ThinkingCap-Qwen3.8-27B-GGUF
GGUF / llama.cpp quantizations of bottlecapai/ThinkingCap-Qwen3.8-27B — the ThinkingCap finetune of Qwen3.8-27B that cuts reasoning tokens by 37% on average while holding 85.8% average accuracy against the base model's 86.6%.
Params
27.0 B
Context
—
Downloads 30d
923 K
Likes
97
Download history
daily snapshots · 17 days943 K851 K
Oct 25Oct 30Nov 5Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| ThinkingCap-Qwen3.8-27B-IQ4_XS.gguf | IQ4_XS | 15.5 GB | 21.6 GB | ⚠️ Tight — reduce context |
| ThinkingCap-Qwen3.8-27B-Q4_K_M.gguf | Q4_K_M | 17.4 GB | 23.7 GB | ⚠️ Tight — reduce context |
| ThinkingCap-Qwen3.8-27B-Q6_K.gguf | Q6_K | 23.9 GB | 30.8 GB | ❌ Won’t fit |
| ThinkingCap-Qwen3.8-27B-Q8_0.gguf | Q8_0 | 29.0 GB | 36.5 GB | ❌ Won’t fit |
| ThinkingCap-Qwen3.8-27B-f16.gguf | GGUF | 54.7 GB | 64.7 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Parameters
- 27.0 B
- Licence
- other
- First seen on the Hub
- 2026-09-23
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-25
Compare with any image-text-to-text model