THInkling Small Open vs 
o1 Paid
Inkling Small vs o1 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$1.2 /M outputNo per-token fees if you self-host
$60 /M outputManaged API (no infra to run)
Inkling Small vs o1 specs
| Spec | Inkling Small | o1 | Winner |
|---|---|---|---|
| Maker | Thinkingmachines | OpenAI | – |
| Type | Open-weight | Proprietary | THInkling Small |
| Context window | 1M tokens | 200K tokens | THInkling Small |
| Input price | $0.45/M · free self-host | $15/M | THInkling Small |
| Output price | $1.2/M · free self-host | $60/M | THInkling Small |
| Vision / multimodal | Yes | Yes | = Tie |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | THInkling Small |
| License | Open weights | Proprietary | THInkling Small |
Price gap & when to choose each
Inkling Small is ~50× cheaper than o1 on output tokens ($1.2 vs $60 per M tokens).
- You want to self-host or run on your cloud
- You need the longer 1M context window
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Inkling Small | o1 |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: Inkling Small vs o1
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Inkling Small and o1 score
| Criterion | Inkling Small | o1 |
|---|---|---|
| Cost-efficiency | 4.5 | 2.0 |
| Context window | 5.0 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 5.0 |
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.
What each model is
Inkling Small Open
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...
o1 Paid
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Inkling Small as good as o1?
Inkling Small is open-weight and competitive on many tasks, but o1 may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run Inkling Small locally?
Yes. Inkling Small has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. o1 is API-only and cannot be self-hosted.
How much cheaper is Inkling Small?
Inkling Small costs $1.2/M output vs $60/M for o1 — roughly 50x cheaper via API, and free if you self-host.
Inkling Small vs o1 — which should I pick in 2026?
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 o1 if you want frontier capability through a managed API with zero infrastructure to run.
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