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Google · dense · Apache-2.0
What runs Gemma 4 E4B IT
On-device Gemma 4 with 4.5B effective parameters (8B with per-layer embeddings) and audio input. Runs on phones, laptops and small GPUs.
- Parameters
- 8B
- 4-bit file
- 5.0 GB
- Q4_K_M
- Needs at 8k context
- 6.5 GB
- context memory not counted
- Longest context
- 131,072 tokens
Context memory: no per-token figure. 35 of 42 layers use 512-token sliding-window attention and 18 layers share KV with earlier layers (num_kv_shared_layers). Card gives no per-token figure. How context memory works.
Measured on this hardware
Machines that hold the 4-bit file with 8,192 tokens of context and have published runs on the same chip or cards, fastest first. Median of single-user runs with plain decoding.
No published run on a machine that fits it.
Estimated, not measured
These fit but nobody has published a run we could match. The figure is memory bandwidth divided by the bytes read per token, scaled by the share of that ceiling measured runs reach. How estimates work.
| Machine | Fit | Price | Generation |
|---|---|---|---|
| Dell Pro Precision with GB300NVIDIA workstation | Fits | ~$159,283 | ~1,585–1,900 tok/sestimate |
| Dell Pro Max Tower T2 with NVIDIA RTX PRO 6000 BlackwellNVIDIA workstation | Fits | ~$13,909 | ~289–454 tok/sestimate |
| 1x RTX 5090Single GPU | Fits | ~$3,234 + unpriced parts | ~289–454 tok/sestimate |
| 2x RTX 5090Multi-GPU | Fits | ~$4,109 + unpriced parts | ~289–454 tok/sestimate |
| 1x RTX PRO 6000 BlackwellSingle GPU | Fits | ~$20,833 | ~289–454 tok/sestimate |
| RTX 5090 + EPYC 9355P with 768 GB DDR5 (MoE offload)Hybrid GPU + RAM | Fits | ~$3,763 + unpriced parts | ~289–454 tok/sestimate |
| Apple Mac Studio (M5 Ultra, 64-core GPU)Apple unified memory | Fitsassumed limitfrom 96 GB | ~$5,499–$9,499 | ~290–361 tok/sestimate |
| Apple Mac Studio (M5 Ultra, 80-core GPU)Apple unified memory | Fitsassumed limitfrom 96 GB | ~$6,799–$10,799 | ~290–361 tok/sestimate |
| 4x Instinct MI50 32GB (used) on EPYC 7003Multi-GPU | Fits | ~$1,998 + unpriced parts | ~165–259 tok/sestimate |
| 2x Radeon RX 7900 XTXMulti-GPU | Fits | ~$5,637 | ~155–243 tok/sestimate |
| 1x RTX 3090 (used)Single GPU | Fits | ~$2,944 + unpriced parts | ~151–237 tok/sestimate |
| 2x RTX 3090 (used)Multi-GPU | Fits | ~$3,639 + unpriced parts | ~151–237 tok/sestimate |
| 4x RTX 3090 (used) on EPYC 7003, open frameMulti-GPU | Fits | ~$2,178 + unpriced parts | ~151–237 tok/sestimate |
| RTX 3090 (used) + 128 GB DDR5 on AM5 (MoE offload)Hybrid GPU + RAM | Fits | ~$4,833 + unpriced parts | ~151–237 tok/sestimate |
| Apple Mac Studio (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 48 GB | ~$3,099–$5,099 | ~148–185 tok/sestimate |
| Apple MacBook Pro 14-inch (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 48 GB | ~$4,699–$6,699 | ~148–185 tok/sestimate |
| Apple MacBook Pro 16-inch (M5 Max, 40-core GPU)Apple unified memory | Fitsassumed limitfrom 48 GB | ~$4,999–$6,999 | ~148–185 tok/sestimate |
| tiny corp tinybox red flashGPU desktop (prebuilt) | Fits | ~$22,000 | ~103–162 tok/sestimate |
| Apple Mac Studio (M5 Max, 32-core GPU)Apple unified memory | Fitsassumed limit | ~$2,499 | ~111–138 tok/sestimate |
| Apple MacBook Pro 14-inch (M5 Max, 32-core GPU)Apple unified memory | Fitsassumed limit | ~$4,099 | ~111–138 tok/sestimate |
| Apple MacBook Pro 16-inch (M5 Max, 32-core GPU)Apple unified memory | Fitsassumed limit | ~$4,399 | ~111–138 tok/sestimate |
| 2x Intel Arc Pro B60Multi-GPU | Fits | ~$4,367 | ~74–115 tok/sestimate |
| Apple Mac mini (M5 Pro, 16-core GPU)Apple unified memory | Fitsassumed limitfrom 24 GB | ~$1,699–$2,699 | ~74–92 tok/sestimate |
| Apple Mac mini (M5 Pro, 20-core GPU)Apple unified memory | Fitsassumed limitfrom 24 GB | ~$1,899–$2,899 | ~74–92 tok/sestimate |
| Framework Desktop (Ryzen AI Max+ PRO 495)AMD unified memory | Fitsassumed limit | ~$6,799 | ~61–73 tok/sestimate |
| NVIDIA DGX SparkNVIDIA GB10 | Fitsassumed limit | ~$4,699 | ~61–73 tok/sestimate |
| Dell Pro Precision with GB10NVIDIA GB10 | Fitsassumed limit | ~$5,523 | ~61–73 tok/sestimate |
| Framework Desktop (Ryzen AI Max+ 395)AMD unified memory | Fitsassumed limitfrom 64 GB | ~$1,959–$3,449 | ~57–68 tok/sestimate |
| Framework Desktop (Ryzen AI Max 385)AMD unified memory | Fitsassumed limit | ~$1,269 | ~57–68 tok/sestimate |
| GMKtec EVO-X2 (Ryzen AI Max+ 395)AMD unified memory | Fitsassumed limitfrom 64 GB | ~$2,600–$4,000 | ~57–68 tok/sestimate |
| Beelink GTR9 Pro (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,699 | ~57–68 tok/sestimate |
| Minisforum MS-S1 MAX (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,899 | ~57–68 tok/sestimate |
| Corsair AI Workstation 300 (Ryzen AI Max+ 395)AMD unified memory | Fits | ~$4,800 | ~57–68 tok/sestimate |
| HP Z2 Mini G1a (Ryzen AI Max+ PRO 395)AMD unified memory | Fits | ~$4,999 | ~57–68 tok/sestimate |
Fits, no speed figure
Files
| Quant | Format | Size | Repo |
|---|---|---|---|
| 4bit | MLX | 4.8 GB | mlx-community/gemma-4-E4B-it-4bit |
| Q4_K_M | GGUF | 5.0 GB | bartowski/google_gemma-4-E4B-it-GGUF |
| Q5_K_M | GGUF | 5.4 GB | bartowski/google_gemma-4-E4B-it-GGUF |
| Q6_K | GGUF | 5.9 GB | bartowski/google_gemma-4-E4B-it-GGUF |
| Q8_0 | GGUF | 7.5 GB | bartowski/google_gemma-4-E4B-it-GGUF |
| 8bit | MLX | 8.3 GB | mlx-community/gemma-4-E4B-it-8bit |
Sources
- huggingface.co: model card: parameters, context length, license and attention layout; release month
- huggingface.co: downloads (last 30 days), license tag, safetensors param count
- huggingface.co: layer count, KV heads and head size
- huggingface.co: GGUF file sizes (shards summed)
- huggingface.co: MLX 4bit safetensors sizes
- huggingface.co: MLX 8bit safetensors sizes