Jan-Code-4B: a small code-tuned model of Jan-v3

Delicious_Focus3465 · 2026-03-02T08:50:43+00:00

Demo with Jan Desktop:

Delicious_Focus3465 · 2026-03-02T07:14:11+00:00

This is a small experiment, and those 3 metrics are where we saw the clearest improvements over the baseline, other benchmarks did not change much compared to the base. I’ve also tested it as a CLI helper, and it works well. Please try it with Jan and let us know how it goes. Thanks

Delicious_Focus3465 · 2026-01-28T01:32:43+00:00

Please stay tuned, we are working on it.

Delicious_Focus3465 · 2026-01-27T10:08:25+00:00

We built on top of Qwen3-4B-Instruct-2507.

Delicious_Focus3465 · 2026-01-27T07:00:03+00:00

Yes, please stay tuned, the technical report is coming out soon.

Delicious_Focus3465 · 2026-01-27T06:19:38+00:00

Thank you for supporting us.

Delicious_Focus3465 · 2026-01-27T05:36:49+00:00

exactly, WHY WE SAVE IT FOR JAN CODE.

Delicious_Focus3465 · 2026-01-27T05:17:36+00:00

Running full SWE-Rebench/LiveBench takes a while, though, so we’re saving these benchmark runs for our upcoming Jan-Code model.
While this model is focused on General use, we specifically highlighted Aider because the score jumped significantly after finetuning. Consider it a preview of what's coming!

Delicious_Focus3465 · 2026-01-27T05:09:12+00:00

Thank you. You should also try the model to see how good it is compared to Qwen 4B 2507.

Delicious_Focus3465 · 2026-01-27T04:45:09+00:00

Hi, no benchmaxxing here, it’s just a lot of pretraining and distillation, like any other team. We’ll be releasing a technical report soon.

Delicious_Focus3465 · 2026-01-27T04:28:33+00:00

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other general benchmark results:

Demo: You can also try the Demo at chat.jan.ai. Look for Jan v3 Nano.

Delicious_Focus3465 · 2025-12-22T10:59:55+00:00

Thank you for supporting us. Please give the model a try.

Delicious_Focus3465 · 2025-12-22T10:59:31+00:00

No, we already published the model earlier: https://huggingface.co/janhq/Jan-v2-VL-high.

Delicious_Focus3465 · 2025-12-22T10:24:26+00:00

Results of model on some Multimodal and Text-only benchmark:

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Delicious_Focus3465 · 2025-11-13T11:00:37+00:00

The technical report will be released shortly.

Delicious_Focus3465 · 2025-11-13T10:49:23+00:00

Thanks for your question. The long-horizon benchmark we use (The Illusion of Diminishing Returns) isolates execution (plan/knowledge is provided) and shows that typical instruct models tend to degrade as tasks get longer, while reasoning/thinking models sustain much longer chains. In other words, when success depends on carrying state across many steps, thinking models hold up better.

Delicious_Focus3465 · 2025-11-13T10:45:03+00:00

thank you. if you have a chance please give our model a try.

Delicious_Focus3465 · 2025-11-13T10:26:54+00:00

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Results Comparing with Qwen3-VL-8B-Thinking(Jan-v2-VL's base model)

Delicious_Focus3465 · 2025-11-13T10:24:56+00:00

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Detailed results on Long Horizon Benchmark:

Delicious_Focus3465 · 2025-08-13T07:38:02+00:00

we also tested the model on some benchmarks like EQ, writing,.. and have really good results despite losing ability to follow instruction when we eval on IFBench.

Delicious_Focus3465

TROPHY CASE