Gemma 4 12B Coder Fable5 Composer2.5 V1 — Hardware Requirements & GPU Compatibility
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Gemma 4 12B Coder Fable5 Composer2.5 V1 is a 12.0B-parameter open language model from yuxinlu1 in the Gemma 4 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 8.23 GB of VRAM — see which GPUs and Macs can run it below.
37.9K downloads
55 likesSpecifications
- Publisher
- yuxinlu1
- Family
- Gemma 4
- Parameters
- 12.0B
- Architecture
- Gemma4UnifiedForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-06-17
- License
- Apache 2.0
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How Much VRAM Does Gemma 4 12B Coder Fable5 Composer2.5 V1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 6.1 GB | 102.0 GB | 5.08 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 6.9 GB | 102.8 GB | 5.83 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 8.2 GB | 104.1 GB | 7.18 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 9.6 GB | 105.5 GB | 8.52 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 10.9 GB | 106.8 GB | 9.87 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 13.0 GB | 108.9 GB | 11.96 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 25.0 GB | 120.9 GB | 23.92 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 12B Coder Fable5 Composer2.5 V1?
Q4_K_M · 8.2 GBGemma 4 12B Coder Fable5 Composer2.5 V1 (Q4_K_M) requires 8.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 11+ GB is recommended. Using the full 262K context window can add up to 95.9 GB, bringing total usage to 104.1 GB. 39 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Gemma 4 12B Coder Fable5 Composer2.5 V1?
Q4_K_M · 8.2 GB49 devices with unified memory can run Gemma 4 12B Coder Fable5 Composer2.5 V1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Gemma 4 12B Coder Fable5 Composer2.5 V1
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 12B Coder Fable5 Composer2.5 V1 need?
Gemma 4 12B Coder Fable5 Composer2.5 V1 requires 8.2 GB of VRAM at Q4_K_M, or 25.0 GB at BF16. Full 262K context adds up to 95.9 GB (104.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 12.0B × 4.8 bits ÷ 8 = 7.2 GB
KV Cache + Overhead ≈ 1 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 96.9 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M8.2 GBQ4_K_M + full context104.1 GB- Can NVIDIA GeForce RTX 4090 run Gemma 4 12B Coder Fable5 Composer2.5 V1?
Yes, at Q8_0 (13.0 GB) or lower. Higher quantizations like BF16 (25.0 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Gemma 4 12B Coder Fable5 Composer2.5 V1?
For Gemma 4 12B Coder Fable5 Composer2.5 V1, Q4_K_M (8.2 GB) offers the best balance of quality and VRAM usage. Q5_K_M (9.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 6.1 GB.
VRAM requirement by quantization
Q2_K6.1 GBQ4_K_M ★8.2 GBQ5_K_M9.6 GBQ6_K10.9 GBQ8_013.0 GBBF1625.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 4 12B Coder Fable5 Composer2.5 V1 on a Mac?
Gemma 4 12B Coder Fable5 Composer2.5 V1 requires at least 6.1 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 12B Coder Fable5 Composer2.5 V1 locally?
Yes — Gemma 4 12B Coder Fable5 Composer2.5 V1 can run locally on consumer hardware. At Q4_K_M quantization it needs 8.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 4 12B Coder Fable5 Composer2.5 V1?
At Q4_K_M, Gemma 4 12B Coder Fable5 Composer2.5 V1 can reach ~535 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~80 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 ÷ 8.2 × 0.65 = ~632 tok/s
Estimated speed at Q4_K_M (8.2 GB)
~632 tok/s~80 tok/s~632 tok/s~535 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 12B Coder Fable5 Composer2.5 V1?
At Q4_K_M, the download is about 7.18 GB. The full-precision BF16 version is 23.92 GB. The smallest option (Q2_K) is 5.08 GB.
- Which GPUs can run Gemma 4 12B Coder Fable5 Composer2.5 V1?
39 consumer GPUs can run Gemma 4 12B Coder Fable5 Composer2.5 V1 at Q4_K_M (8.2 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Gemma 4 12B Coder Fable5 Composer2.5 V1?
52 devices with unified memory can run Gemma 4 12B Coder Fable5 Composer2.5 V1 at Q4_K_M (8.2 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.