.8-Flash-Next architecture preview) free on Hugging Face and Ollama; commercial API on Alibaba Cloud Model Studio (~$0.15 / $0.47 per 1M tokens on Flash tiers and ~$2.00 / $6.00 per 1M tokens on Max tiers).

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | Provides state-of-the-art open-weight reasoning models and low-cost APIs, but with less emphasis on multimodal Alibaba ecosystem tools. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides robust developer tools and multimodal APIs, but relies on Google's closed Gemini models rather than open-weight alternatives. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 3 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Aggregates hundreds of models behind one API gateway, but functions as a router rather than hosting native Qwen infrastructure. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 4 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Offers competing Chinese foundation model APIs and agent builders, but specializes in Zhipu AI's GLM architecture. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 5 | [Gemma Open Models by Google](https://openaitools.app/tool/gemma-open-models-by-google) | 4,900,914 | -13.5% | Freemium, Paid | Provides lightweight open-weight models for local deployment, but offers smaller parameter sizes compared to top-tier Qwen variants. | [.md](https://openaitools.app/tool/gemma-open-models-by-google.md) |
| 6 | [Groq](https://openaitools.app/tool/groq) | 3,987,936 | +10% | Paid | Delivers ultra-fast inference speeds using custom LPU hardware, but supports a more limited selection of open models. | [.md](https://openaitools.app/tool/groq.md) |
| 7 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Offers robust serverless APIs for open-source models, but lacks native training integrations specific to Alibaba's ecosystem. | [.md](https://openaitools.app/tool/together-ai.md) |
| 8 | [Tencent Hunyuan](https://openaitools.app/tool/tencent-hunyuan-large-model) | 1,485,463 | -1.2% | Contact for Pricing | Provides comparable multimodal foundation model APIs from a major tech giant, but utilizes Tencent's proprietary Hunyuan architecture. | [.md](https://openaitools.app/tool/tencent-hunyuan-large-model.md) |
| 9 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Specializes in memory-efficient fine-tuning for open-weight models, but requires external infrastructure to deploy full production APIs. | [.md](https://openaitools.app/tool/unsloth-ai.md) |
| 10 | [DeepWiki by Cognition](https://openaitools.app/tool/deepwiki-by-congnition) | 879,539 | -3.1% | Free | AI-generated wikis and chat for any public GitHub repository | [.md](https://openaitools.app/tool/deepwiki-by-congnition.md) |

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Source: https://openaitools.app/compare/gitmore-vs-qwen-4

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