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Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro. In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally. Use cases: - Web search - Deep Research Built on the new version of Qwen's Qwen3-4B-Thinking (up to 256k...

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👋 Jan

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690,176 просмотров • 10 месяцев назад •via X (Twitter)

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Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.
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Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.

👋 Jan

17,759 просмотров • 9 месяцев назад

Meet Jan-nano, a 4B model that outscores DeepSeek-v3-671B using MCP. It's built on Qwen3-4B with DAPO fine-tuning, it handles: - real-time web search - deep research Model + GGUF: To run it locally: - Install Jan Beta: - Download Jan-nano in Jan Hub - Settings -> MCP, enable MCP and add your Serper API key for web tools Full technical report will be published shortly.
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Meet Jan-nano, a 4B model that outscores DeepSeek-v3-671B using MCP. It's built on Qwen3-4B with DAPO fine-tuning, it handles: - real-time web search - deep research Model + GGUF: To run it locally: - Install Jan Beta: - Download Jan-nano in Jan Hub - Settings -> MCP, enable MCP and add your Serper API key for web tools Full technical report will be published shortly.

Menlo Research

56,600 просмотров • 1 год назад

Introducing Jan-Code-4B 💻 A compact coding model tuned for practical day-to-day tasks. Generation, refactors, debugging, tests — all runnable locally in Jan. Download Jan: Model:
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Introducing Jan-Code-4B 💻 A compact coding model tuned for practical day-to-day tasks. Generation, refactors, debugging, tests — all runnable locally in Jan. Download Jan: Model:

👋 Jan

109,873 просмотров • 3 месяцев назад

Introducing Jan-v2-VL, a multimodal agent built for long-horizon tasks. Jan-v2-VL executes 49 steps without failure, while the base model stops at 5 and other similar-scale VLMs stop between 1 and 2. It achieves longer, stable task execution in your browser without accuracy loss. 3 variants are available: - Jan-v2-VL-low (efficiency-oriented) - Jan-v2-VL-med (balanced) - Jan-v2-VL-high (deeper reasoning and longer execution) Models: To use it, update your Jan App and download Jan-v2-VL from the Model Hub. Activate Browser MCP servers for agentic use cases. Credit to the Qwen team for Qwen3-VL-8B-Thinking base model.
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Introducing Jan-v2-VL, a multimodal agent built for long-horizon tasks. Jan-v2-VL executes 49 steps without failure, while the base model stops at 5 and other similar-scale VLMs stop between 1 and 2. It achieves longer, stable task execution in your browser without accuracy loss. 3 variants are available: - Jan-v2-VL-low (efficiency-oriented) - Jan-v2-VL-med (balanced) - Jan-v2-VL-high (deeper reasoning and longer execution) Models: To use it, update your Jan App and download Jan-v2-VL from the Model Hub. Activate Browser MCP servers for agentic use cases. Credit to the Qwen team for Qwen3-VL-8B-Thinking base model.

👋 Jan

130,234 просмотров • 7 месяцев назад

Introducing a brand new way to use Jan 💛 You can now search the web, do deep research, and let Jan use your browser. Powered by Jan-v2-VL-Max, 30B model beating Gemini 2.5 Pro & DeepSeek R1 on execution benchmarks. Try it:
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Introducing a brand new way to use Jan 💛 You can now search the web, do deep research, and let Jan use your browser. Powered by Jan-v2-VL-Max, 30B model beating Gemini 2.5 Pro & DeepSeek R1 on execution benchmarks. Try it:

👋 Jan

29,403 просмотров • 6 месяцев назад

Most search models need the cloud. II-Search-4B doesn’t. 4B model tuned for reasoning with search tools, built for local use. Performance of models 10x its size. Search that is small, smart, and open.
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Most search models need the cloud. II-Search-4B doesn’t. 4B model tuned for reasoning with search tools, built for local use. Performance of models 10x its size. Search that is small, smart, and open.

