Does not fit: Qwen3.8-27B needs 19.36 GiB on RTX 5080 (Rough estimate)

Does not fit. Needs 16.11 GiB–19.36 GiB on RTX 5080 (16 GB GDDR7) against 14.00 GiB net. GGUF UD-Q4_K_M (Unsloth), 8,192 tokens. Rough estimate

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), 8,192 cached tokens, 1 sequence, engine llama.cpp. Status: Insufficient memory. Software: Not verified..

A published GGUF UD-IQ2_S (Unsloth) file fits instead: estimated 8.57 GiB–10.52 GiB against the same 14.00 GiB net budget.

Insufficient memoryNot verifiedThis result is an estimate, not a measured trace.

Verdict on GeForce RTX 5080 16GB (desktop)

No. The smallest published GGUF (Q4_K_M) needs 16.4 GiB–19.7 GiB against 14.0 GiB of usable VRAM (after the driver reserve). It would only run by spilling layers to system RAM, which this site does not model.

Published GGUF quants for Qwen3.8-27B on GeForce RTX 5080 16GB (desktop) at 8,192 tokens
GGUF quantFile weightsKV cacheEstimated totalVerdict
Q8_027.1 GiB0.5 GiB27.8 GiB–33.1 GiBDoes not fit
Q6_K20.9 GiB0.5 GiB21.7 GiB–25.9 GiBDoes not fit
Q5_K_M18.2 GiB0.5 GiB19.0 GiB–22.7 GiBDoes not fit
Q4_K_M15.7 GiB0.5 GiB16.4 GiB–19.7 GiBDoes not fit

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 UD-Q4_K_M on the catalog RTX 5080 16 GB SKU. Same published quant as the 4090 allowlisted combo. The calculator verdict at 8,192 tokens is does-not-fit. This page is not a measurement.

Technical identifiers and share data
  • Modelqwen3.8-27b
  • Hardwarenvidia-geforce-rtx-5080-16gb-desktop
  • Quantizationgguf-ud-q4_k_m
  • Share fragment for this identityv2.eyJzY2hlbWFWZXJzaW9uIjoyLCJjYWxjdWxhdG9yVmVyc2lvbiI6IjAuMy4wIiwiZGF0YXNldFZlcnNpb24iOiIyMDI2LTEwLTAyLjEiLCJjb25maWciOnsibW9kZWxJZCI6InF3ZW4zLjgtMjdiIiwiaGFyZHdhcmVJZCI6Im52aWRpYS1nZWZvcmNlLXJ0eC01MDgwLTE2Z2ItZGVza3RvcCIsImRldmljZUNvdW50IjoxLCJxdWFudGl6YXRpb25JZCI6ImdndWYtdWQtcTRfa19tIiwiY29udGV4dFRva2VucyI6ODE5MiwiY29uY3VycmVudFNlcXVlbmNlcyI6MSwiZW5naW5lIjoibGxhbWEuY3BwIiwia3ZUeXBlIjoiZnAxNiJ9fQ

Memory breakdown

Weight artifact
15.33 GiB (16,464,440,224 bytes)
Raw KV cache
0.50 GiB (536,870,912 bytes)
Engine extras / workspace
0.27 GiB–3.53 GiB
Total estimated demand
16.11 GiB–19.36 GiB
Net calculator budget
14.00 GiB
OS / display reserve
2.00 GiB
Remaining vs net budget
-5.36 GiB–-2.11 GiB

19.36 GiB high estimate vs 14.00 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 (8,192 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
QuantizationEngineEstimated memoryFit
BF16 safetensorsvllm53.02 GiB–63.15 GiBDoes not fit · Rough estimate
GGUF BF16 (Unsloth)llama.cpp51.68 GiB–61.08 GiBDoes not fit · Rough estimate
GGUF UD-Q8_K_XL (Unsloth)llama.cpp30.07 GiB–35.74 GiBDoes not fit · Rough estimate
GGUF Q8_0 (Unsloth)llama.cpp27.83 GiB–33.10 GiBDoes not fit · Rough estimate
GGUF Q8_0 (mradermacher)llama.cpp27.83 GiB–33.10 GiBDoes not fit · Rough estimate
GGUF UD-Q6_K_XL (Unsloth)llama.cpp24.33 GiB–29.01 GiBDoes not fit · Rough estimate
GGUF Q6_K (mradermacher)llama.cpp21.66 GiB–25.88 GiBDoes not fit · Rough estimate
GGUF UD-Q5_K_M (Unsloth)llama.cpp19.19 GiB–22.97 GiBDoes not fit · Rough estimate
GGUF Q5_K_M (mradermacher)llama.cpp18.97 GiB–22.71 GiBDoes not fit · Rough estimate
GGUF Q5_K_S (mradermacher)llama.cpp18.44 GiB–22.10 GiBDoes not fit · Rough estimate
GGUF UD-Q4_K_XL (Unsloth)llama.cpp17.13 GiB–20.55 GiBDoes not fit · Rough estimate
GGUF Q4_1 (Unsloth)llama.cpp17.11 GiB–20.53 GiBDoes not fit · Rough estimate
GGUF Q4_K_M (mradermacher)llama.cpp16.43 GiB–19.74 GiBDoes not fit · Rough estimate
GGUF UD-Q4_K_M (Unsloth) This pagellama.cpp16.11 GiB–19.36 GiBDoes not fit · Rough estimate
GGUF Q4_0 (Unsloth)llama.cpp15.73 GiB–18.91 GiBDoes not fit · Rough estimate
GGUF Q4_K_S (mradermacher)llama.cpp15.51 GiB–18.66 GiBDoes not fit · Rough estimate
GGUF IQ4_XS (mradermacher)llama.cpp15.13 GiB–18.22 GiBDoes not fit · Rough estimate
GGUF Q3_K_L (mradermacher)llama.cpp14.33 GiB–17.28 GiBDoes not fit · Rough estimate
GGUF UD-IQ4_XS (Unsloth)llama.cpp14.05 GiB–16.94 GiBDoes not fit · Rough estimate
GGUF Q3_K_M (mradermacher)llama.cpp13.35 GiB–16.12 GiBTight fit · Rough estimate
GGUF Q3_K_S (mradermacher)llama.cpp12.19 GiB–14.76 GiBTight fit · Rough estimate
GGUF UD-IQ3_S (Unsloth)llama.cpp11.99 GiB–14.53 GiBTight fit · Rough estimate
GGUF UD-IQ3_XXS (Unsloth)llama.cpp10.96 GiB–13.32 GiBTight fit · Rough estimate
GGUF Q2_K (mradermacher)llama.cpp10.89 GiB–13.24 GiBTight fit · Rough estimate
GGUF UD-IQ2_S (Unsloth)llama.cpp8.57 GiB–10.52 GiBFits · Rough estimate
GGUF UD-IQ2_XXS (Unsloth)llama.cpp7.54 GiB–9.31 GiBRuns comfortably · Rough estimate
GGUF UD-IQ1_M (Unsloth)llama.cpp7.04 GiB–8.72 GiBRuns comfortably · Rough estimate
GGUF UD-IQ1_S (Unsloth)llama.cpp6.54 GiB–8.14 GiBRuns comfortably · Rough estimate

Assumptions that affect this result

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Quantization

Device type

Workload

Context length primarily affects KV cache memory.

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Runtime

Engine and KV cache type for this estimate.

Workload

Overhead scenario and the prefill workspace.

Topology

How the model is split across devices. Memory is not added together.

Replica count is an advanced deployment option. Quantity is nodes or GPUs, not replicas.

Budget

System reserve and safety margin. An empty number keeps the previous value.

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