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Lumina Image 2.0 VRAM requirements

A 2.6B model from Alpha-VLLM and the base of the popular Neta Lumina anime fine-tunes. Small and quick.

Released 2025-01Licence: Apache-2.0Steps: 25–40Text encoder: Gemma 2 2B (5.2 GB as 16-bit)
TypeImage
Parameters2.61B
Fits entirely from3 GB
8-bit or better from5 GB

01The files, and how much VRAM each needs

FileSizeNeededMin. VRAMQualitySource
16-bit5.2 GB7.0 GB8 GBthe original weightsComfy-Org/Lumina_Image_2.0_Repackaged →
Q8_02.8 GB4.6 GB5 GBpractically identical to the originalcalcuis/lumina-gguf →
Q6_K2.1 GB3.9 GB4 GBvery close to the originalcalcuis/lumina-gguf →
Q5_K_M1.8 GB3.6 GB4 GBclose; small differences in fine detailcalcuis/lumina-gguf →
Q4_K_M1.5 GB3.3 GB4 GBgood; some loss in fine detail and textcalcuis/lumina-gguf →
Q3_K_M1.1 GB2.9 GB3 GBnoticeable loss of detailcalcuis/lumina-gguf →
Q2_K1.1 GB2.9 GB3 GBheavy loss; a last resortcalcuis/lumina-gguf →

“Needed” = file + 1 GB working memory + 0.8 GB system reserve.

03Best GPU for Lumina 2.0

The cheapest cards (by launch price) that run it well, and every card sorted by memory: best GPU for Lumina 2.0 → Planning bigger images or longer clips? Open the calculator →

