Runs comfortably: Qwen3.8-27B needs 21.20 GiB on DGX Spark (GB10) (Rough estimate)
GB10 is the superchip named on this record, NVIDIA DGX Spark (GB10, 128 GB unified). 128 GB LPDDR5x unified memory on the GB10 Superchip.
Runs comfortably. Needs 17.61 GiB–21.20 GiB on DGX Spark (GB10) (128 GB LPDDR5x coherent unified system memory) against 112.00 GiB net. GGUF UD-Q4_K_M (Unsloth), 32,768 tokens. Rough estimate 128 GB LPDDR5x coherent unified system memory is not discrete VRAM.
Conditional memory judgement for one configuration. Change context, quant, or engine and the conclusion can change. Configuration used on this page: GGUF UD-Q4_K_M (Unsloth), 32,768 cached tokens, 1 sequence, engine llama.cpp. Status: Likely fits. Software: Not verified..
How this estimate is calculated
Catalog config for Qwen/Qwen3.8-27B (revision 1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0) is the Hugging Face config.json linked below. text_config records 64 layers, hidden size 5,120, 24 attention heads, 4 KV heads, head_dim 256, and max_position_embeddings 262,144. The hybrid spec is 16 groups of 3 Gated DeltaNet layers and 1 gated-attention layer (16 attention layers, 48 linear layers). KV uses those attention layers only. The all-layer GQA formula is not used. This page pins GGUF UD-Q4_K_M (Unsloth), file Qwen3.8-27B-UD-Q4_K_M.gguf from unsloth/Qwen3.8-27B-GGUF, 16,464,440,224 bytes. The model page auto-select is GGUF Q4_K_M (mradermacher), file Qwen3.8-27B.Q4_K_M.gguf, a different published file. At 32,768 tokens, 1 sequence, FP16 KV, llama.cpp, the calculator estimates 17.61 GiB–21.20 GiB. This catalog has no calibration and no planned benchmark for this model. The range is a calculator estimate, not a measured run.
On DGX Spark (GB10) the catalog net budget is 112.00 GiB after the default reserve. 128 GB LPDDR5x coherent unified system memory is unified memory, one shared pool. Host RAM is not added on top.
- config.json num_hidden_layers64
- config.json hidden_size5,120
- config.json num_attention_heads24
- config.json num_key_value_heads4
- config.json head_dim256
- config.json max_position_embeddings262,144
- catalog hybrid groups16
- Gated DeltaNet layers48
- gated-attention layers16
- linear_num_key_heads16
- linear_num_value_heads48
- linear_key_head_dim128
- linear_value_head_dim128
- linear_conv_kernel_dim4
- recurrent state dtypefp32
- total parameters27,781,427,952
- weight fileQwen3.8-27B-UD-Q4_K_M.gguf (16,464,440,224 bytes)
Calculator notes for this setup
- Weight bytes come from the selected weight files only, not from every file in the repository.
- Counted files: Qwen3.8-27B-UD-Q4_K_M.gguf.
- Download file size is not peak GPU memory. Runtime layout, allocator padding, and KV are extra.
- This checkpoint has a vision component. Text-only inference does not include vision encoder or projector bytes.
- Multi-token prediction / draft weights exist and are not included unless enabled.
- Hybrid layout: 16 groups of Gated DeltaNet plus gated attention (16 attention layers, 48 linear layers).
- Attention KV uses 16 gated-attention layers, 4 KV heads, head dim 256. Linear layers are not counted as extra KV layers.
- Gated DeltaNet recurrent state uses 1 sequences × 48 layers × 48 value heads × 128×128 × fp32 element size. It does not grow with context the way KV does, and is not treated as zero.
- Gated DeltaNet conv state uses 1 sequences × 48 layers × recorded channels × kernel 4 × fp32. Layout follows the published kernel dim, not a runtime dump.
- Using 4 KV heads, not 24 query heads.
- KV dtype is independent of weight quantization unless you change it.
- Recurrent and conv state dtype is independent of KV cache dtype. Changing KV precision does not silently change state precision.
- Context budget is the number of cached tokens per sequence (prompt plus reserved generation).
- Concurrent sequences share one model replica; weights are not multiplied by sequence count.
- Hybrid cache packing differs by engine (Transformers recurrent/conv vs vLLM mamba_cache_dtype / mamba_ssm_cache_dtype). This is a partial estimate, not a complete green result.
- Unified memory is a shared CPU/GPU pool. Host RAM is not added on top of this capacity.
- llama.cpp compute buffers grow with context and batch. Values here are user-adjustable scenarios, not measured traces — unless a matching calibration is shown.
