# Qwen 4 (Alibaba Qwen4) vs Rivet.dev

Qwen 4 (Alibaba Qwen4) records 35,101,353 monthly visits with -6.2% month-over-month growth and Freemium pricing. Rivet.dev records 21,359 monthly visits with -44.3% growth and Freemium, Contact for Pricing pricing.

| Metric | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | [Rivet.dev](https://openaitools.app/tool/rivet-dev) |
| :--- | :--- | :--- |
| Website URL | https://qwen.ai | https://rivet.dev |
| Categories | Large Language Models (LLMs), Open Source AI Models, AI Chatbot, AI Assistant | AI Agent, AI Workflow, AI Developer Tools, AI App Builder |
| Pricing Model | Freemium | Freemium, Contact for Pricing |
| Monthly Visits | 35,101,353 | 21,359 |
| MoM Growth Rate | -6.2% | -44.3% |
| Primary Market | Russia | United States |
| Direct Visits | 25,020,350 | 10,710 |
| Review Score | 4.7 | 4.5 |
| Saved Count | 1,180 | 0 |
| Supported Platforms | Website, API, Open Source | Website |

## 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)

## Rivet.dev

At its core Rivet replaces the container per agent with an in-process primitive. An Actor runs inside your existing Node.js or Bun backend rather than in its own container or VM, which is why Rivet reports cold starts measured in single-digit milliseconds and a footprint of tens of kilobytes per Actor instead of hundreds of megabytes. Each Actor carries a SQLite database for memory, can access a filesystem and shell, sleeps when idle, and wakes with its durable state ready for the next request.

The platform handles the operational pieces teams usually build themselves: fault tolerance that reschedules Actors when a node goes down, multi-region placement that routes requests to wherever an Actor currently lives, end-to-end type safety where Actor definitions generate client types, and scheduling via cron or self-set timestamps. Storage is pulled apart into two tiers — a fast SSD for instant writes and object storage that settles writes at a fraction of the cost — so running many small databases stays affordable.

Rivet positions itself as infrastructure for the "agentic era" and can be deployed as a managed cloud, inside your own VPC through a bring-your-own-cloud model, or fully self-hosted down to air-gapped networks. It is open source under Apache 2.0, backed by Y Combinator and a16z Speedrun, and integrates with popular coding agents and frameworks.

**Pricing & Plans:** Rivet Cloud uses a plan-plus-nodes model. The control plane is Free ($0) for prototyping, Hobby at $10/month, Team at $120/month, and Enterprise at $900/month, each raising control-plane redundancy, Actor Node caps, and support. Actor Nodes are billed per month on top, from $4.20 (R-5) to $94.50 (R-160). Self-hosting is free and open source under Apache 2.0, and startups from Y Combinator or a16z Speedrun get 50% off the Team plan for 12 months.

- **Durable actors with persistent state:** Every Actor gets a SQLite database and a filesystem, so an agent's memory and progress survive restarts and idle periods without a separate database.
- **Lightweight secure sandboxing:** Run untrusted or AI-generated code on your own infrastructure with fine-grained control over network access, filesystem permissions, and resource limits.
- **Fault tolerance and workflows:** A node failure reschedules its Actors elsewhere with state intact, and multi-step work replays after a crash — with no checkpointing harness to build yourself.
- **Realtime and multiplayer:** Address an Actor directly over HTTP or hold a live WebSocket, and use the React SDK to subscribe components to an Actor's state in real time.
- **One-binary deployment and observability:** Ship with a single stateless Rust binary, embeds storage in S3-compatible buckets, and emits OpenTelemetry traces, metrics, and logs to your existing collector.

**Strengths:** Four-digit millisecond cold starts and a very small per-Actor memory footprint let a single server host far more agents; Open source (Apache 2.0) with a single Rust binary, so it can be self-hosted, run in a VPC, or air-gapped; Durable state via per-Actor SQLite plus object-storage-backed tiers keeps agents restart-safe and cheap; Strong developer ergonomics: typed SDKs, a React SDK, WebSocket networking, and OpenTelemetry baked in

**Limitations:** Requires Node.js or Bun and a working Rust-based control plane deployment for self-hosting, so it favors backend engineers over no-code users; Advanced durability and sandboxing concepts (Actors, WarpDrive storage) carry a learning curve; Managed cloud cost scales with Actor Nodes, which can climb for many mid-sized/sized nodes; Enterprise features like multi-tenancy and hardened compliance guidance sit behind sales conversations

[Profile (Markdown)](https://openaitools.app/tool/rivet-dev.md)

## Frequently Asked Questions

### How do Qwen 4 (Alibaba Qwen4) and Rivet.dev compare in monthly traffic?

Qwen 4 (Alibaba Qwen4) has 35,101,353 monthly visits, while Rivet.dev has 21,359. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Qwen 4 (Alibaba Qwen4) has a month-over-month growth rate of -6.2%; Rivet.dev has -44.3%.

### How does pricing compare?

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). Rivet.dev: Freemium, Contact for Pricing. Rivet Cloud uses a plan-plus-nodes model. The control plane is Free ($0) for prototyping, Hobby at $10/month, Team at $120/month, and Enterprise at $900/month, each raising control-plane redundancy, Actor Node caps, and support. Actor Nodes are billed per month on top, from $4.20 (R-5) to $94.50 (R-160). Self-hosting is free and open source under Apache 2.0, and startups from Y Combinator or a16z Speedrun get 50% off the Team plan for 12 months.

## 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 | [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | +6% | Contact for Pricing | Delivers exceptionally high-throughput inference for open-weight models, but focuses more on general open-source deployment than Qwen-specific tools. | [.md](https://openaitools.app/tool/fireworks-ai.md) |

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

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)