Trinity Mini — Hardware Requirements & GPU Compatibility
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Trinity Mini is a 26.1B-parameter open language model from Arcee AI. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 16.04 GB of VRAM — see which GPUs and Macs can run it below.
22.6K downloads
199 likesSpecifications
- Publisher
- Arcee AI
- Parameters
- 26.1B
- Architecture
- AfmoeForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 200,192
- Release Date
- 2025-12-01
- License
- Other
Get Started
HuggingFace
How Much VRAM Does Trinity Mini Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 11.5 GB | 15.7 GB | 11.10 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 11.8 GB | 16.0 GB | 11.43 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 13.1 GB | 17.3 GB | 12.74 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 13.4 GB | 17.7 GB | 13.06 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 16.0 GB | 20.3 GB | 15.67 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 19.0 GB | 23.2 GB | 18.61 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 21.9 GB | 26.1 GB | 21.55 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 26.5 GB | 30.7 GB | 26.12 GB | 8-bit quantization, near-lossless |
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 Trinity Mini?
Q4_K_M · 16.0 GBTrinity Mini (Q4_K_M) requires 16.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 21+ GB is recommended. Using the full 131K context window can add up to 4.2 GB, bringing total usage to 20.3 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Trinity Mini?
Q4_K_M · 16.0 GB41 devices with unified memory can run Trinity Mini, 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 Trinity Mini
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Frequently Asked Questions
- How much VRAM does Trinity Mini need?
Trinity Mini requires 16.0 GB of VRAM at Q4_K_M, or 52.6 GB at BF16. Full 131K context adds up to 4.2 GB (20.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 26.1B × 4.8 bits ÷ 8 = 15.7 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.6 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M16.0 GBQ4_K_M + full context20.3 GB- Can NVIDIA GeForce RTX 4090 run Trinity Mini?
Yes, at Q6_K (21.9 GB) or lower. Higher quantizations like Q8_0 (26.5 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Trinity Mini?
For Trinity Mini, Q4_K_M (16.0 GB) offers the best balance of quality and VRAM usage. Q4_K_L (16.4 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 7.5 GB.
VRAM requirement by quantization
IQ2_XXS7.5 GBQ2_K11.5 GBIQ4_XS14.4 GBQ4_K_M ★16.0 GBQ4_K_L16.4 GBBF1652.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Trinity Mini on a Mac?
Trinity Mini requires at least 7.5 GB at IQ2_XXS, 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 Trinity Mini locally?
Yes — Trinity Mini can run locally on consumer hardware. At Q4_K_M quantization it needs 16.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Trinity Mini?
At Q4_K_M, Trinity Mini can reach ~274 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~41 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 ÷ 16.0 × 0.65 = ~324 tok/s
Estimated speed at Q4_K_M (16.0 GB)
~324 tok/s~41 tok/s~324 tok/s~274 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Trinity Mini?
At Q4_K_M, the download is about 15.67 GB. The full-precision BF16 version is 52.25 GB. The smallest option (IQ2_XXS) is 7.18 GB.
- Which GPUs can run Trinity Mini?
8 consumer GPUs can run Trinity Mini at Q4_K_M (16.0 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Trinity Mini?
41 devices with unified memory can run Trinity Mini at Q4_K_M (16.0 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.