Spark-X2.6-4B: VRAM requirements by quant
Key facts
Spark-X2.6-4B needs about 3.8 GB at standard quality (Q4, estimate).
Checked . bartowski Q4_K_M GGUF.
Spark-X2.6-4B is a small, fast AI model you can download and run on your own computer. It needs about 3.8 GB of memory at standard quality.
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Memory needed
About 3.8 GB
At standard quality, with room for a conversation of about 12 pages.
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Machines that run Spark-X2.6-4B
Each of these holds the whole model in memory. Speed is in tokens per second (tok/s); from about 8 it keeps up with your reading.
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Mac mini M4 16GB
16 GB shared memory · second-hand
Comfortable~19.3 tok/s$615€549usedunverified
Machine details →Mac mini M6 16GB
16 GB shared memory
Fast~25 tok/s$989€1,069new
Machine details →Used PC with RTX 3090 24GB
24 GB graphics memory · second-hand
Fast~234 tok/s$2,413€2,346estimateused parts
Machine details →The buttons look up the graphics card, the part of this PC worth comparing.
PC with Radeon RX 7900 XTX 24GB
24 GB graphics memory · second-hand
Fast~231 tok/s$2,422€2,354estimateused parts
Machine details →The buttons look up the graphics card, the part of this PC worth comparing.
PC with RTX 5090 32GB
32 GB graphics memory
Fast~429 tok/s$7,834€8,467estimate
Machine details →The buttons look up the graphics card, the part of this PC worth comparing.
Where our price is for a used card or Mac, these shops mostly sell new ones, so their price can be higher.
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About these prices
Each price is the amount we last wrote down for that machine, with its date on the machine page. "Estimate" is our own figure: for a complete PC we add our estimate for the other parts to the graphics card price, and some Mac prices are estimates, not a checked shop listing. "Used" is a second-hand price. "Unverified" means we have no checked shop listing for that exact amount. The shop buttons open a search for that machine at each shop, so you see today's price there. 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.
Or rent one by the hour: RTX A6000 at Vast.ai holds it, for $0.40 an hour (median of live offers, 21 Oct 2026). Compare GPU cloud prices
Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate
Memory at each quality level
A lower quality level makes the model smaller, so it fits on a smaller machine. Standard (Q4) is what most people run.
| Quality | Memory needed |
|---|---|
| Q4 · standard (smallest that keeps quality) | 3.8 GB |
| Q5 · a bit sharper, a bit bigger | 4.1 GB |
| Q8 · near full quality, almost twice Q4 | 5.6 GB |
| FP16 · full quality, over three times Q4 | 9.4 GB |
With a conversation of 8,192 tokens · about 12 pages of text.
Sources and method
At standard quality: 2.6 GB for the model itself (a measured file), 0.4 GB for a conversation of 8,192 tokens, and 0.8 GB for the software.
Size source: huggingface.co/XHToken/Spark-X2.6-4B/raw/main/model.safetensors.index.json. The published size is rounded, so ours is an estimate.
Dense text model, 4.11B parameters. Hugging Face safetensors metadata lists 4,112,079,360 parameters, all BF16. 4.11B is that count to two decimals, so our parameter count is an estimate. Architecture Spark2_5ForCausalLM (model type spark2_5): 36 layers, 27 sliding-window layers with a 512-token window and 9 full-attention layers, 4 KV heads, head dim 256, max context 1,048,576. At 8,192 tokens our estimate adds 0.36 GB of conversation memory across that 1,048,576-token max context, plus 0.80 GB of working space. Bartowski's Q4_K_M measured 2.62 GB on 27 Oct 2026 (2,621,104,768 bytes), so the total at 8,192 tokens is 3.78 GB. XHToken's official Q4_K_M measured 3.54 GB on the same day (3,543,441,312 bytes), so that file's total at 8,192 tokens is 4.70 GB. The bartowski file is the one this page uses for the standard total. Apache-2.0. Other runtimes (not llama.cpp). Spark2_5ForCausalLM (spark2_5) runs out of the box via GGUF in llama.cpp, Ollama and LM Studio. Stock vLLM and Transformers releases need custom model registration.
Licence
Commercial use: yes
Commercial use allowed. Keep the licence and copyright notice when you share the weights.
Licence: Apache-2.0 · checked 27 Oct 2026
Our reading of the licence, not legal advice.
Will Spark-X2.6-4B run on my graphics card?
Common questions
- How much memory does Spark-X2.6-4B need?
- About 3.8 GB at standard quality (Q4) with a conversation of 8,192 tokens: 2.6 GB for the model itself, 0.4 GB for the conversation and 0.8 GB for the software. The model size is a measured file; the conversation and software parts are our estimate.
- Does Spark-X2.6-4B fit on a single 24 GB graphics card?
- Yes, by our estimate. It needs about 3.8 GB, and we count 23.4 GB of a 24 GB card as usable.
- Are the speeds measured?
- No. They are our estimate from how fast each machine's memory is. Real speed also depends on the software and its settings.
- How much memory does Spark-X2.6-4B need at Q4_K_M, Q8_0 and BF16?
- At Q4_K_M (2.62 GB measured GGUF + 0.36 GB conversation memory at 8,192 tokens + 0.80 GB working space = 3.78 GB / 3.8 GB total estimate). At Q8_0 (4.38 GB measured GGUF + 0.36 GB conversation memory at 8,192 tokens + 0.80 GB working space = 5.54 GB / 5.5 GB total estimate). At BF16 (8.23 GB measured GGUF + 0.36 GB conversation memory at 8,192 tokens + 0.80 GB working space = 9.39 GB / 9.4 GB total estimate). XHToken's official Q4_K_M is 3.54 GB measured. With the same conversation memory and working space that file is 4.70 GB at 8,192 tokens. The bartowski Q4_K_M is the file this page uses for the standard total.
- Why is Spark-X2.6-4B's conversation memory only 0.36 GB at 8,192 tokens across a 1,048,576-token max context?
- Spark-X2.6-4B uses Spark2_5ForCausalLM hybrid attention: 27 sliding-window layers with a 512-token window and 9 full-attention layers. At 8,192 tokens that is 0.36 GB of conversation memory. At the full 1,048,576-token context it is 38.71 GB. The sliding layers keep only 512 tokens each, so the long context does not store a full conversation for every layer.
- Does Spark2_5ForCausalLM run in llama.cpp, Ollama, LM Studio, vLLM or Transformers?
- Spark2_5ForCausalLM (spark2_5) runs out of the box via GGUF in llama.cpp, Ollama and LM Studio. Stock vLLM and Transformers releases need custom model registration. The measured files are on https://localllmrig.com/can-i-run/spark-x2.6-4b.
- Where can I test open models in the browser before downloading Spark-X2.6-4B?
- Spark-X2.6-4B is not one of the 10 free models. You can test those open models in the browser at https://localllmrig.com/ with no login and no local graphics memory, then read the fit on https://localllmrig.com/can-i-run/spark-x2.6-4b.
- What licence does Spark-X2.6-4B use, and is commercial use allowed?
- Spark-X2.6-4B is listed as Apache-2.0, and our reading of the licence is that commercial use is allowed. That is our reading of the licence, not legal advice. File sizes and the machines that hold them are on https://localllmrig.com/can-i-run/spark-x2.6-4b. You can try open models live for free at https://localllmrig.com/.