- config.json — revision 1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0
- Qwen3.8-27B model card
- unsloth/Qwen3.8-27B-GGUF weight repo
- Methodology
- Qwen3.8-27B VRAM
- NVIDIA DGX Spark product page — 128 GB LPDDR5x coherent unified system memory. This is not dedicated VRAM. Default reserve deducts OS and other processes. Multiple Sparks are not one pool.
Verdict on NVIDIA DGX Spark (GB10, 128 GB unified)
Yes, run Q8_0. The calculator puts it at 27.8 GiB–33.1 GiB at 8,192 tokens, inside 112.0 GiB of usable unified memory (after the OS reserve).
With Q8_0, the longest context that still counts as a fit is about 262,144 tokens (the model's full 262,144-token window), one sequence, fp16 KV cache.
| GGUF quant | File weights | KV cache | Estimated total | Verdict |
|---|---|---|---|---|
| Q8_0 (recommended) | 27.1 GiB | 0.5 GiB | 27.8 GiB–33.1 GiB | Comfortable |
| Q6_K | 20.9 GiB | 0.5 GiB | 21.7 GiB–25.9 GiB | Comfortable |
| Q5_K_M | 18.2 GiB | 0.5 GiB | 19.0 GiB–22.7 GiB | Comfortable |
| Q4_K_M | 15.7 GiB | 0.5 GiB | 16.4 GiB–19.7 GiB | Comfortable |
Engine llama.cpp, one sequence, fp16 KV. File weights are the published GGUF sizes in the catalog. Totals come from the same calculator that powers the tool below; they are estimates, not a measurement of this setup.
Fixed page configuration
Qwen3.8-27B GGUF Q4-class on DGX Spark unified memory after the 16 GiB default reserve.
- ModelQwen3.8-27B VRAM
- HardwareNVIDIA DGX Spark (GB10, 128 GB unified)
- QuantizationGGUF UD-Q4_K_M (Unsloth)
- Context length (cached tokens)32,768
- Engine
llama.cpp - Concurrent sequences1
- KV cache typefp16
Technical identifiers and share data
- Model
qwen3.8-27b - Hardware
nvidia-dgx-spark-128gb-unified - Quantization
gguf-ud-q4_k_m - Share fragment for this identity
v2.eyJzY2hlbWFWZXJzaW9uIjoyLCJjYWxjdWxhdG9yVmVyc2lvbiI6IjAuMy4wIiwiZGF0YXNldFZlcnNpb24iOiIyMDI2LTEwLTAyLjEiLCJjb25maWciOnsibW9kZWxJZCI6InF3ZW4zLjgtMjdiIiwiaGFyZHdhcmVJZCI6Im52aWRpYS1kZ3gtc3BhcmstMTI4Z2ItdW5pZmllZCIsImRldmljZUNvdW50IjoxLCJxdWFudGl6YXRpb25JZCI6ImdndWYtdWQtcTRfa19tIiwiY29udGV4dFRva2VucyI6MzI3NjgsImNvbmN1cnJlbnRTZXF1ZW5jZXMiOjEsImVuZ2luZSI6ImxsYW1hLmNwcCIsImt2VHlwZSI6ImZwMTYifX0
Memory breakdown
- Weight artifact
- 15.33 GiB (16,464,440,224 bytes)
- Raw KV cache
- 2.00 GiB (2,147,483,648 bytes)
- Engine extras / workspace
- 0.27 GiB–3.87 GiB
- Total estimated demand
- 17.61 GiB–21.20 GiB
- Net calculator budget
- 112.00 GiB
- OS / display reserve
- 16.00 GiB
- Remaining vs net budget
- 90.80 GiB–94.39 GiB
21.20 GiB high estimate vs 112.00 GiB net
Enough memory does not mean this engine, quant, and OS will run. Support does not mean it will be fast.
Other published files on this device
Same model, device and context (32,768 tokens, 1 sequence, FP16 KV). Each row is one published weight-file set with its usual engine, sorted by memory.
