Amazon Nova Pro vs Inkling

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

Quick verdict

Pick Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20 or deep aws and bedrock integration for enterprise pipelines. 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 Pro if you want a managed API.

Amazon Nova Pro (Amazon) and Inkling (Thinking Machines Lab) are two of the models people most often weigh against each other in 2026. Amazon Nova Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. 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, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecAmazon Nova ProInkling
ProviderAmazon (US) Thinking Machines Lab (US)
ReleasedDecember 5, 2024 July 15, 2026
Context window300K (~450 pages) 1M (~1,500 pages)
Price (in/out)$0.8/$3.2 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, video, code text, image, audio, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Multimodal input across text, image and video at $0.80/$3.20

Amazon Nova Pro

Amazon Nova Pro lists multimodal input across text, image and video at $0.80/$3.20 among its strengths; Inkling does not.

Deep AWS and Bedrock integration for enterprise pipelines

Amazon Nova Pro

Amazon Nova Pro lists deep AWS and Bedrock integration for enterprise pipelines among its strengths; Inkling does not.

Balanced cost-to-capability for general business tasks

Amazon Nova Pro

Amazon Nova Pro lists balanced cost-to-capability for general business tasks 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 Pro 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 Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships

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 it carries the larger 1M context.

Lowest cost at scale

Inkling

Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.

Largest single-prompt input

Inkling

Its 1M window is about 3.3× larger than Amazon Nova Pro's 300K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Inkling

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

Someone analysing very long documents or codebases

Inkling

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

Inkling

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

Anyone whose priority is multimodal input across text, image and video at $0.80/$3.20

Amazon Nova Pro

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 Pro: where it fits

Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. Released December 5, 2024 by Amazon, it is built for multimodal input across text, image and video at $0.80/$3.20, deep AWS and Bedrock integration for enterprise pipelines, balanced cost-to-capability for general business tasks, and a 300K context for long documents and mixed media.

Its trade-offs are real: not a frontier reasoning or coding model against 2026 flagships, no published SWE-Bench Verified score, best value is realised inside the AWS ecosystem, and late-2024 model — older than most of the field here. At $0.8 in / $3.2 out per million tokens, it sits in the budget 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 Pro 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 Pro 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 Pro 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 Pro leans toward multimodal input across text, image and video at $0.80/$3.20 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 Pro or Inkling?

Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Amazon Nova Pro is API-metered at $0.8/$3.2 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?

Inkling — 1M vs 300K, about 3.3× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Amazon Nova Pro and Inkling together?

Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, 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 Pro or Inkling?

Inkling — released July 15, 2026, about 20 months after Amazon Nova Pro.

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.