# Thinking Machines Nears $5 Billion Round at $40 Billion Valuation

- URL: https://usa-24.com/thinking-machines-lab-funding-round/
- Publisher: USA 24
- Section: Artificial Intelligence (AI)
- Published: 2026-11-07T11:49:12.281Z
- Updated: 2026-11-07T11:49:12.287Z
- Topics: AI Funding, Thinking Machines Lab, Mira Murati, Nvidia, Open-Weight Models

> Mira Murati's Thinking Machines Lab is reportedly closing a $5 billion round led by Accel, with Nvidia among the backers, as it ships a new open-weight model.

## Key takeaways

- Business Insider reported that Thinking Machines Lab is closing a $5 billion round led by Accel at a $40 billion pre-money valuation, though the deal has not been announced.
- The reported pre-money price is more than triple the roughly $12 billion valuation from the company's $2 billion seed round in July 2025.
- Nvidia is reported to be in talks to invest about $2.5 billion, and the two companies already agreed in March to deploy at least one gigawatt of Vera Rubin systems.
- Inkling 2 Small, a 594-billion-parameter mixture-of-experts model, launched on November 5, and the company says it will publish the weights under Apache 2.0 next week.
- Benchmark results for Inkling 2 Small are mixed, with one report saying it beat Claude Sonnet 5.5 on one test and trailed it on another while using substantially more tokens.

The Thinking Machines Lab funding round is nearing its close, with Mira Murati's startup reportedly raising $5 billion at a $40 billion pre-money valuation and Nvidia among the investors. [Business Insider reported the deal on November 6](https://dnyuz.com/2026/11/06/thinking-machines-lab-is-closing-in-on-a-new-5-billion-funding-round-at-a-40-billion-valuation/), saying it could close as soon as this week. Nothing has been announced. The company declined to comment, and Accel did not respond to requests for comment.

The timing is hard to ignore. The same week, Thinking Machines released Inkling 2 Small, a 594-billion-parameter open-weight model, and said it will publish the weights under the Apache 2.0 license next week. Investors are reportedly prepared to pay more than triple the company's last known valuation, even after a recent AI stock selloff.

## Thinking Machines Lab funding round at a $40 billion valuation

Business Insider's reporting puts the round at $5 billion, led by Accel, at a $40 billion pre-money valuation. If the deal closes on those terms, the post-money valuation would be about $45 billion, according to [AI Weekly's roundup of the report](https://aiweekly.co/alerts/thinking-machines-lab-raising-5b-led-by-accel-at-40b-pre-money-tripling-last). That is a steep climb from the company's last public round. In July 2025, Thinking Machines raised a $2 billion seed round at about $12 billion, led by Andreessen Horowitz, according to [the company's Wikipedia entry](https://en.wikipedia.org/wiki/Thinking_Machines_Lab).

The pre-money figure is about 3.3 times the seed valuation, which is why the story is drawing attention from investors. Business Insider also reported that the company abandoned talks last year to raise at a $50 billion valuation. The price has moved up and down in a short period, and the latest figure is the one that matters most to current backers.

The round has also grown in size. In September, The Information reported that Thinking Machines was seeking about $1 billion. It later updated that figure to $5 billion to $6 billion, [according to TheNextWeb's summary of the report](https://thenextweb.com/news/thinking-machines-lab-6bn-round-nvidia-accel). Readers who saw the earlier number should treat it as outdated.

## How Nvidia fits into the deal

Nvidia's role carries the most money. Business Insider reported that Nvidia is in talks to invest about $2.5 billion. The Information's earlier reporting said Nvidia would supply about half of the $5 billion to $6 billion round, which would put its share at roughly $2.5 billion to $3 billion. The figures point in the same direction, but they are still reports, not company disclosures.

The two companies already have a longer relationship. In March, Thinking Machines and Nvidia announced a multiyear partnership to deploy at least one gigawatt of Nvidia Vera Rubin systems, with first deployment targeted for early 2027. Nvidia invested at the same time, but neither side disclosed the amount.

That arrangement ties a large share of Nvidia's future chip sales to one lab's growth. For chip buyers, it shows how frontier labs and their hardware suppliers are becoming bound together. Nvidia's dealings with AI companies have also drawn attention in Washington. Lawmakers recently asked Nvidia CEO [Jensen Huang to brief them on the company's ties to Megaspeed](https://usa-24.com/jensen-huang-megaspeed-congress-briefing/).

## Inkling 2 Small: what the new model is

Thinking Machines launched Inkling 2 Small on November 5. It is a mixture-of-experts model with 594 billion total parameters and 17 billion active, built for autonomous coding, visual reasoning and knowledge work. The company makes it available through its Tinker platform.

The model follows Inkling, a larger open-weight family the company released in July 2026 with 975 billion parameters under Apache 2.0. The company then released a distilled Inkling Small on July 31. Inkling 2 Small is the newest step in that line.

The benchmark picture is mixed. One report, [from Techstrong.ai](https://techstrong.ai/articles/thinking-machines-launches-inkling-2-small/), says Inkling 2 Small beat Claude Sonnet 5.5 on one test, trailed it on another, and used substantially more tokens. The same coverage cites one analysis finding that the model generated roughly four times as many output tokens as a rival model. USA 24 did not independently verify those results, so treat them as a starting point for your own testing.

