Liquid AI·LFM2.5·Lfm2DSparkDraftModel

LFM2.5 8B A1B DSpark — Hardware Requirements & GPU Compatibility

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LFM2.5 8B A1B DSpark is a 8B-parameter open language model from Liquid AI in the LFM2.5 family. It supports a context window of up to 128,000 tokens. At Q4_K_M it needs about 5.12 GB of VRAM — see which GPUs and Macs can run it below.

4.2K downloads 38 likes 112.2K quant downloads128K context
Based on LFM2.5 8B A1B

Specifications

Publisher
Liquid AI
Family
LFM2.5
Parameters
8B
Architecture
Lfm2DSparkDraftModel
Context Length
128,000 tokens
Vocabulary Size
128,000
Release Date
2026-08-10
License
Other

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How Much VRAM Does LFM2.5 8B A1B DSpark Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q2_Kest.3.403.7 GB
Q3_K_Mest.3.904.2 GB
Q4_K_M4.805.1 GB
Q5_K_Mest.5.706.0 GB
Q6_Kest.6.606.9 GB
Q8_08.008.3 GB
BF16est.16.0016.3 GB

est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.

Which GPUs Can Run LFM2.5 8B A1B DSpark?

Q4_K_M · 5.1 GB

LFM2.5 8B A1B DSpark (Q4_K_M) requires 5.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 128K context window can add up to 1.3 GB, bringing total usage to 6.4 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Runs great

— Plenty of headroom
NVIDIA GeForce RTX 5090~1213 tok/sNVIDIA GeForce RTX 3090 Ti~799 tok/sNVIDIA GeForce RTX 4090~799 tok/sNVIDIA GeForce RTX 5080~769 tok/sNVIDIA GeForce RTX 3090~754 tok/sNVIDIA GeForce RTX 3080 Ti~739 tok/sNVIDIA GeForce RTX 5070 Ti~728 tok/sNVIDIA GeForce RTX 5090 Laptop GPU~728 tok/sNVIDIA GeForce RTX 3080~637 tok/sNVIDIA GeForce RTX 4080 SUPER~620 tok/sNVIDIA GeForce RTX 4080~607 tok/sNVIDIA GeForce RTX 4070 Ti SUPER~575 tok/sNVIDIA GeForce RTX 5070~575 tok/sNVIDIA TITAN RTX~575 tok/sNVIDIA GeForce RTX 2080 Ti~534 tok/sNVIDIA GeForce RTX 3070 Ti~528 tok/sNVIDIA GeForce RTX 4090 Laptop GPU~504 tok/sAMD Radeon RX 7900 XTX~474 tok/sNVIDIA GeForce RTX 4070~449 tok/sNVIDIA GeForce RTX 4070 SUPER~449 tok/sNVIDIA GeForce RTX 4070 Ti~449 tok/sNVIDIA GeForce GTX 1080 Ti~433 tok/sAMD Radeon RX 7900 XT~429 tok/sNVIDIA GeForce RTX 3060 Ti~404 tok/sNVIDIA GeForce RTX 3070~404 tok/sNVIDIA GeForce RTX 5060~404 tok/sNVIDIA GeForce RTX 5060 Ti 16GB~404 tok/sNVIDIA GeForce RTX 5060 Ti 8GB~404 tok/sAMD Radeon RX 9070~375 tok/sAMD Radeon RX 9070 XT~375 tok/sAMD Radeon RX 7800 XT~369 tok/sAMD Radeon RX 7900 GRE~351 tok/sNVIDIA GeForce RTX 3060 12GB~332 tok/sAMD Radeon RX 6800~324 tok/sAMD Radeon RX 6800 XT~324 tok/sAMD Radeon RX 6900 XT~324 tok/sIntel Arc A770 16GB~304 tok/sAMD Radeon RX 7700 XT~288 tok/sAMD Radeon RX 9070 GRE~288 tok/sIntel Arc A750~286 tok/sNVIDIA GeForce RTX 4060 Ti 16GB~271 tok/sNVIDIA GeForce RTX 4060 Ti 8GB~271 tok/sAMD Radeon RX 6700 XT~265 tok/sIntel Arc B580~263 tok/sNVIDIA GeForce RTX 4060~257 tok/sAMD Radeon RX 9060 XT 16GB~231 tok/sIntel Arc B570~229 tok/sNVIDIA GeForce RTX 3060 8GB~228 tok/sNVIDIA GeForce RTX 3050 8GB~214 tok/sAMD Radeon RX 7600~213 tok/sAMD Radeon RX 7600 XT~213 tok/sAMD Radeon RX 9050~213 tok/s

Which Devices Can Run LFM2.5 8B A1B DSpark?

Q4_K_M · 5.1 GB

58 devices with unified memory can run LFM2.5 8B A1B DSpark, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.

