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Which GPUs and Macs run NVIDIA Nemotron 3.5 Bolt E4B?

Key facts

Yes. NVIDIA Nemotron 3.5 Bolt E4B needs about 7.3 GB of graphics memory, so it runs on every graphics card setup on this page, even the RTX 3060 12GB.

About 7.3 GB at Q4_K_M, our estimate. Checked . NVIDIA Q4_K_M GGUF (official).

The cheapest graphics card on our list that runs it (it still needs the rest of a PC): GeForce RTX 3060 12GB, $292€261, used (median of sold listings).

Fast~43 tok/sAnswers appear faster than you can read them.

Our price is for a used card. These shops mostly sell new ones, so their price can be higher.

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We never pass off an estimate as a benchmark. Commissions never change which hardware we recommend. How we calculate

The cheapest complete machine that runs it: Mac mini M4 16GB, about $615€549 (used). Comfortable~8.9 tok/s

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Which graphics cards run it

Seven popular graphics cards and two PCs with two cards each, at the standard quality (Q4). Click one for the full answer: memory, speed and price.

Runs well10

The whole model fits in the graphics memory.

Every model on every card

Which Macs and mini PCs run it

Macs and mini PCs from the picker, at the standard quality (Q4). A Mac shares its memory with the rest of the computer. Each name opens that machine's page.

Runs well12

The whole model fits in the memory the graphics can use.

Cheapest hardware for each size

From all 43 graphics cards, PCs and Macs on our list. "Runs slowly" means part of the model runs from normal memory: cheaper, but much slower. A smaller download needs less memory and answers a little less well.

  • Standard quality (Q4_K_M)GeForce RTX 3060 12GB, $292€261, used (median of sold listings)
  • Standard quality (Q4_K_M), runs slowlyNo machine on our list runs this size.
  • Smallest download (UD-IQ2_M)GeForce RTX 3060 12GB, $292€261, used (median of sold listings)
  • Smallest download (UD-IQ2_M), runs slowlyNo machine on our list runs this size.

Prices excl. shipping unless marked. Euro prices incl. VAT where the seller charges it. Dollar prices are converted from our euro prices without the 21% EU VAT, before US sales tax.

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

About NVIDIA Nemotron 3.5 Bolt E4B

8B parameters. Parameter count is an estimate. More parameters usually means a smarter model that needs more memory.

Licence:
OpenMDW-1.1 source
Longest conversation:
about 98 pages of text (65,536 tokens)
Input:
text
Released:
source
Sources and method

NVIDIA's small Nemotron 3.5: 8B parameters. The card calls 4B of that effective, from per-layer embeddings, not a mixture of experts. Open weights under OpenMDW-1.1; the Gemma 4 base is Apache 2.0. The card says text in and text out, and context up to 64K (65,536). The GGUF header and Ollama list 128K. The config, Ollama and the unsloth GGUFs also include an image encoder; the mmproj files (0.56–0.99 GB) are not in these totals. Ollama's :e4b download was 7.91 GB on 23 Oct 2026 (the 6.18 GB Q4_K_M plus a projector and a draft). Without :e4b, Ollama pulls the 74B model. 18 of 42 layers share key and value state, which this estimate does not model, so the conversation figure is conservative.

Builder interview

Fabio Matricardi (@fabiomatricardi) runs NVIDIA-Nemotron-3.5-Bolt-E4B-UD-Q5_K_XL.gguf in llama.cpp Vulkan on a Lenovo ThinkPad with an AMD Radeon 780M iGPU (32 GB unified RAM) and on a Dell i5 workplace laptop with an Intel Ultra iGPU (32 GB unified RAM). For opencode agent-harness runs he stays at Q6, with Q5_K_M as an occasional exception, so structured output and tool calls do not drift. Self-reported, 25 October 2026. Read Fabio Matricardi's interview.

Ran NVIDIA Nemotron 3.5 Bolt E4B on your own hardware? Send us your llama-bench result.

Parameter source · Architecture source · Model page

Memory at each quality level

Each download of NVIDIA Nemotron 3.5 Bolt E4B is a different size. The total adds the file, the memory a conversation of about 12 pages of text (8,192 tokens) takes, and 0.8 GB of working space. A measured file size is labelled; the rest is our estimate. The last column is the cheapest machine that holds the total.

Swipe the table sideways to see every column, up to the cheapest machine.

Memory per quant for NVIDIA Nemotron 3.5 Bolt E4B
Quality (file)File sizeConversationWorking spaceTotalCheapest machine that holds it
BF1615.05 GBmeasured GGUF0.3 GB0.8 GB16.1 GBGeForce RTX 3090 24GB, $1,395€1,246, used (median of sold listings)
UD-Q8_K_XL8.19 GBmeasured GGUF0.3 GB0.8 GB9.3 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
Q8_08.03 GBmeasured GGUF0.3 GB0.8 GB9.1 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
UD-Q6_K_XL7.26 GBmeasured GGUF0.3 GB0.8 GB8.3 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
Q4_K_M6.18 GBmeasured GGUF0.3 GB0.8 GB7.3 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
UD-Q5_K_XL5.83 GBmeasured GGUF0.3 GB0.8 GB6.9 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
UD-Q4_K_XL5.06 GBmeasured GGUF0.3 GB0.8 GB6.1 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
UD-Q3_K_XL4.22 GBmeasured GGUF0.3 GB0.8 GB5.3 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)
MLX-4bitMLX: Apple Silicon only4.20 GBmeasured MLX0.3 GB0.8 GB5.3 GBMac mini M4 16GB, $615€549 (used), price unverified
UD-IQ2_M3.53 GBmeasured GGUF0.3 GB0.8 GB4.6 GBGeForce RTX 3060 12GB, $292€261, used (median of sold listings)

Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate

Questions

Can I run NVIDIA Nemotron 3.5 Bolt E4B on an 8GB or 12GB GPU?
Yes, by our estimate. At Q4_K_M (6.18 GB measured GGUF + 0.27 GB conversation memory at 8,192 tokens + 0.80 GB working space = 7.25 GB / 7.3 GB total estimate), it fits a 12 GB GPU (11.4 GB usable; cheapest on our list: GeForce RTX 3060 12GB at €261 / $292, about 43 tok/s estimate) and just fits the 7.4 GB an 8 GB card would leave usable under the same 0.6 GB reserve (this list has no 8 GB card). For more headroom on 8 GB, UD-Q5_K_XL (5.83 GB measured GGUF, 6.9 GB total estimate) or UD-Q4_K_XL (5.06 GB measured GGUF, 6.1 GB total estimate) or UD-Q3_K_XL (4.22 GB measured GGUF, 5.3 GB total estimate) or UD-IQ2_M (3.53 GB measured GGUF, 4.6 GB total estimate). The model notes put the mmproj image files at 0.56–0.99 GB, and those files are not included in these totals.
Can I run NVIDIA Nemotron 3.5 Bolt E4B on 24GB?
Yes, by our estimate. At Q4_K_M (6.18 GB measured GGUF + 0.27 GB conversation memory at 8,192 tokens + 0.80 GB working space = 7.25 GB / 7.3 GB total estimate), NVIDIA Nemotron 3.5 Bolt E4B fits inside the 23.4 GB usable memory of a 24 GB card. The cheapest 24 GB card on our list is GeForce RTX 3090 24GB at €1,246 / $1,395. A 24 GB card also holds BF16 (15.05 GB measured GGUF, 16.1 GB total estimate) and UD-Q8_K_XL (8.19 GB measured GGUF, 9.3 GB total estimate) and Q8_0 (8.03 GB measured GGUF, 9.1 GB total estimate) and UD-Q6_K_XL (7.26 GB measured GGUF, 8.3 GB total estimate).
Can I run NVIDIA Nemotron 3.5 Bolt E4B on a 16GB or 128GB Mac?
Yes, by our estimate. It fits on Mac mini M4 16GB (10.7 GB usable of 16 GB, €549 / $615, price unverified, about 8.9 tok/s estimate at Q4_K_M). MLX-4bit (4.2 GB measured MLX, 5.3 GB total estimate) is the Apple Silicon build. It also fits Mac Studio M4 Max 128GB and Mac Studio M5 Max 128GB (96.0 GB usable of 128 GB).
How fast is NVIDIA Nemotron 3.5 Bolt E4B on an RTX 5090, RTX 4090, and RTX 3090?
Our hardware-spec estimates at Q4 are about 208 tok/s on an RTX 5090, about 119 tok/s on an RTX 4090, about 111 tok/s on an RTX 3090, about 109 tok/s on an RX 7900 XTX, about 43 tok/s on an RTX 3060 12GB (estimates, not measured benchmark runs).
Why does Ollama download 7.91 GB or pull a 74B model for Nemotron 3.5 Bolt?
Include the :e4b tag (ollama run nemotron-3.5-bolt:e4b). Without :e4b, Ollama pulls the larger model (NVIDIA Nemotron 3.5 Bolt 74B-A9B, https://localllmrig.com/can-i-run/nemotron-3-5-bolt-74b). The model notes record that :e4b download as 7.91 GB, bundling the 6.18 GB Q4_K_M weights with a projector and a draft model.
Can I test Nemotron 3.5 models live in my browser before downloading?
Yes. At https://localllmrig.com/ and in the inline test box on https://localllmrig.com/can-i-run/nemotron-3-5-bolt-e4b, you can test 10 open models for free with no account, including NVIDIA Nemotron 3.5 Lightning (https://localllmrig.com/can-i-run/nemotron-3.5-lightning), Nemotron 3 Nano Omni, NVIDIA Nemotron 3.5 Super VL (https://localllmrig.com/can-i-run/nemotron-3.5-super-vl).
Can I try NVIDIA Nemotron 3.5 Bolt E4B online for free?
Yes. NVIDIA Nemotron 3.5 Bolt E4B is on the free chat on the home page. Pick it there, ask a question, and read the answer in your browser. No login and no install.
Do I need a GPU to test it?
No. The free chat runs in your browser. It does not download the model and it does not use a graphics card on your computer. A graphics card only matters if you run the model yourself.
Do I need an account to try NVIDIA Nemotron 3.5 Bolt E4B?
No. The free chat needs no account and no login.