Inkling Small vs Perceptron Mk1 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Perceptron Mk1 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
| Spec | Inkling Small | Perceptron Mk1 | Winner |
|---|---|---|---|
| Maker | Thinkingmachines | Perceptron | – |
| Type | Open-weight | Proprietary | THInkling Small |
| Context window | 1M tokens | 33K tokens | THInkling Small |
| Input price | $0.45/M · free self-host | $0.15/M | PEPerceptron Mk1 |
| Output price | $1.2/M · free self-host | $1.5/M | THInkling Small |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | No | THInkling Small |
| Self-hostable | Yes | No (API only) | THInkling Small |
| License | Open weights | Proprietary | THInkling Small |
| Capability | Inkling Small | Perceptron Mk1 |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✗ |
| 1M+ context window | ✓ | ✗ |
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
| Criterion | Inkling Small | Perceptron Mk1 |
|---|---|---|
| Cost-efficiency | 4.5 | 4.5 |
| Context window | 5.0 | 2.5 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 3.5 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of...
Perceptron Mk1 (Mark One) is Perceptron's highest-quality vision-language model for video and embodied reasoning.** It accepts image and video inputs paired with natural language queries, and produces detailed visual understanding...
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Inkling Small is open-weight and competitive on many tasks, but Perceptron Mk1 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Yes. Inkling Small has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Perceptron Mk1 is API-only and cannot be self-hosted.
Choose Inkling Small if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Perceptron Mk1 if you want frontier capability through a managed API with zero infrastructure to run.
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