## Why the valuation matters beyond the lab

For investors, the reported price signals that private AI valuations are still climbing even as public AI stocks have stumbled. [AI Weekly's daily roundup](https://aiweekly.co/ai-news-today/edition/2026-11-06) placed the Business Insider report alongside an AI stock selloff and a midterm-election backlash against data centers. Those market details come from that roundup and were not verified in this reporting. Still, the contrast is the story: late-stage investors appear willing to pay up while public markets reprice.

That matters for people who do not own lab shares directly. Retirement accounts and funds with private AI exposure can carry these marks, and private rounds often set the values those funds report. USA 24 has also reported that [Anthropic's $1.5 trillion IPO faces valuation pushback after an AI rout](https://usa-24.com/anthropic-ipo-valuation-doubt/). Read together, the two stories show how far opinions differ on what AI companies are worth.

The talent picture complicates the valuation story. Business Insider reported in May that about one-third of the founding team had left for rivals, and the company has lost people to Meta and OpenAI. A high valuation buys compute and hiring power, but it also raises the bar for what the company has to deliver.

## What the numbers still don't settle

Several questions remain open. The round has not been announced as closed. Sources describe it as 'set to close,' and Thinking Machines declined to comment.

Nvidia's share is also unsettled. Business Insider's $2.5 billion figure and The Information's earlier estimate of about half of a $5 billion to $6 billion round point in the same direction. Neither has been confirmed by the company.

The final terms could also differ from the early reports. The $1 billion figure from September circulated widely before The Information updated it, which is a reminder that early numbers in this market often shift.

## What developers should check before using Inkling 2 Small

Consumers have no action to take here. Developers and companies that evaluate open-weight models have a few concrete steps.

1. Wait for the weights and read the license. The company says it will publish them under Apache 2.0 next week, so confirm the released license text matches that claim before you build on it.
2. Compare cost per completed task, not the listed price per token. The token-usage findings suggest a model can cost more overall if it writes much longer outputs.
3. Run your own evaluations. Benchmark results have been mixed, so test coding and reasoning tasks on your own data.
4. Plan the hardware. A 594-billion-parameter model needs memory for all of its weights, even though only 17 billion parameters are active for each token, so self-hosting is a serious infrastructure decision.

## What to watch next

Three events will show whether the story holds. The first is a formal announcement of the round, including the investor list and Nvidia's actual check. The second is the promised release of Inkling 2 Small weights under Apache 2.0, which will let outside researchers test the benchmark claims. The third is the Nvidia compute deal, with first Vera Rubin deployment targeted for early 2027.

If the round closes near $5 billion at a $40 billion pre-money valuation, it will reinforce a pattern in which the largest AI labs raise at prices far above their last rounds. The harder test is whether investor appetite for frontier labs survives the next AI stock selloff.

## Frequently asked questions

### Has the Thinking Machines Lab funding round closed?

Not as of the latest reporting. Business Insider said the $5 billion round, led by Accel at a $40 billion pre-money valuation, could close as soon as the week of November 6, but the company has not announced a close. Thinking Machines declined to comment, and Accel did not respond to requests for comment.

### How much is Nvidia investing in Thinking Machines Lab?

Business Insider reported that Nvidia is in talks to invest about $2.5 billion. An earlier report from The Information said Nvidia would supply about half of a $5 billion to $6 billion round. Neither figure has been confirmed by the company.

### What is Inkling 2 Small?

Inkling 2 Small is a mixture-of-experts model from Thinking Machines Lab, released November 5, 2026. It has 594 billion total parameters, with 17 billion active, and is built for autonomous coding, visual reasoning and knowledge work. The company says it will publish the weights under the Apache 2.0 license next week.

### Is Inkling 2 Small better than Claude Sonnet 5.5?

Results depend on the test. One report says Inkling 2 Small beat Claude Sonnet 5.5 on one benchmark and trailed it on another, while also using substantially more tokens. USA 24 did not independently verify those results, so developers should run their own evaluations.

## Sources

1. [Thinking Machines Lab is closing in on a new $5 billion funding round at a $40 billion valuation (Business Insider, repost on Dnyuz)](https://dnyuz.com/2026/11/06/thinking-machines-lab-is-closing-in-on-a-new-5-billion-funding-round-at-a-40-billion-valuation/)
2. [Thinking Machines Lab Raising $5B Led by Accel at $40B Pre-Money, Tripling Last Year's Valuation (AI Weekly)](https://aiweekly.co/alerts/thinking-machines-lab-raising-5b-led-by-accel-at-40b-pre-money-tripling-last)
3. [AI News for November 6, 2026 — Daily Edition (AI Weekly)](https://aiweekly.co/ai-news-today/edition/2026-11-06)
4. [Thinking Machines Launches Inkling 2 Small as Reported $5B Funding Round Nears (Techstrong.ai)](https://techstrong.ai/articles/thinking-machines-launches-inkling-2-small/)
5. [Thinking Machines Lab Unveils Inkling 2 Small as It Reportedly Nears a $5B Round (WOWTALE)](https://en.wowtale.net/2026/11/07/235890/)
6. [Thinking Machines is in talks to raise $6bn, The Information reports (TheNextWeb)](https://thenextweb.com/news/thinking-machines-lab-6bn-round-nvidia-accel)
7. [Thinking Machines Nears $5B Raise at $40B, 3.3x Its Seed (FourWeekMBA)](https://fourweekmba.com/ai-thinking-machines-nears-5b-raise-at-40b-3-3x-its-seed/)
8. [Thinking Machines Lab (Wikipedia)](https://en.wikipedia.org/wiki/Thinking_Machines_Lab)