04By graphics card

GPUVRAMVerdictBest fileNeeded
Desktop graphics cards
RTX 2060 6 GB6 GBRuns wellQ8_04.6 GB
RTX 3050 6 GB6 GBRuns wellQ8_04.6 GB
RTX 2070 Super 8 GB8 GBRuns well16-bit7.0 GB
RTX 2080 Super 8 GB8 GBRuns well16-bit7.0 GB
RTX 3050 8 GB8 GBRuns well16-bit7.0 GB
RTX 3060 8 GB8 GBRuns well16-bit7.0 GB
RTX 3060 Ti 8 GB8 GBRuns well16-bit7.0 GB
RTX 3070 8 GB8 GBRuns well16-bit7.0 GB
RTX 3070 Ti 8 GB8 GBRuns well16-bit7.0 GB
RTX 4060 8 GB8 GBRuns well16-bit7.0 GB
RTX 4060 Ti 8 GB8 GBRuns well16-bit7.0 GB
RTX 5050 8 GB8 GBRuns well16-bit7.0 GB
RTX 5060 8 GB8 GBRuns well16-bit7.0 GB
RTX 5060 Ti 8 GB8 GBRuns well16-bit7.0 GB
RX 7600 8 GB8 GBRuns well16-bit7.0 GB
RX 9050 8 GB8 GBRuns well16-bit7.0 GB
RX 9060 XT 8 GB8 GBRuns well16-bit7.0 GB
Arc B570 10 GB10 GBRuns well16-bit7.0 GB
RTX 3080 10 GB10 GBRuns well16-bit7.0 GB
RTX 2080 Ti 11 GB11 GBRuns well16-bit7.0 GB
Arc B580 12 GB12 GBRuns well16-bit7.0 GB
RTX 2060 12 GB12 GBRuns well16-bit7.0 GB
RTX 3060 12 GB12 GBRuns well16-bit7.0 GB
RTX 3080 12 GB12 GBRuns well16-bit7.0 GB
RTX 3080 Ti 12 GB12 GBRuns well16-bit7.0 GB
RTX 4070 12 GB12 GBRuns well16-bit7.0 GB
RTX 4070 Super 12 GB12 GBRuns well16-bit7.0 GB
RTX 4070 Ti 12 GB12 GBRuns well16-bit7.0 GB
RTX 5070 12 GB12 GBRuns well16-bit7.0 GB
RX 7700 XT 12 GB12 GBRuns well16-bit7.0 GB
RX 9070 GRE 12 GB12 GBRuns well16-bit7.0 GB
Arc A770 16 GB16 GBRuns well16-bit7.0 GB
RTX 4060 Ti 16 GB16 GBRuns well16-bit7.0 GB
RTX 4070 Ti Super 16 GB16 GBRuns well16-bit7.0 GB
RTX 4080 16 GB16 GBRuns well16-bit7.0 GB
RTX 4080 Super 16 GB16 GBRuns well16-bit7.0 GB
RTX 5060 Ti 16 GB16 GBRuns well16-bit7.0 GB
RTX 5070 Ti 16 GB16 GBRuns well16-bit7.0 GB
RTX 5080 16 GB16 GBRuns well16-bit7.0 GB
RX 7600 XT 16 GB16 GBRuns well16-bit7.0 GB
RX 7800 XT 16 GB16 GBRuns well16-bit7.0 GB
RX 7900 GRE 16 GB16 GBRuns well16-bit7.0 GB
RX 9060 XT 16 GB16 GBRuns well16-bit7.0 GB
RX 9070 16 GB16 GBRuns well16-bit7.0 GB
RX 9070 XT 16 GB16 GBRuns well16-bit7.0 GB
RX 7900 XT 20 GB20 GBRuns well16-bit7.0 GB
Arc Pro B60 24 GB24 GBRuns well16-bit7.0 GB
RTX 3090 24 GB24 GBRuns well16-bit7.0 GB
RTX 3090 Ti 24 GB24 GBRuns well16-bit7.0 GB
RTX 4090 24 GB24 GBRuns well16-bit7.0 GB
RX 7900 XTX 24 GB24 GBRuns well16-bit7.0 GB
Arc Pro B70 32 GB32 GBRuns well16-bit7.0 GB
RTX 5090 32 GB32 GBRuns well16-bit7.0 GB
Laptop GPUs
RTX 3050 Laptop 4 GB4 GBRunsQ6_K3.9 GB
RTX 3050 Ti Laptop 4 GB4 GBRunsQ6_K3.9 GB
RTX 2060 Laptop 6 GB6 GBRuns wellQ8_04.6 GB
RTX 3050 Laptop 6 GB6 GBRuns wellQ8_04.6 GB
RTX 3060 Laptop 6 GB6 GBRuns wellQ8_04.6 GB
RTX 4050 Laptop 6 GB6 GBRuns wellQ8_04.6 GB
RTX 2070 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 2070 Super Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 2080 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 2080 Super Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 3070 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 3070 Ti Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 3080 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 4060 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 4070 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 5050 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 5060 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RTX 5070 Laptop 8 GB8 GBRuns well16-bit7.0 GB
RX 7600M 8 GB8 GBRuns well16-bit7.0 GB
RX 7600M XT 8 GB8 GBRuns well16-bit7.0 GB
RX 7600S 8 GB8 GBRuns well16-bit7.0 GB
RX 7700S 8 GB8 GBRuns well16-bit7.0 GB
RTX 4080 Laptop 12 GB12 GBRuns well16-bit7.0 GB
RTX 5070 Laptop 12 GB12 GBRuns well16-bit7.0 GB
RTX 5070 Ti Laptop 12 GB12 GBRuns well16-bit7.0 GB
RX 7800M 12 GB12 GBRuns well16-bit7.0 GB
RTX 3080 Laptop 16 GB16 GBRuns well16-bit7.0 GB
RTX 3080 Ti Laptop 16 GB16 GBRuns well16-bit7.0 GB
RTX 4090 Laptop 16 GB16 GBRuns well16-bit7.0 GB
RTX 5080 Laptop 16 GB16 GBRuns well16-bit7.0 GB
RX 7900M 16 GB16 GBRuns well16-bit7.0 GB
RTX 5090 Laptop 24 GB24 GBRuns well16-bit7.0 GB
Unified memory
Radeon 8060S (Strix Halo) 96 GB96 GBRuns well16-bit7.0 GB
Radeon 8065S (Gorgon Halo) 160 GB160 GBRuns well16-bit7.0 GB
Apple Silicon Macs (by memory)
Mac 16 GB12.7 GBRuns well16-bit7.0 GB
Mac 18 GB14.4 GBRuns well16-bit7.0 GB
Mac 24 GB19.6 GBRuns well16-bit7.0 GB
Mac 32 GB26.8 GBRuns well16-bit7.0 GB
Mac 36 GB30.2 GBRuns well16-bit7.0 GB
Mac 48 GB40.2 GBRuns well16-bit7.0 GB
Mac 64 GB55.7 GBRuns well16-bit7.0 GB
Mac 96 GB85 GBRuns well16-bit7.0 GB
Mac 128 GB115.4 GBRuns well16-bit7.0 GB
Mac 192 GB175.4 GBRuns well16-bit7.0 GB
Mac 256 GB236.9 GBRuns well16-bit7.0 GB
Mac 512 GB498.1 GBRuns well16-bit7.0 GB

