estimate, except measured file sizes

Can I run Qwen3.8-27B locally?

27.78B parameters. Parameter count is an estimate.

Licence:

Apache-2.0 source

Context:

262,144 tokens

Modality:

text + image/video in, text out

Released:

not recorded

Dense vision-language model, Apache-2.0 (the LICENSE file is Apache 2.0, and the card metadata says apache-2.0). The card's parameter headline is 27B. Hugging Face safetensors metadata lists 27,781,427,952 parameters, all BF16. 27.78B is that count to two decimals, so paramsEstimated stays true. 64 layers in text_config: 48 linear_attention (Gated DeltaNet) and 16 full_attention (Gated Attention). 24 query heads, 4 KV heads, head dim 256. Config max_position_embeddings is 262,144. The card says that window is extensible to 1,000,000 tokens with a RoPE change; this catalog uses 262,144. Linear-attention layers are stored with a sliding window of 0 so this formula gives them no token KV. The KV figure uses only the 16 full-attention layers and is an FP16 estimate. The card's citation is August 2026. Hugging Face lists the repo as created on 5 August 2026. That createdAt is repo metadata, not a dated announcement in the citation. Vision projector and the MTP drafter are separate files, not rows in the memory table. On unsloth/Qwen3.8-27B-GGUF, checked 19 Oct 2026: mmproj-F16 is 0.93 GB (927,607,488 bytes) and mmproj-BF16 is 0.93 GB (931,146,432 bytes). MTP/mtp-Qwen3.8-27B-Q4_0.gguf is 1.37 GB (1,369,590,656 bytes). Main GGUF sizes are decimal GB from that tree, single files: UD-IQ2_XXS 7.27, UD-IQ3_XXS 10.93, UD-IQ4_XS 14.25, UD-Q4_K_M 16.46, UD-Q4_K_XL 17.56, UD-Q5_K_XL 20.88, UD-Q6_K 21.98, Q8_0 29.05. A separate community speed table for one RTX 3090 is stored on this row. It is not the calculator estimate.

Parameter source · Architecture source · Model page

Memory per quant

KV is at 8,192 tokens. Overhead is 0.8 GB. Both are estimates. A measured file size is labelled. The last column is the cheapest machine that fits the total fully.

Cheapest rig that fits

UD-Q4_K_M, full: GeForce RTX 3090 24GB, €1,224 (used (median of sold listings))

UD-Q4_K_M, slow, partly in system RAM: Budget PC with RTX 3060 12GB, slow, partly in system RAM, €1,357 (estimate)

UD-IQ2_XXS (smallest file), full: GeForce RTX 3060 12GB, €257 (used (median of sold listings))

UD-IQ2_XXS (smallest file), slow, partly in system RAM: Nothing on our list of 34 machines fits this quant.

Prices moved: see Building a local LLM rig in the RAMageddon.

On a specific GPU

• Qwen3.8-27B on RTX 3060 12GB
• Qwen3.8-27B on RTX 4060 Ti 16GB
• Qwen3.8-27B on RTX 3090
• Qwen3.8-27B on RTX 4090
• Qwen3.8-27B on RTX 5080
• Qwen3.8-27B on RTX 5090
• Qwen3.8-27B on RX 7900 XTX
• Qwen3.8-27B on Dual RTX 3090
• Qwen3.8-27B on Dual RTX 4090