bge-reranker-v2-m3

Rerank BAAI Partly verified
  • Open weights

Prices

0 offerings · prices as listed

No priced offering is listed for this model yet.

Run locally

Weights: BAAI/bge-reranker-v2-m3
  • Parameters 0.6B
  • Dense
  • Native precision FP32
  • Layers 24
  • KV cache per token 96 KB
  • Config positions 8K (config.json max_position_embeddings)
My hardware GeForce RTX 4090 24 GB · 1008 GB/s · 64 GB DDR5 dual channel · 89.6 GB/s
On your hardware · GeForce RTX 4090
Runs well FP32 (native) (automatic) 8K context 164–246 tok/sOne GPU
WeightsKV cacheOverheadUsable
Needs
≈ 3.4 GB (weights 2.1 (maker’s file) + KV cache 0.8 + overhead 0.5)
Usable
21.6 GB (90% of its memory)
Generation speed
164–246 tok/s
Longest context
8K (the model’s limit)
First token
about 0.02–0.03 s for a 2K prompt
PrecisionWeightsNeeds at 8KOn your hardwareLongest context
FP32 (native)maker’s file2.1 GB≈ 3.4Runs well 164–246 tok/s8K
Q8_00.6 GB≈ 1.8Runs well 358–537 tok/s8K
FP80.5 GB≈ 1.8Runs well 367–551 tok/s8K
Q6_K0.4 GB≈ 1.7Runs well 396–595 tok/s8K
Q5_K_M0.4 GB≈ 1.6Runs well 417–625 tok/s8K
Q5_00.4 GB≈ 1.6Runs well 422–632 tok/s8K
Q4_K_M0.3 GB≈ 1.6Runs well 438–657 tok/s8K
Q4_00.3 GB≈ 1.5Runs well 448–672 tok/s8K
IQ4_XS0.3 GB≈ 1.5Runs well 455–683 tok/s8K
Q3_K_Mquality drops0.3 GB≈ 1.5Runs well 465–698 tok/s8K
IQ3_XXSquality drops0.2 GB≈ 1.5Runs well 493–739 tok/s8K
Q2_Kquality drops0.2 GB≈ 1.4Runs well 495–742 tok/s8K
IQ2_XXSquality drops0.1 GB≈ 1.4Runs well 530–795 tok/s8K

Click a row to choose a precision. “Maker’s file” sizes are the maker’s own files; others are parameters × bits per weight.

Compared with other hardware

Each at the highest precision it runs. Click one for details.

Smallest that runs it (Q4_K_M, 8K): GPU GeForce RTX 3080; unified memory Apple M5 · 16 GB.

Run commands

vLLM
vllm serve BAAI/bge-reranker-v2-m3 --max-model-len 8192
Memory to fine-tune
Full≈ 11.0 GBFits your hardware
LoRA≈ 3.7 GBFits your hardware
QLoRA≈ 2.9 GBFits your hardware

Batch 1, 2,048-token sequences, gradient checkpointing; LoRA and QLoRA train rank-16 adapters on the attention projections.

Estimates; facts from the maker’s Hugging Face repositories, as of 2026-11-06. How it’s estimated

Cited scores

From third-party leaderboards, not measured by us

No cited leaderboard covers rerank models yet.

No changes recorded yet.

Sources

Some values on this page are still waiting to be checked against official pages: a filled dot is verified, a hollow one is not yet (with or without a source on file). How we verify data

BAAI · China · baai.ac.cn

Snapshots, the same family and other models from this provider