Gemma 4 31B IT Speculator.eagle3 — Hardware Requirements & GPU Compatibility
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Gemma 4 31B IT Speculator.eagle3 is a 31B-parameter open language model from RedHatAI in the Gemma 4 family. At Q4_K_M it needs about 20.46 GB of VRAM — see which GPUs and Macs can run it below.
100.2K downloads
49 likesSpecifications
- Publisher
- RedHatAI
- Family
- Gemma 4
- Parameters
- 31B
- Architecture
- Eagle3DraftModel
- Release Date
- 2026-04-09
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Gemma 4 31B IT Speculator.eagle3 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 14.5 GB | — | 13.18 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 16.6 GB | — | 15.11 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 20.5 GB | — | 18.60 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 24.3 GB | — | 22.09 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 28.1 GB | — | 25.57 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 34.1 GB | — | 31.00 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 68.2 GB | — | 62.00 GB | Brain floating point 16 — preferred for training |
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 Gemma 4 31B IT Speculator.eagle3?
Q4_K_M · 20.5 GBGemma 4 31B IT Speculator.eagle3 (Q4_K_M) requires 20.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 27+ GB is recommended. 7 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Gemma 4 31B IT Speculator.eagle3?
Q4_K_M · 20.5 GB41 devices with unified memory can run Gemma 4 31B IT Speculator.eagle3, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Gemma 4 31B IT Speculator.eagle3
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 Gemma 4 31B IT Speculator.eagle3 need?
Gemma 4 31B IT Speculator.eagle3 requires 20.5 GB of VRAM at Q4_K_M, or 68.2 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 31B × 4.8 bits ÷ 8 = 18.6 GB
KV Cache + Overhead ≈ 1.9 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M20.5 GB- Can NVIDIA GeForce RTX 4090 run Gemma 4 31B IT Speculator.eagle3?
Yes, at Q4_K_M (20.5 GB) or lower. Higher quantizations like Q5_K_M (24.3 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Gemma 4 31B IT Speculator.eagle3?
For Gemma 4 31B IT Speculator.eagle3, Q4_K_M (20.5 GB) offers the best balance of quality and VRAM usage. Q5_K_M (24.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 14.5 GB.
VRAM requirement by quantization
Q2_K14.5 GBQ4_K_M ★20.5 GBQ5_K_M24.3 GBQ6_K28.1 GBQ8_034.1 GBBF1668.2 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 4 31B IT Speculator.eagle3 on a Mac?
Gemma 4 31B IT Speculator.eagle3 requires at least 14.5 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 Gemma 4 31B IT Speculator.eagle3 locally?
Yes — Gemma 4 31B IT Speculator.eagle3 can run locally on consumer hardware. At Q4_K_M quantization it needs 20.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 4 31B IT Speculator.eagle3?
At Q4_K_M, Gemma 4 31B IT Speculator.eagle3 can reach ~215 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~32 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 ÷ 20.5 × 0.65 = ~254 tok/s
Estimated speed at Q4_K_M (20.5 GB)
~254 tok/s~32 tok/s~254 tok/s~215 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma 4 31B IT Speculator.eagle3?
At Q4_K_M, the download is about 18.60 GB. The full-precision BF16 version is 62.00 GB. The smallest option (Q2_K) is 13.18 GB.
- Which GPUs can run Gemma 4 31B IT Speculator.eagle3?
7 consumer GPUs can run Gemma 4 31B IT Speculator.eagle3 at Q4_K_M (20.5 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Gemma 4 31B IT Speculator.eagle3?
41 devices with unified memory can run Gemma 4 31B IT Speculator.eagle3 at Q4_K_M (20.5 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (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.