Inkling vs Qwen 3.7 Plus

Thinking Machines Lab · US  |  Alibaba · China · Updated June 2026

Quick verdict

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. Pick Qwen 3.7 Plus for reading screens and interacting with guis or generating code from visual references. Choose Inkling if you need self-hosting or data privacy; Qwen 3.7 Plus if you want a managed API.

Inkling (Thinking Machines Lab, US) and Qwen 3.7 Plus (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Qwen 3.7 Plus is alibaba's cost-effective multimodal agent in the Qwen3.7 series, built to perceive scenes, read screens and GUIs, generate code from visual references, and navigate mobile apps end-to-end. 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

SpecInklingQwen 3.7 Plus
ProviderThinking Machines Lab (US) Alibaba (China)
ReleasedJuly 15, 2026 June 1, 2026
Context window1M (~1,500 pages) 1M (~1,500 pages)
Price (in/out)Open weight (self-host / free) $0.4/$1.6 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, image, audio, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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 — Qwen 3.7 Plus 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

Qwen 3.7 Plus is comparatively weak here — outputs text only, no image, audio, or video generation

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 Qwen 3.7 Plus is API-only.

Reading screens and interacting with GUIs

Qwen 3.7 Plus

Qwen 3.7 Plus lists reading screens and interacting with GUIs among its strengths; Inkling does not.

Generating code from visual references

Qwen 3.7 Plus

Qwen 3.7 Plus lists generating code from visual references among its strengths; Inkling does not.

Agentic tool use, verification, and autonomous iteration

Qwen 3.7 Plus

Inkling is comparatively weak here — independent third-party benchmark verification is still limited given how recently it shipped

Lowest cost at scale

Inkling

Its weights are open, so at volume you pay for your own hardware instead of Qwen 3.7 Plus's $0.4/$1.6 per 1M tokens.

Which should you pick?

A cost-sensitive startup shipping high volume

Inkling

At Open weight (self-host / free) it undercuts Qwen 3.7 Plus, 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; Qwen 3.7 Plus is API-only.

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

It is specifically built for that.

Anyone whose priority is reading screens and interacting with guis

Qwen 3.7 Plus

That is its strongest area.

An enterprise with regional data-residency rules

Inkling or Qwen 3.7 Plus

Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

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 are real: 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.

Qwen 3.7 Plus: where it fits

Alibaba's cost-effective multimodal agent in the Qwen3.7 series, built to perceive scenes, read screens and GUIs, generate code from visual references, and navigate mobile apps end-to-end. Released June 1, 2026 by Alibaba, it is built for reading screens and interacting with GUIs, generating code from visual references, agentic tool use, verification, and autonomous iteration, and cost-effective vision-language processing at 1M context.

Its trade-offs: proprietary and API-only, with no downloadable weights, and outputs text only, no image, audio, or video generation. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.

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. Qwen 3.7 Plus 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 Inkling and Qwen 3.7 Plus 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 Inkling or Qwen 3.7 Plus 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, 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 while Qwen 3.7 Plus leans toward reading screens and interacting with guis, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Inkling or Qwen 3.7 Plus?

Inkling is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Plus is API-metered at $0.4/$1.6 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 Inkling and Qwen 3.7 Plus together?

Yes — a multi-model platform like LumiChats gives you Inkling, Qwen 3.7 Plus 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, Inkling or Qwen 3.7 Plus?

Inkling — released July 15, 2026, about 44 days after Qwen 3.7 Plus.

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.