Show all 28 published files
| Quantization | Engine | Estimated memory | Fit |
|---|---|---|---|
| BF16 safetensors | vllm | 54.52 GiB–64.93 GiB | Runs comfortably · Rough estimate |
| GGUF BF16 (Unsloth) | llama.cpp | 53.18 GiB–62.93 GiB | Runs comfortably · Rough estimate |
| GGUF UD-Q8_K_XL (Unsloth) | llama.cpp | 31.57 GiB–37.58 GiB | Runs comfortably · Rough estimate |
| GGUF Q8_0 (Unsloth) | llama.cpp | 29.33 GiB–34.95 GiB | Runs comfortably · Rough estimate |
| GGUF Q8_0 (mradermacher) | llama.cpp | 29.33 GiB–34.95 GiB | Runs comfortably · Rough estimate |
| GGUF UD-Q6_K_XL (Unsloth) | llama.cpp | 25.83 GiB–30.86 GiB | Runs comfortably · Rough estimate |
| GGUF Q6_K (mradermacher) | llama.cpp | 23.16 GiB–27.72 GiB | Runs comfortably · Rough estimate |
| GGUF UD-Q5_K_M (Unsloth) | llama.cpp | 20.69 GiB–24.82 GiB | Runs comfortably · Rough estimate |
| GGUF Q5_K_M (mradermacher) | llama.cpp | 20.47 GiB–24.56 GiB | Runs comfortably · Rough estimate |
| GGUF Q5_K_S (mradermacher) | llama.cpp | 19.94 GiB–23.94 GiB | Runs comfortably · Rough estimate |
| GGUF UD-Q4_K_XL (Unsloth) | llama.cpp | 18.63 GiB–22.40 GiB | Runs comfortably · Rough estimate |
| GGUF Q4_1 (Unsloth) | llama.cpp | 18.61 GiB–22.38 GiB | Runs comfortably · Rough estimate |
| GGUF Q4_K_M (mradermacher) | llama.cpp | 17.93 GiB–21.58 GiB | Runs comfortably · Rough estimate |
| GGUF UD-Q4_K_M (Unsloth) This page | llama.cpp | 17.61 GiB–21.20 GiB | Runs comfortably · Rough estimate |
| GGUF Q4_0 (Unsloth) | llama.cpp | 17.23 GiB–20.76 GiB | Runs comfortably · Rough estimate |
| GGUF Q4_K_S (mradermacher) | llama.cpp | 17.01 GiB–20.51 GiB | Runs comfortably · Rough estimate |
| GGUF IQ4_XS (mradermacher) | llama.cpp | 16.63 GiB–20.06 GiB | Runs comfortably · Rough estimate |
| GGUF Q3_K_L (mradermacher) | llama.cpp | 15.83 GiB–19.12 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ4_XS (Unsloth) | llama.cpp | 15.55 GiB–18.79 GiB | Runs comfortably · Rough estimate |
| GGUF Q3_K_M (mradermacher) | llama.cpp | 14.85 GiB–17.97 GiB | Runs comfortably · Rough estimate |
| GGUF Q3_K_S (mradermacher) | llama.cpp | 13.69 GiB–16.61 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ3_S (Unsloth) | llama.cpp | 13.49 GiB–16.37 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ3_XXS (Unsloth) | llama.cpp | 12.46 GiB–15.16 GiB | Runs comfortably · Rough estimate |
| GGUF Q2_K (mradermacher) | llama.cpp | 12.39 GiB–15.09 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ2_S (Unsloth) | llama.cpp | 10.07 GiB–12.36 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ2_XXS (Unsloth) | llama.cpp | 9.04 GiB–11.16 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ1_M (Unsloth) | llama.cpp | 8.54 GiB–10.57 GiB | Runs comfortably · Rough estimate |
| GGUF UD-IQ1_S (Unsloth) | llama.cpp | 8.04 GiB–9.98 GiB | Runs comfortably · Rough estimate |
Assumptions that affect this result
- Requested context is within the recorded native window of 262144 tokens.
- Full-resident weight estimates use total parameters, including inactive MoE experts.
- Weight bytes come from the selected weight files only, not from every file in the repository.
- Download file size is not peak GPU memory. Runtime layout, allocator padding, and KV are extra.
- Counted files: Qwen3.8-27B-UD-Q4_K_M.gguf.
- This checkpoint has a vision component. Text-only inference does not include vision encoder or projector bytes.
- Multi-token prediction / draft weights exist and are not included unless enabled.
- Context budget is the number of cached tokens per sequence (prompt plus reserved generation).
Related pages
Sources
- Qwen3.8-27B model card
- config.json — revision 1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0
- safetensors index — metadata.total_size=55562855904
- Artifact repo unsloth/Qwen3.8-27B-GGUF
- Artifact repo mradermacher/Qwen3.8-27B-GGUF
- NVIDIA DGX Spark product page — 128 GB LPDDR5x coherent unified system memory. This is not dedicated VRAM. Default reserve deducts OS and other processes. Multiple Sparks are not one pool.
- NVIDIA DGX Spark hardware docs — 128 GB LPDDR5x unified memory on the GB10 Superchip.
Calculator
This combo page keeps the route model and device. Customize to change them on the main calculator; the share then keeps that identity.
Loading catalog snapshot…
Search or pick a catalog checkpoint to see memory demand.