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// Qwen · Reranker

Qwen3-VL-Reranker-2B: VRAM & local deployment

2.13B parameters. About 1.9 GB at 4-bit and 5.2 GB at BF16.

released 2026-01-07licence: Commercial OKmemory figures are estimates

01Specs

PublisherAlibaba Qwen · Qwen
Family / seriesQwen · Qwen3-VL-Reranker
TypeReranker (text-ranking)
Parameters2.13B Source: counted from official safetensors weights
Released weightsBF16 · 4.3 GBdownload
LicenceApache-2.0 · Commercial OKPermissive licence (Apache-2.0 / MIT / CC-BY / OpenMDW): commercial use allowed.
Released2026-01-07 (Hugging Face repo created)

02How much VRAM it needs (estimate)

Rerankers are small; memory grows with batch size and sequence length.

PrecisionWeightsWeights + overheadSmallest GPUMac
BF16 / FP16 (original)4.3 GB 5.2 GB 8GB GPUMac 16GB
FP8 / INT8 / Q8_02.3 GB 3.0 GB 8GB GPUMac 16GB
4-bit (Q4_K_M / AWQ / GPTQ-Int4)1.3 GB 1.9 GB 8GB GPUMac 16GB

Bits per weight: BF16 16, FP8 8.5, 4-bit 4.85. “Fits” = total ≤ 90% of memory; Mac GPU can use ~2/3 of unified memory (≤36GB) or ~3/4 (larger). For MoE, all experts must be in memory, so size by total parameters. Method →

03How to run it

Only runtimes the publisher or the runtime’s official library names for this model.

Which inference engine to choose →

04Official repositories & quantised builds

1 official repo(s) from Qwen.

05Other Qwen models

All 112 →
ModelParams4-bit totalReleased
Qwen3-VL-Reranker-8B · same series8.77B6.3 GB2026-01-07
Qwen-Image-2.1-Turbo7.12B5.2 GB2026-10-09
Qwen-Image-2.17.12B5.2 GB2026-09-14
Qwen3.8-Flash-Next180B / 6B121 GB2026-08-24
Qwen3.8-2.4T-A95B2.4T / 95B1.60 TB2026-08-08
Qwen3.8-27B27.8B19.6 GB2026-08-05
Qwen3.6-27B27.8B19.6 GB2026-04-21
Qwen3.6-35B-A3B36B / 3B24.6 GB2026-04-15
Qwen3.5-0.8B873M1.2 GB2026-02-28

06Sources

Data checked 2026-04-16. Parameters, context and licence are copied from the official repository; memory figures are our estimates.

Data updated: Self-host open models(UTC+8)