Qwen3-8B-Base on RTX 4070: Runs comfortably (Sep 2026)

Conditional memory judgement for one configuration. Change context, quant, or engine and the conclusion can change. Configuration used on this page: GGUF Q4_K_M (mradermacher), 8,192 cached tokens, 1 sequence, engine llama.cpp. Status: Likely fits. Software: Not verified..

Likely fitsNot verifiedThis result is an estimate, not a measured trace.

Verdict on GeForce RTX 4070 12GB (desktop, GDDR6X)

Yes, run Q6_K. The calculator puts it at 7.5 GiB–8.1 GiB at 8,192 tokens, inside 11.0 GiB of usable VRAM (after the driver reserve). Q8_0 is the next step up and does not clear the bar (9.4 GiB–10.0 GiB).

With Q6_K, the longest context that still counts as a fit is about 20,489 tokens of a 32,768-token native window, one sequence, fp16 KV cache.

Published GGUF quants for Qwen3-8B-Base on GeForce RTX 4070 12GB (desktop, GDDR6X) at 8,192 tokens
GGUF quantFile weightsKV cacheEstimated totalVerdict
Q8_08.1 GiB1.1 GiB9.4 GiB–10.0 GiBTight
Q6_K (recommended)6.3 GiB1.1 GiB7.5 GiB–8.1 GiBFits
Q5_K_M5.4 GiB1.1 GiB6.7 GiB–7.3 GiBComfortable
Q4_K_M4.7 GiB1.1 GiB5.9 GiB–6.5 GiBComfortable

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

Qwen3-8B-Base GGUF Q4_K_M on the catalog RTX 4070 12 GB SKU, matching the instruct sibling's allowlisted setup.

Technical identifiers and share data
  • Modelqwen3-8b-base
  • Hardwarenvidia-geforce-rtx-4070-12gb-desktop
  • Quantizationgguf-q4_k_m
  • Share fragment for this identityv2.eyJzY2hlbWFWZXJzaW9uIjoyLCJjYWxjdWxhdG9yVmVyc2lvbiI6IjAuMy4wIiwiZGF0YXNldFZlcnNpb24iOiIyMDI2LTEwLTAyLjEiLCJjb25maWciOnsibW9kZWxJZCI6InF3ZW4zLThiLWJhc2UiLCJoYXJkd2FyZUlkIjoibnZpZGlhLWdlZm9yY2UtcnR4LTQwNzAtMTJnYi1kZXNrdG9wIiwiZGV2aWNlQ291bnQiOjEsInF1YW50aXphdGlvbklkIjoiZ2d1Zi1xNF9rX20iLCJjb250ZXh0VG9rZW5zIjo4MTkyLCJjb25jdXJyZW50U2VxdWVuY2VzIjoxLCJlbmdpbmUiOiJsbGFtYS5jcHAiLCJrdlR5cGUiOiJmcDE2In19

Memory breakdown

Weight artifact
4.68 GiB (5,027,783,936 bytes)
Raw KV cache
1.13 GiB (1,207,959,552 bytes)
Engine extras / workspace
0.13 GiB–0.67 GiB
Total estimated demand
5.93 GiB–6.48 GiB
Net calculator budget
11.00 GiB
OS / display reserve
1.00 GiB
Remaining vs net budget
4.52 GiB–5.07 GiB

6.48 GiB high estimate vs 11.00 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.

QuantizationEngineEstimated memoryFit
BF16 safetensorsvllm17.01 GiB–18.92 GiBDoes not fit
GGUF Q8_0 (mradermacher)llama.cpp9.36 GiB–9.98 GiBTight fit
GGUF Q6_K (mradermacher)llama.cpp7.51 GiB–8.09 GiBFits
GGUF Q5_K_M (mradermacher)llama.cpp6.70 GiB–7.26 GiBRuns comfortably
GGUF Q4_K_M (mradermacher) This pagellama.cpp5.93 GiB–6.48 GiBRuns comfortably

Assumptions that affect this result

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