05Text encoder, VAE and other files

FileFolderSizeWhen
Gemma 2 2B FP16
gemma_2_2b_fp16.safetensors
models/text_encoders5.2 GBrequiredDownload →
FLUX.1 VAE (ae)
ae.safetensors
models/vae0.3 GBrequiredDownload →

The files the official ComfyUI workflows load next to the model. Sizes read from Hugging Face (2026-10-01).

06Where the files go in ComfyUI

FileFolderLoader node
Diffusion model (.safetensors: 16-bit, FP8, INT8)ComfyUI/models/diffusion_modelsLoad Diffusion Model
GGUF file (.gguf)ComfyUI/models/unetUnet Loader (GGUF) - from the ComfyUI-GGUF node pack
Text encoderComfyUI/models/text_encodersLoad CLIP / DualCLIPLoader (or the GGUF versions)
VAEComfyUI/models/vaeLoad VAE

07Measured and reported results

No measured results yet. Send yours.

08Training a LoRA for Lumina 2.0

No trainer documentation with a VRAM figure for this model was found yet. What the trainers say for other models →

09Every file tracked for Lumina 2.0

FileTypeSizeRepo
lumina_2.safetensors16-bit10.62 GBComfy-Org/Lumina_Image_2.0_Repackaged →
all-in-one checkpoint: includes text encoder(s) and VAE, not diffusion-model-only (Gemma 2 2B + VAE)
lumina_2_model_bf16.safetensorsBF165.22 GBComfy-Org/Lumina_Image_2.0_Repackaged →
lumina2-q8_0.ggufQ8_02.77 GBcalcuis/lumina-gguf →
lumina2-q6_k.ggufQ6_K2.14 GBcalcuis/lumina-gguf →
lumina2-q5_1.ggufQ5_11.96 GBcalcuis/lumina-gguf →
lumina2-q5_k_m.ggufQ5_K_M1.79 GBcalcuis/lumina-gguf →
lumina2-q5_0.ggufQ5_01.79 GBcalcuis/lumina-gguf →
lumina2-q5_k_s.ggufQ5_K_S1.69 GBcalcuis/lumina-gguf →
lumina2-q4_1.ggufQ4_11.63 GBcalcuis/lumina-gguf →
lumina2-q4_k_m.ggufQ4_K_M1.47 GBcalcuis/lumina-gguf →
lumina2-q4_0.ggufQ4_01.47 GBcalcuis/lumina-gguf →
lumina2-q4_k_s.ggufQ4_K_S1.24 GBcalcuis/lumina-gguf →
lumina2-q3_k_m.ggufQ3_K_M1.12 GBcalcuis/lumina-gguf →
lumina2-q2_k.ggufQ2_K1.08 GBcalcuis/lumina-gguf →

2.6B Unified Next-DiT from Alpha-VLLM (HF API 2.61B F32). VAE: FLUX.1 ae.safetensors (335304388). Native ComfyUI support since Feb 2025. Base of popular anime fine-tunes Neta Lumina / NetaYume Lumina.