Can I run NVIDIA Nemotron 3.5 Bolt E4B on an RX 7900 XTX?
Key facts
Yes. NVIDIA Nemotron 3.5 Bolt E4B runs on an RX 7900 XTX, about 109 tokens per second (tok/s).
It needs about 7.3 GB at standard quality (estimate). Checked . NVIDIA Q4_K_M GGUF (official).
How much memory it needs
It uses about 31% 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 RX 7900 XTX costs
Radeon RX 7900 XTX 24GB$1,404€1,254used (3-month median)
EU shops · Shown to visitors in Europe.US shops · Shown to visitors outside Europe.
We never pass off an estimate as a benchmark. Commissions never change which hardware we recommend. How we calculate
Price details
$1,404€1,254
How we priced this
Used price, the typical price over the last three months.
Source: GPU PRIX, checked 17 Oct 2026.
New in stock, €3,972 at GPU PRIX on 17 Oct 2026 (unusually high). Source: GPU PRIX, 17 Oct 2026. More than 1.5 times the typical price of €1,254, so we do not use it as the main price.
€1,254 is the typical price over the past 3 months on GPU PRIX, checked 17 Oct 2026. The only board in stock (an ASUS TUF Gaming at €3,972) cost more than 1.5 times that, and cheaper boards, such as an XFX Speedster at €1,049, were 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~109 tok/s | 6.2 GBmeasured file | 0.3 GB | 0.8 GB | 7.3 GB | 23.4 GB |
| Q5 · a bit sharper, a bit bigger | ~12 pages8,192 tokens | Runs | Fast~93 tok/s | 7.3 GB | 0.3 GB | 0.8 GB | 8.4 GB | 23.4 GB |
| Q8 · near full quality, almost twice Q4 | ~12 pages8,192 tokens | Runs | Fast~80 tok/s | 8.6 GB | 0.3 GB | 0.8 GB | 9.6 GB | 23.4 GB |
| FP16 · full quality, over three times Q4 | ~12 pages8,192 tokens | Runs | Fast~44 tok/s | 16.0 GB | 0.3 GB | 0.8 GB | 17.1 GB | 23.4 GB |
| Q4 · standard, longer conversation | ~49 pages32,768 tokens | Runs | Fast~99 tok/s | 6.2 GBmeasured file | 1.0 GB | 0.8 GB | 8.0 GB | 23.4 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 RX 7900 XTX yourself? Send us your llama-bench result.
Questions
- Can I run NVIDIA Nemotron 3.5 Bolt E4B on an RX 7900 XTX?
- Yes. NVIDIA Nemotron 3.5 Bolt E4B runs on an RX 7900 XTX, about 109 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 RX 7900 XTX?
- Fast: about 109 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