Qwen3.8-27B-DFlash2
incoaiapache-2.0text

Qwen3.8-27B-DFlash2

Updated Oct 31, 2026
Parameters
1.9B
Context
262,144
License
apache-2.0
Q4 GGUF
1.14 GB
Updated
Oct 31, 2026

Q4 GGUF download: incoai/Qwen3.8-27B-DFlash2-GGUF - 1.14 GB on disk, read 2026-10-30. VRAM figures above are estimates; this is the actual file size.

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at FP16
4 of 4 quantizations fit Qwen3.8-27B-DFlash2 with real runtime overhead.
Q4_K_M
1 GB
Q5_K_M
1 GB
Q8_0
2 GB
FP16
4 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve incoai/Qwen3.8-27B-DFlash2

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

Qwen3.8-27B-DFlash2 is a 1.9B-parameter apache-2.0 model from incoai. At Q4_K_M it needs roughly 1 GB of VRAM, placing it in the CPU / ≤4 GB hardware tier.

Popularity

Qwen3.8-27B-DFlash2 has 376,317 downloads in the last month on HuggingFace and 294 likes.

Frequently asked

Quick answers to common questions

How much VRAM does Qwen3.8-27B-DFlash2 need?

Qwen3.8-27B-DFlash2 with 1.9B parameters needs approximately 1 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is Qwen3.8-27B-DFlash2 better than other incoai models?

Qwen3.8-27B-DFlash2 has 1.9B parameters with 262,144 context - a strong choice for general use.

What license is Qwen3.8-27B-DFlash2 under?

Qwen3.8-27B-DFlash2 is released under the apache-2.0 license, making it suitable for most commercial and personal projects.

What hardware runs Qwen3.8-27B-DFlash2 well?

With 1.9B parameters, Qwen3.8-27B-DFlash2 requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for Qwen3.8-27B-DFlash2?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~1 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

How long can Qwen3.8-27B-DFlash2's context window handle?

Qwen3.8-27B-DFlash2 supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.

What models compete with Qwen3.8-27B-DFlash2?

Qwen3.8-27B-DFlash2 competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec