AI21 Jamba Mini 1.5 — Hardware Requirements & GPU Compatibility
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AI21 Jamba Mini 1.5 is a 51.6B-parameter open language model from AI21 Labs in the Jamba family. At BF16 it needs about 113.45 GB of VRAM — see which GPUs and Macs can run it below.
23.8K downloads
270 likesSpecifications
- Publisher
- AI21 Labs
- Family
- Jamba
- Parameters
- 51.6B
- Release Date
- 2024-08-19
- License
- Other
Get Started
HuggingFace
How Much VRAM Does AI21 Jamba Mini 1.5 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 113.5 GB | — | 103.14 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 AI21 Jamba Mini 1.5?
BF16 · 113.5 GBAI21 Jamba Mini 1.5 (BF16) requires 113.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 148+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run AI21 Jamba Mini 1.5?
BF16 · 113.5 GB10 devices with unified memory can run AI21 Jamba Mini 1.5, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Pro 16" M5 Max (128 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightFrequently Asked Questions
- How much VRAM does AI21 Jamba Mini 1.5 need?
AI21 Jamba Mini 1.5 requires 113.5 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 51.6B × 16 bits ÷ 8 = 103.1 GB
KV Cache + Overhead ≈ 10.4 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF16113.5 GB- Can NVIDIA GeForce RTX 5090 run AI21 Jamba Mini 1.5?
No — AI21 Jamba Mini 1.5 requires at least 113.5 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run AI21 Jamba Mini 1.5 on a Mac?
AI21 Jamba Mini 1.5 requires at least 113.5 GB at BF16, 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 AI21 Jamba Mini 1.5 locally?
Yes — AI21 Jamba Mini 1.5 can run locally on consumer hardware. At BF16 quantization it needs 113.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is AI21 Jamba Mini 1.5?
At BF16, AI21 Jamba Mini 1.5 can reach ~39 tok/s on AMD Instinct MI350X. 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 ÷ 113.5 × 0.65 = ~46 tok/s
Estimated speed at BF16 (113.5 GB)
~46 tok/s~46 tok/s~39 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of AI21 Jamba Mini 1.5?
At BF16, the download is about 103.14 GB.
- Which GPUs can run AI21 Jamba Mini 1.5?
No single consumer GPU has enough VRAM to run AI21 Jamba Mini 1.5 at BF16 (113.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run AI21 Jamba Mini 1.5?
18 devices with unified memory can run AI21 Jamba Mini 1.5 at BF16 (113.5 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (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.