Inkling Small — Hardware Requirements & GPU Compatibility
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Inkling Small is a 266.0B-parameter open language model from Thinking Machines in the Inkling family. At Q4_K_M it needs about 160.23 GB of VRAM — see which GPUs and Macs can run it below.
272.6K downloads
401 likesSpecifications
- Publisher
- Thinking Machines
- Family
- Inkling
- Parameters
- 266.0B
- Architecture
- InklingForConditionalGeneration
- Vocabulary Size
- 201,024
- Release Date
- 2026-07-27
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Inkling Small Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 113.7 GB | — | 113.03 GB | 2-bit quantization with K-quant improvements |
| Q3_K_M | 3.90 | 130.3 GB | — | 129.65 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 160.2 GB | — | 159.57 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 190.2 GB | — | 189.49 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 220.1 GB | — | 219.41 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 266.6 GB | — | 265.96 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Inkling Small?
Q4_K_M · 160.2 GBInkling Small (Q4_K_M) requires 160.2 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 209+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Inkling Small?
Q4_K_M · 160.2 GB6 devices with unified memory can run Inkling Small, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 256GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Inkling Small
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Frequently Asked Questions
- How much VRAM does Inkling Small need?
Inkling Small requires 160.2 GB of VRAM at Q4_K_M, or 532.6 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 266.0B × 4.8 bits ÷ 8 = 159.6 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M160.2 GB- Can NVIDIA GeForce RTX 5090 run Inkling Small?
No — Inkling Small requires at least 73.8 GB at IQ2_XXS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Inkling Small?
For Inkling Small, Q4_K_M (160.2 GB) offers the best balance of quality and VRAM usage. Q5_K_S (183.5 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 73.8 GB.
VRAM requirement by quantization
IQ2_XXS73.8 GBQ2_K113.7 GBQ4_K_S150.3 GBQ4_K_M ★160.2 GBQ5_K_M190.2 GBBF16532.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Inkling Small on a Mac?
Inkling Small requires at least 73.8 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 Inkling Small locally?
Yes — Inkling Small can run locally on consumer hardware. At Q4_K_M quantization it needs 160.2 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Inkling Small?
At Q4_K_M, Inkling Small can reach ~30 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 ÷ 160.2 × 0.65 = ~33 tok/s
Estimated speed at Q4_K_M (160.2 GB)
~33 tok/s~33 tok/s~30 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Inkling Small?
At Q4_K_M, the download is about 159.57 GB. The full-precision BF16 version is 531.91 GB. The smallest option (IQ2_XXS) is 73.14 GB.
- Which GPUs can run Inkling Small?
No single consumer GPU has enough VRAM to run Inkling Small at Q4_K_M (160.2 GB). Multi-GPU or professional hardware is required.
- Which devices can run Inkling Small?
6 devices with unified memory can run Inkling Small at Q4_K_M (160.2 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.