Intelligent Internet

499,961 просмотров • 10 месяцев назад

Introducing Lucy: 1.7B model that Google for you It's an agentic‑search model that can even run on your phone. - Agentic search on tap - Lucy calls tools ( ‑aware) - Fits in your pocket - runs on CPU or mobile Under the hood: - Built on Qwen's Qwen3‑1.7B - Smooth multi‑category rewards replace brittle if‑else scoring - Task‑vector RLVR optimizes the "thinking" tag for targeted search moves. Benchmarks: - SimpleQA + MCP = 78.3 - Close to Jan‑Nano-4B (80.7) Run locally: - Demo uses vLLM in Jan - You can spin it up with Georgi Gerganov's llama.cpp or vLLM Models on Hugging Face: - Lucy 1.7B 40k: - Lucy 1.7B 128K:
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Introducing Lucy: 1.7B model that Google for you It's an agentic‑search model that can even run on your phone. - Agentic search on tap - Lucy calls tools ( ‑aware) - Fits in your pocket - runs on CPU or mobile Under the hood: - Built on Qwen's Qwen3‑1.7B - Smooth multi‑category rewards replace brittle if‑else scoring - Task‑vector RLVR optimizes the "thinking" tag for targeted search moves. Benchmarks: - SimpleQA + MCP = 78.3 - Close to Jan‑Nano-4B (80.7) Run locally: - Demo uses vLLM in Jan - You can spin it up with Georgi Gerganov's llama.cpp or vLLM Models on Hugging Face: - Lucy 1.7B 40k: - Lucy 1.7B 128K:

Menlo Research

20,205 просмотров • 11 месяцев назад

If you are not using Jan with Jan-V1-4B, drop anything you are doing and install it now! It's a little Open gem. BTW: yes, I'm an AC Milan fan 😢
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If you are not using Jan with Jan-V1-4B, drop anything you are doing and install it now! It's a little Open gem. BTW: yes, I'm an AC Milan fan 😢

Ivan Fioravanti ᯅ

19,984 просмотров • 10 месяцев назад

Just made an MCP server to use Anthropic’s new web search tool. What I love about it is that the search is agentic. You can use any model to call a Claude instance that returns processed search results. Or specify how deep the search should be. 🔗 Link in the comments.
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Just made an MCP server to use Anthropic’s new web search tool. What I love about it is that the search is agentic. You can use any model to call a Claude instance that returns processed search results. Or specify how deep the search should be. 🔗 Link in the comments.

Pietro Schirano

29,189 просмотров • 1 год назад

We've added a new "reasoning" focus (beta) on Perplexity for Pro users. It will use the new OpenAI o1-mini. There is no search integration yet. The model is slow, and usage is limited because of rate limits. It is good for puzzles, math, and coding. Pro searches are your best way to use multi-step reasoning + web search.
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We've added a new "reasoning" focus (beta) on Perplexity for Pro users. It will use the new OpenAI o1-mini. There is no search integration yet. The model is slow, and usage is limited because of rate limits. It is good for puzzles, math, and coding. Pro searches are your best way to use multi-step reasoning + web search.

Aravind Srinivas

288,789 просмотров • 1 год назад

You can run Kimi-K2-Thinking, the most strongest agentic model, in Jan through Hugging Face. Add it to your Hugging Face Inference models to use it.
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You can run Kimi-K2-Thinking, the most strongest agentic model, in Jan through Hugging Face. Add it to your Hugging Face Inference models to use it.

👋 Jan

40,181 просмотров • 7 месяцев назад

The new Qwen 3.5 4B runs incredibly well on M5. The model is close to GPT-4o in benchmarks. Running fully on-device with MLX.
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The new Qwen 3.5 4B runs incredibly well on M5. The model is close to GPT-4o in benchmarks. Running fully on-device with MLX.

