MiniMax M2.7 JANGTQ K CRACK — Hardware Requirements & GPU Compatibility
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MiniMax M2.7 JANGTQ K CRACK is a 20.0B-parameter open language model from dealignai in the MiniMax family. It supports a context window of up to 196,608 tokens. At Q4_K_M it needs about 12.55 GB of VRAM — see which GPUs and Macs can run it below.
971 downloads
14 likesSpecifications
- Publisher
- dealignai
- Family
- MiniMax
- Parameters
- 20.0B
- Architecture
- MiniMaxM2ForCausalLM
- Context Length
- 196,608 tokens
- Vocabulary Size
- 200,064
- Release Date
- 2026-05-09
- License
- Other
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HuggingFace
How Much VRAM Does MiniMax M2.7 JANGTQ K CRACK Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 9.1 GB | 33.8 GB | 8.49 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 10.3 GB | 35.0 GB | 9.74 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 12.6 GB | 37.3 GB | 11.99 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 14.8 GB | 39.5 GB | 14.24 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 17.1 GB | 41.8 GB | 16.49 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 20.5 GB | 45.3 GB | 19.98 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 40.5 GB | 65.2 GB | 39.97 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 MiniMax M2.7 JANGTQ K CRACK?
Q4_K_M · 12.6 GBMiniMax M2.7 JANGTQ K CRACK (Q4_K_M) requires 12.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 17+ GB is recommended. Using the full 197K context window can add up to 24.7 GB, bringing total usage to 37.3 GB. 26 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run MiniMax M2.7 JANGTQ K CRACK?
Q4_K_M · 12.6 GB48 devices with unified memory can run MiniMax M2.7 JANGTQ K CRACK, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does MiniMax M2.7 JANGTQ K CRACK need?
MiniMax M2.7 JANGTQ K CRACK requires 12.6 GB of VRAM at Q4_K_M, or 40.5 GB at BF16. Full 197K context adds up to 24.7 GB (37.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 20.0B × 4.8 bits ÷ 8 = 12 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 25.3 GB (at full 197K context)
VRAM usage by quantization
Q4_K_M12.6 GBQ4_K_M + full context37.3 GB- Can NVIDIA GeForce RTX 4090 run MiniMax M2.7 JANGTQ K CRACK?
Yes, at Q8_0 (20.5 GB) or lower. Higher quantizations like BF16 (40.5 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for MiniMax M2.7 JANGTQ K CRACK?
For MiniMax M2.7 JANGTQ K CRACK, Q4_K_M (12.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (14.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 9.1 GB.
VRAM requirement by quantization
Q2_K9.1 GBQ4_K_M ★12.6 GBQ5_K_M14.8 GBQ6_K17.1 GBQ8_020.5 GBBF1640.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run MiniMax M2.7 JANGTQ K CRACK on a Mac?
MiniMax M2.7 JANGTQ K CRACK requires at least 9.1 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 MiniMax M2.7 JANGTQ K CRACK locally?
Yes — MiniMax M2.7 JANGTQ K CRACK can run locally on consumer hardware. At Q4_K_M quantization it needs 12.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is MiniMax M2.7 JANGTQ K CRACK?
At Q4_K_M, MiniMax M2.7 JANGTQ K CRACK can reach ~351 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~52 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 ÷ 12.6 × 0.65 = ~414 tok/s
Estimated speed at Q4_K_M (12.6 GB)
~414 tok/s~52 tok/s~414 tok/s~351 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of MiniMax M2.7 JANGTQ K CRACK?
At Q4_K_M, the download is about 11.99 GB. The full-precision BF16 version is 39.97 GB. The smallest option (Q2_K) is 8.49 GB.
- Which GPUs can run MiniMax M2.7 JANGTQ K CRACK?
26 consumer GPUs can run MiniMax M2.7 JANGTQ K CRACK at Q4_K_M (12.6 GB). Top options include AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, AMD Radeon RX 6800. 8 GPUs have plenty of headroom for comfortable inference.
- Which devices can run MiniMax M2.7 JANGTQ K CRACK?
49 devices with unified memory can run MiniMax M2.7 JANGTQ K CRACK at Q4_K_M (12.6 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.