Runs great

— Plenty of headroom
NVIDIA DGX H100~3208 tok/sNVIDIA DGX A100 640GB~2982 tok/sMac Studio (M3 Ultra, 256GB)~473 tok/sMac Studio (M3 Ultra, 512GB)~473 tok/sMac Studio (M3 Ultra, 96GB)~473 tok/sMac Pro M2 Ultra (192 GB)~467 tok/sMac Studio M2 Ultra (192 GB)~467 tok/sMacBook Pro 16" M5 Max (128 GB)~402 tok/sMac Studio M4 Max (128 GB)~374 tok/sMac Studio M4 Max (64 GB)~374 tok/sMacBook Pro 16" M4 Max (48 GB)~374 tok/sMacBook Pro 16" M4 Max (64 GB)~374 tok/sMac Studio M4 Max (36 GB)~309 tok/sMacBook Pro 14" M4 Max (36 GB)~309 tok/sMacBook Pro 16" M3 Max (48 GB)~309 tok/sNVIDIA DGX Spark~258 tok/sNVIDIA Jetson AGX Thor Developer Kit~258 tok/sMacBook Pro 14-inch (M5 Pro)~251 tok/sASUS Ascent GX10~244 tok/sAsus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB)~230 tok/sBeelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB)~230 tok/sFramework Desktop (Ryzen AI Max+ 395, 128 GB)~230 tok/sGMKtec EVO-X2 (Ryzen AI Max+ 395, 128 GB)~230 tok/sHP Z2 Mini G1a (Ryzen AI Max+ PRO 395, 128 GB)~230 tok/sHP ZBook Ultra G1a 14 (Ryzen AI Max+ PRO 395, 128 GB)~230 tok/sMinisforum MS-S1 MAX (Ryzen AI Max+ 395, 128 GB)~230 tok/sMac Mini M4 Pro (24 GB)~230 tok/sMac Mini M4 Pro (48 GB)~230 tok/sMacBook Pro 14" M4 Pro (24 GB)~230 tok/sMacBook Pro 16" M4 Pro (24 GB)~230 tok/sSnapdragon X2 Elite Extreme Copilot+ PC~208 tok/sNVIDIA Jetson AGX Orin 32GB~197 tok/sNVIDIA Jetson AGX Orin 64GB~197 tok/sMacBook Pro 14-inch (M5)~144 tok/siPad Pro M5 13" (16 GB)~143 tok/sSnapdragon X Elite Copilot+ PC~128 tok/sMac Mini M4 (16 GB)~116 tok/sMac Mini M4 (32 GB)~116 tok/sMacBook Air 13" M4 (16 GB)~116 tok/sMacBook Air 13" M4 (24 GB)~116 tok/sMacBook Air 15" M4 (16 GB)~116 tok/sMacBook Air 15" M4 (24 GB)~116 tok/sMacBook Pro 14" M4 (16 GB)~116 tok/siPad Pro M4 13" (16 GB)~116 tok/sAMD Ryzen AI 9 HX 370 (Strix Point) Laptop~101 tok/sNVIDIA Jetson Orin NX 16GB~101 tok/sMacBook Air 13" M3 (16 GB)~101 tok/sMacBook Air 13" M3 (24 GB)~101 tok/sMacBook Air 13" M3 (8 GB)~101 tok/sNVIDIA Jetson Orin Nano 8GB (Super)~101 tok/sIntel Core Ultra 9 288V (Lunar Lake) Laptop~96 tok/siPhone 15 ProiPhone 15 Pro MaxiPhone 16 ProiPhone 16 Pro Max

Where to Download LFM2.5 8B A1B DSpark

Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.

Related Models

Frequently Asked Questions

How much VRAM does LFM2.5 8B A1B DSpark need?

LFM2.5 8B A1B DSpark requires 5.1 GB of VRAM at Q4_K_M, or 16.3 GB at BF16. Full 128K context adds up to 1.3 GB (6.4 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 8B × 4.8 bits ÷ 8 = 4.8 GB

KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead ≈ 1.6 GB (at full 128K context)

VRAM usage by quantization

5.1 GB
6.4 GB

Learn more about VRAM estimation →

What's the best quantization for LFM2.5 8B A1B DSpark?

For LFM2.5 8B A1B DSpark, Q4_K_M (5.1 GB) offers the best balance of quality and VRAM usage. Q5_K_M (6.0 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.7 GB.

VRAM requirement by quantization

Q2_K
3.7 GB
Q4_K_M ★
5.1 GB
Q5_K_M
6.0 GB
Q6_K
6.9 GB
Q8_0
8.3 GB
BF16
16.3 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run LFM2.5 8B A1B DSpark on a Mac?

LFM2.5 8B A1B DSpark requires at least 3.7 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.

Can I run LFM2.5 8B A1B DSpark locally?

Yes — LFM2.5 8B A1B DSpark can run locally on consumer hardware. At Q4_K_M quantization it needs 5.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is LFM2.5 8B A1B DSpark?

At Q4_K_M, LFM2.5 8B A1B DSpark can reach ~882 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~799 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: NVIDIA B200 → 8000 ÷ 5.1 × 0.65 = ~2512 tok/s

Estimated speed at Q4_K_M (5.1 GB)

~2512 tok/s
~799 tok/s
~2512 tok/s
~2101 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of LFM2.5 8B A1B DSpark?

At Q4_K_M, the download is about 4.80 GB. The full-precision BF16 version is 16.00 GB. The smallest option (Q2_K) is 3.40 GB.

Which GPUs can run LFM2.5 8B A1B DSpark?

52 consumer GPUs can run LFM2.5 8B A1B DSpark at Q4_K_M (5.1 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.

Which devices can run LFM2.5 8B A1B DSpark?

59 devices with unified memory can run LFM2.5 8B A1B DSpark at Q4_K_M (5.1 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.