Mistral-Nemo-Instruct-2407 on RTX 3060: Fits (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 (Unsloth), 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 3060 12GB (desktop)

Yes, run Q4_K_M. The calculator puts it at 8.3 GiB–8.9 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 (13.5 GiB–14.2 GiB).

With Q4_K_M, the longest context that still counts as a fit is about 14,069 tokens of a 131,072-token native window, one sequence, fp16 KV cache.

Published GGUF quants for Mistral-Nemo-Instruct-2407 on GeForce RTX 3060 12GB (desktop) at 8,192 tokens
GGUF quantFile weightsKV cacheEstimated totalVerdict
Q8_012.1 GiB1.3 GiB13.5 GiB–14.2 GiBDoes not fit
Q6_K9.4 GiB1.3 GiB10.7 GiB–11.4 GiBTight
Q5_K_M8.1 GiB1.3 GiB9.5 GiB–10.1 GiBTight
Q4_K_M (recommended)7.0 GiB1.3 GiB8.3 GiB–8.9 GiBFits

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

GGUF Q4_K_M needs 8.3 GiB-8.9 GiB at 8,192 tokens against 11.00 GiB net on GeForce RTX 3060 12GB (desktop). Q8_0, Q6_K, Q5_K_M are tight or over budget.

Technical identifiers and share data
  • Modelmistral-nemo-instruct-2407
  • Hardwarenvidia-geforce-rtx-3060-12gb-desktop
  • Quantizationgguf-q4_k_m
  • Share fragment for this identityv2.eyJzY2hlbWFWZXJzaW9uIjoyLCJjYWxjdWxhdG9yVmVyc2lvbiI6IjAuMy4wIiwiZGF0YXNldFZlcnNpb24iOiIyMDI2LTEwLTAyLjEiLCJjb25maWciOnsibW9kZWxJZCI6Im1pc3RyYWwtbmVtby1pbnN0cnVjdC0yNDA3IiwiaGFyZHdhcmVJZCI6Im52aWRpYS1nZWZvcmNlLXJ0eC0zMDYwLTEyZ2ItZGVza3RvcCIsImRldmljZUNvdW50IjoxLCJxdWFudGl6YXRpb25JZCI6ImdndWYtcTRfa19tIiwiY29udGV4dFRva2VucyI6ODE5MiwiY29uY3VycmVudFNlcXVlbmNlcyI6MSwiZW5naW5lIjoibGxhbWEuY3BwIiwia3ZUeXBlIjoiZnAxNiJ9fQ

Memory breakdown

Weight artifact
6.96 GiB (7,477,204,512 bytes)
Raw KV cache
1.25 GiB (1,342,177,280 bytes)
Engine extras / workspace
0.13 GiB–0.73 GiB
Total estimated demand
8.34 GiB–8.94 GiB
Net calculator budget
11.00 GiB
OS / display reserve
1.00 GiB
Remaining vs net budget
2.06 GiB–2.66 GiB

8.94 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 safetensorsvllm24.69 GiB–26.60 GiBDoes not fit
GGUF Q8_0 (Unsloth)llama.cpp13.50 GiB–14.21 GiBDoes not fit
GGUF Q6_K (Unsloth)llama.cpp10.74 GiB–11.39 GiBTight fit
GGUF Q5_K_M (Unsloth)llama.cpp9.50 GiB–10.13 GiBTight fit
GGUF Q4_K_M (Unsloth) This pagellama.cpp8.34 GiB–8.94 GiBFits

Assumptions that affect this result

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