Qwen3 Reranker 0.6B

By our estimate, Qwen3 Reranker 0.6B needs about 0.9 GB at Q4, 1.2 GB at Q8 and 1.9 GB at FP16 of VRAM. That covers the weights plus headroom for a short context, and longer contexts need more.

Yes, by our estimates Qwen3 Reranker 0.6B fits on an 8 GB GPU at FP16 (about 1.9 GB) and at higher precision on larger cards.

Yes, a Mac with at least 8 GB of unified memory should run Qwen3 Reranker 0.6B at Q4, which needs an estimated 0.9 GB. This assumes macOS gives the GPU about 75% of unified memory.

Yes, PrimeIntellect lists a free Qwen3 Reranker 0.6B endpoint at $0 per 1M input and output tokens. Free endpoints often have tighter rate limits.

1 of 1 tracked Qwen3 Reranker 0.6B endpoints had 99% uptime or better over the last day. The best was PrimeIntellect at 100.0%.

PrimeIntellect offers zero data retention for Qwen3 Reranker 0.6B, so prompts are not stored after the request.

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Yes, Qwen3 Reranker 0.6B has open weights, so you can run it on your own hardware and keep prompts on your own machines.

Run Qwen3 Reranker 0.6B locally

Qwen3 Reranker 0.6B has a 33K token context window.

No, Qwen3 Reranker 0.6B takes text input only.

Similar models from other labs include Nemotron 3.5 Rerank 8B (NVIDIA), rerank-2.5-lite (VoyageAI by MongoDB) and rerank-2.5 (VoyageAI by MongoDB). They are the closest matches by kind and release date.

Nemotron 3.5 Rerank 8BQwen3 Reranker 0.6B vs Nemotron 3.5 Rerank 8Brerank-2.5-liteQwen3 Reranker 0.6B vs rerank-2.5-litererank-2.5Qwen3 Reranker 0.6B vs rerank-2.5

Both have a 33K token context window.

Qwen3 Reranker 8BQwen3 Reranker 0.6B vs Qwen3 Reranker 8B

Qwen3 Reranker 0.6B has open weights, so you can download and run it yourself.

The Qwen3 Reranker 0.6B weights are on Hugging Face at Qwen/Qwen3-Reranker-0.6B.

Run Qwen3 Reranker 0.6B locally

Qwen3 Reranker 0.6B was made by Qwen. It was first listed on OpenRouter on August 26, 2026.

More from Qwen

Yes, PrimeIntellect offers a free Qwen3 Reranker 0.6B API endpoint. Its weights are also open, so you can run it on your own hardware without API fees.

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