Amazon Nova Premier vs Inkling

Amazon · US  |  Thinking Machines Lab · US · Updated June 2026

Quick verdict

Pick Amazon Nova Premier for 1m-token context with deep aws bedrock integration or amazon's most capable nova model, positioned as a 'teacher' for distilling smaller models. Pick Inkling for the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai or a 975b-parameter moe (41b active) with native text, image, and audio reasoning in one model. Choose Inkling if you need self-hosting or data privacy; Amazon Nova Premier if you want a managed API.

Amazon Nova Premier (Amazon) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. Amazon Nova Premier is amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. Inkling is mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecAmazon Nova PremierInkling
ProviderAmazon (US) Thinking Machines Lab (US)
ReleasedApril 30, 2025 July 15, 2026
Context window1M (~1,500 pages) 1M (~1,500 pages)
Price (in/out)$2.5/$12.5 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image text, image, audio, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

1M-token context with deep AWS Bedrock integration

Amazon Nova Premier

Amazon Nova Premier lists 1M-token context with deep AWS Bedrock integration among its strengths; Inkling does not.

Amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models

Amazon Nova Premier

Amazon Nova Premier lists amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models among its strengths; Inkling does not.

A natural fit for teams already building on AWS

Amazon Nova Premier

Amazon Nova Premier lists a natural fit for teams already building on AWS among its strengths; Inkling does not.

The first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI

Inkling

Open weights make this possible at all — Amazon Nova Premier is API-only, so it cannot leave the vendor's servers.

A 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model

Inkling

Amazon Nova Premier is comparatively weak here — a 2025 model - older than the 2026 frontier it competes against

A dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request

Inkling

Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control — and its weights are open while Amazon Nova Premier is API-only.

Lowest cost at scale

Inkling

Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Premier's $2.5/$12.5 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

Inkling

At Open weight (self-host / free) it undercuts Amazon Nova Premier, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

Inkling

Open weights let you run it on your own hardware; Amazon Nova Premier is API-only.

Anyone whose priority is 1m-token context with deep aws bedrock integration

Amazon Nova Premier

It is specifically built for that.

Anyone whose priority is the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai

Inkling

That is its strongest area.

Amazon Nova Premier: where it fits

Amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. Released April 30, 2025 by Amazon, it is built for 1M-token context with deep AWS Bedrock integration, amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models, a natural fit for teams already building on AWS, and multimodal input for complex reasoning across text and images.

Its trade-offs are real: weak on independent intelligence - Artificial Analysis Intelligence Index of 13, below average for its tier, expensive for its score at $2.50/$12.50 per million tokens, a 2025 model - older than the 2026 frontier it competes against, and sources disagree on modalities (Amazon cites image input; some evaluations list text-only). At $2.5 in / $12.5 out per million tokens, it sits in the mid price band.

Inkling: where it fits

Mira Murati's Thinking Machines Lab debuts with Inkling - a 975B open-weight MoE with native multimodal reasoning and a dialable thinking-effort control. Released July 15, 2026 by Thinking Machines Lab, it is built for the first model release from Mira Murati's Thinking Machines Lab (ex-OpenAI CTO) - one of the most closely-watched new labs in AI, a 975B-parameter MoE (41B active) with native text, image, and audio reasoning in one model, a dialable 'thinking effort' knob (0.2-0.99) that lets you trade speed for depth of reasoning per-request, and fully open weights (Apache 2.0) at frontier scale - unusual for a model this large and this new.

Its trade-offs: a brand-new lab's first release - no multi-generation track record yet, no official hosted API price - available via third-party hosts only at launch, and independent third-party benchmark verification is still limited given how recently it shipped. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

The defining split here is open vs. closed. Inkling gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Amazon Nova Premier gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Amazon Nova Premier and Inkling without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Amazon Nova Premier or Inkling better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration while Inkling leans toward the first model release from mira murati's thinking machines lab (ex-openai cto) - one of the most closely-watched new labs in ai, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Amazon Nova Premier or Inkling?

Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Amazon Nova Premier is API-metered at $2.5/$12.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Amazon Nova Premier and Inkling together?

Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, Inkling and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Amazon Nova Premier or Inkling?

Inkling — released July 15, 2026, about 15 months after Amazon Nova Premier.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.