Adrien Grondin

230,383 просмотров • 3 месяцев назад

Thank you to everyone who has played The Alters and to 11 bit studios | NEW GAME REVEALED for letting me be part of The Alters | MAJOR UPDATE OUT NOW🐑 love from, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, and Jan. #TheAlters
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Thank you to everyone who has played The Alters and to 11 bit studios | NEW GAME REVEALED for letting me be part of The Alters | MAJOR UPDATE OUT NOW🐑 love from, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, Jan, and Jan. #TheAlters

Alex Jordan

63,640 просмотров • 1 год назад

Ollama now supports subagents and web search in Claude Code! Subagents can run tasks in parallel, such as file search, code exploration, and research, each in their own context. No MCP servers to configure or API keys required. Try it with any model on Ollama's cloud: ollama launch claude --model minimax-m2.5:cloud
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Ollama now supports subagents and web search in Claude Code! Subagents can run tasks in parallel, such as file search, code exploration, and research, each in their own context. No MCP servers to configure or API keys required. Try it with any model on Ollama's cloud: ollama launch claude --model minimax-m2.5:cloud

ollama

84,028 просмотров • 4 месяцев назад

QWEN 3.5 4b MLX running locally with a milk avatar Model by ToxSam
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QWEN 3.5 4b MLX running locally with a milk avatar Model by ToxSam

tensorfish

125,990 просмотров • 3 месяцев назад

Alibaba just changed the AI game! Their QwQ-32B model delivers premium performance but it's completely free and open source. • Outperforms on key benchmarks • 32B parameters (vs 671B for DeepSeek) • Run locally or use web interface • Thinking mode for reasoning • Web search integration Save this video if you need powerful AI tools without the expensive subscriptions 💡 Want the SOP? DM me.
8:47

Alibaba just changed the AI game! Their QwQ-32B model delivers premium performance but it's completely free and open source. • Outperforms on key benchmarks • 32B parameters (vs 671B for DeepSeek) • Run locally or use web interface • Thinking mode for reasoning • Web search integration Save this video if you need powerful AI tools without the expensive subscriptions 💡 Want the SOP? DM me.

Julian Goldie SEO

16,920 просмотров • 1 год назад

Running Qwen 3.5 4B on my iPhone 17 Pro Max Very smart & capable model for how small it is Very fast as well
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Running Qwen 3.5 4B on my iPhone 17 Pro Max Very smart & capable model for how small it is Very fast as well

Ahmad

107,463 просмотров • 3 месяцев назад

Not enough people are talking about NVIDIA's new Nemotron-3-Nano (4B) model! 🤯 Hybrid Mamba + Attention architecture, designed as a unified model for reasoning and non-reasoning tasks. So small and efficient, it can run 100% locally in your web browser at 75 tokens per second.
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Not enough people are talking about NVIDIA's new Nemotron-3-Nano (4B) model! 🤯 Hybrid Mamba + Attention architecture, designed as a unified model for reasoning and non-reasoning tasks. So small and efficient, it can run 100% locally in your web browser at 75 tokens per second.

Xenova

50,063 просмотров • 3 месяцев назад

We are recruiting beta testers for Sela Agent. Apply: Recruitment: Jan 7 to Jan 11 Test period: Jan 12 to Jan 30 Selected testers will receive the Sela Pioneer role in Discord. Details and requirements:
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We are recruiting beta testers for Sela Agent. Apply: Recruitment: Jan 7 to Jan 11 Test period: Jan 12 to Jan 30 Selected testers will receive the Sela Pioneer role in Discord. Details and requirements:

Selanet

12,848 просмотров • 5 месяцев назад

introducing Nozomio Labs v1. state of the art search and index API to reduce hallucinations in AI agents. use it inside any coding agent or power your own products (thread):
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introducing Nozomio Labs v1. state of the art search and index API to reduce hallucinations in AI agents. use it inside any coding agent or power your own products (thread):

Arlan

220,709 просмотров • 3 месяцев назад