surya-ocr-2 vs Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF
Specs, VRAM requirements and download trends — updated 10 November 2026.
datalab-to · A · Open weights
Params
690 M
Context
—
30d
975 K
openrail licence · conditional
cdiamond · B · Open weights
Params
—
Context
—
30d
3.3 M
apache-2.0 · commercial OK
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | surya-ocr-2 | Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF |
|---|---|---|
| Parameters | 690 M | — |
| Architecture | Qwen3_5ForConditionalGeneration | — |
| Context length | — | — |
| Licence | openrail | apache-2.0 |
| Commercial use | Conditional | Allowed |
| Languages | — | — |
| Downloads 30d | 975,415 | 3,260,065 |
| Downloads all time | 5.8 M | 9.6 M |
| Quantizations on the Hub | SAFETENSORS | GGUF |
| Gated | No | No |
| First seen on the Hub | 2026-05-14 | 2026-08-17 |
Download trend
Daily snapshots, last 90 days (13 Aug – 10 Nov)
5.0 M975 K
surya-ocr-2
Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
surya-ocr-2 · fp16
2.1 GB / 24 GB
Adjacent comparisons
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Qwen3.8-27B vs Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF
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gemma-4-31B-it vs Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF
Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF vs Qwen3.8-Flash-Next-GSQ-RCO-GGUF
Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF vs GLM-5.3-Flash