Research · Head-to-head

Inkling-Small vs Elicit

Inkling-Small (free, AI Score 8.8/10) vs Elicit (freemium, AI Score 8.6/10). Side-by-side pricing, features, pros and cons, and which to pick.

The verdict

Pick Inkling-Small if…

Try Inkling-Small →

Pick Elicit if…

→your primary use case is academic and scientific researchers who need literature review findings extracted and synthesized instead of read paper by paper.
→you need: research

Try Elicit →

Spec	Inkling-Small	Elicit
Category	Research	Research
Pricing model	free	freemium
Headline pricing	Free — open weights download; Tinker Playground access	Freemium
Free tier	Yes — the weights themselves are free to download and run. Compute is the real cost.	5,000 credits per month for basic searches
AI Score	8.8/10	8.6/10
Best for	—	Academic and scientific researchers who need literature review findings extracted and synthesized instead of read paper by paper.
Editor's pick	✓ Yes	—
Use cases	—	research
Date added	2026-07-31	2025-08-01

Research · free

✓Open weights on Hugging Face, so it can run fully offline for sensitive audio, documents, or code
✓12B active parameters keeps per-token inference cost near a mid-size dense model despite the 276B total
✓Audio and vision are native to the model rather than a separate encoder stage
✓1M-token context handles whole codebases or long document sets in one pass
✓Hosted Tinker Playground path for teams that want to evaluate before committing hardware

×"Free weights" is misleading on cost — serving 276B parameters requires enough VRAM to put local deployment out of reach for individuals and small teams
×The claim that it outperforms the larger Inkling comes from the lab's own launch benchmarks; independent third-party evaluations aren't in yet
×Released July 30, 2026, so tooling, quantizations, and community fine-tunes are still thin compared to established open-weights families
×It's a raw model, not a product — no chat app, no agent harness, no support contract unless you build or buy one