Can I run NVIDIA Nemotron 3.5 Bolt E4B on an RTX 5090?
Key facts
Yes. NVIDIA Nemotron 3.5 Bolt E4B runs on an RTX 5090, about 208 tokens per second (tok/s).
It needs about 7.3 GB at standard quality (estimate). Checked . NVIDIA Q4_K_M GGUF (official).
The cheapest graphics card on our list that holds it at Q4 is the GeForce RTX 3060 12GB. On an RTX 5090, at 32,768 tokens of context, it still fits in graphics memory (estimate).
How much memory it needs
It uses about 23% of the memory that is free on this card.
Get a 1-line alert when a faster quant for NVIDIA Nemotron 3.5 Bolt E4B drops — or when GPUs that run it drop >10%
Get a 1-line alert when a new open-weight model fits 8 GB VRAM (7.3 GB at Q4 for NVIDIA Nemotron 3.5 Bolt E4B) or when used RTX 3090 / 4090 & Mac Studio prices drop >10% — weekly, zero spam.
What an RTX 5090 costs
GeForce RTX 5090 32GB$6,816€7,367new (lowest in-stock EU)
EU shops · Shown to visitors in Europe.US shops · Shown to visitors outside Europe.
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Price details
$6,816€7,367
How we priced this
New price, the lowest in stock in the EU.
Source: PriceSquirrel, checked 21 Oct 2026.
Cheapest in-stock listing on 21 Oct 2026: €7,367 for an INNO3D iChill Frostbite (water-cooled) at Alternate (Germany), found via PriceSquirrel. A cheaper €7,080 listing, an MSI Ventus 3X OC at Compumsa in Belgium, was out of stock.
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.
The cheapest graphics card on our list that also runs it (it still needs the rest of a PC): GeForce RTX 3060 12GB, $292€261, used (median of sold listings). Fast~43 tok/s
The cheapest complete machine that runs it: Mac mini M4 16GB, about $615€549 (used). Comfortable~8.9 tok/s
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NVIDIA Nemotron 3.5 Bolt E4B on other graphics cards
Runs well10
The whole model fits in the graphics memory.
More about the model itself, what it is good at and its licence: NVIDIA Nemotron 3.5 Bolt E4B.
The numbers behind this answer
A model comes in several sizes. Q4 is the standard one most people use; the bigger ones answer a little better but need more memory. Each row adds up the model file, the memory a conversation takes, and some working space, and compares the total with what is free on this card.
Swipe the table sideways to see every column.
| Quality | Conversation | Result | Speed | Model file | Conversation memory | Working space | Total needed | Free memory |
|---|---|---|---|---|---|---|---|---|
| Q4 · standard (smallest that keeps quality) | ~12 pages8,192 tokens | Runs | Fast~208 tok/s | 6.2 GBmeasured file | 0.3 GB | 0.8 GB | 7.3 GB | 31.4 GB |
| Q5 · a bit sharper, a bit bigger | ~12 pages8,192 tokens | Runs | Fast~178 tok/s | 7.3 GB | 0.3 GB | 0.8 GB | 8.4 GB | 31.4 GB |
| Q8 · near full quality, almost twice Q4 | ~12 pages8,192 tokens | Runs | Fast~153 tok/s | 8.6 GB | 0.3 GB | 0.8 GB | 9.6 GB | 31.4 GB |
| FP16 · full quality, over three times Q4 | ~12 pages8,192 tokens | Runs | Fast~84 tok/s | 16.0 GB | 0.3 GB | 0.8 GB | 17.1 GB | 31.4 GB |
| Q4 · standard, longer conversation | ~49 pages32,768 tokens | Runs | Fast~188 tok/s | 6.2 GBmeasured file | 1.0 GB | 0.8 GB | 8.0 GB | 31.4 GB |
Sources and method
Memory and speed on this page are our estimate, not a measured test. Checked . NVIDIA Q4_K_M GGUF (official).
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.
Some downloads of this model (MLX) only run on Apple Silicon Macs, not on a graphics card.
Measured NVIDIA Nemotron 3.5 Bolt E4B on an RTX 5090 yourself? Send us your llama-bench result.
Questions
- Can I run NVIDIA Nemotron 3.5 Bolt E4B on an RTX 5090?
- Yes. NVIDIA Nemotron 3.5 Bolt E4B runs on an RTX 5090, about 208 tokens per second (tok/s).
- How much memory does NVIDIA Nemotron 3.5 Bolt E4B need?
- About 7.3 GB at the standard quality (Q4) for a conversation of up to about 12 pages of text (8,192 tokens), by our estimate: 6.2 GB for the model file (measured), 0.3 GB to hold the conversation and 0.8 GB of working space.
- How fast is NVIDIA Nemotron 3.5 Bolt E4B on an RTX 5090?
- Fast: about 208 tokens per second (tok/s). Answers appear faster than you can read them. This is our estimate, not a measured test.
Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate