Active Parameters
276B
Context Length
1.05M
Modality
Multimodal
Architecture
Mixture of Experts (MoE)
License
Apache 2.0
Release Date
30 Jul 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.30 · Output: $1.20
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
29x RTX 4090
24GB VRAM
Datacenter
8x NVIDIA A100
80GB VRAM
Apple Silicon
6x Apple M3 Max
128GB VRAM
1,048,576 tokens
Consumer
40x RTX 4090
24GB VRAM
Datacenter
11x NVIDIA A100
80GB VRAM
Apple Silicon
8x Apple M3 Max
128GB VRAM
Rank
#128
| Benchmark | Score | Rank |
|---|---|---|
Graduate-Level QA | 0.895 | 26 |
Agent Arena | -16.14 | 65 |
Agentic Index | 0.23 | 73 |
Web Development | 1409 | 78 |
Coding Index | 0.53 | 80 |
General Text | 1405 | 116 |
Intelligence Index | 0.13 | 229 |
Overall Rank
#128
Coding Rank
#104
Inkling-Small is an open-weights 276B Mixture-of-Experts (MoE) multimodal foundation model with 12B active parameters per token developed by Thinking Machine Labs. Trained on 45T multimodal tokens, it supports text, image, and native audio inputs with up to a 1M token context window, variable thinking effort, and sliding-window attention. It achieves near-parity and on certain benchmarks outperforms the 975B flagship Inkling at substantially lower inference latency and footprint.
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Relative Position Embedding
Sliding Window Attention
Yes
Sliding Window Size
512
Sliding Window Ratio
83.3%
Normalization
RMS Normalization
Dimensions
Hidden Dimension Size
4,096
Number of Layers
42
Tokenizer
Vocabulary Size
201,024
Mixture of Experts
Total Expert Parameters
12.0B
Number of Experts
128
Active Experts
6
Shared Experts
2
FFN Intermediate Size (per Expert)
2,048
Inkling is a family of open-weights multimodal Mixture-of-Experts (MoE) models developed by Thinking Machine Labs.
Assistant
Online