Thinking Machines Puts Inkling 2 Small on Tinker as a 594B MoE and Says Apache Weights Come After Safety Tests
Thinking Machines Lab on November 5 introduced Inkling 2 Small, a multimodal mixture-of-experts model with 594 billion total parameters and 17 billion active, supporting image inputs and variable effort. It is available now on Tinker with closed weights for inference and fine-tuning. The lab says it intends to release the full weights under an Apache 2.0 license next week after external safety testing and red-teaming. It claims an Artificial Analysis Intelligence Index score of 31; its own comparison table lists AA Index v5.0 at 30.6. Those scores are lab-reported.
Thinking Machines is again trying to walk the path from a closed fine-tuning API to downloadable weights — this time at a larger MoE and with an explicit safety gate in between. On November 5 the lab introduced Inkling 2 Small, a multimodal mixture-of-experts model with 594 billion total parameters and 17 billion active, image inputs and variable effort. That is a jump from Inkling-Small, the 276 billion / 12 billion-active open MoE it released in July, and a different shape from the original 975 billion / 41 billion-active Inkling.
The new model is available now on Tinker for inference and fine-tuning, with closed weights. Thinking Machines says it intends to make the full weights available under an Apache 2.0 license next week, after external safety testing and red-teaming, following what it calls a safe path to open weights. Checkpoints will be downloadable when those weights are released, the post says.
What the lab claims#
Thinking Machines says Inkling 2 Small "far surpasses" its previous models on the Artificial Analysis Intelligence Index, citing a score of 31. Its own comparison table lists AA Index v5.0 at 30.6. Evaluations in the post were run at effort 0.99 ("xhigh") and temperature 1.0, with a 1 million-token maximum trajectory limit, up from the 256,000-token limit used for Inkling Small. We have not re-run those evaluations.
On the training side, the lab says the first pre-training phase covered 8.4 trillion tokens and ran for 68 hours on NVIDIA GB300 NVL72 racks, natively in NVFP4. A later joint reinforcement-learning run lasted 1,075 steps and more than 17 million rollouts over nine days on 2,048 GPUs, which the lab contrasts with separate reasoning and agentic RL runs on the previous Inkling. It describes a vision encoder of 292 million parameters based on Perception Encoder, and says the model does not support audio.
Safety numbers in the post are the lab's. It says Inkling 2 Small's chemical, biological, radiological and nuclear knowledge and capability scores sit below the open-weight frontier, and that a helpful-only variant did not significantly advance that frontier on the dimensions it measured. We are not reproducing evaluation methods or assistance detail.
Limits#
- Intelligence-index and benchmark figures are Thinking Machines' citations of third-party boards or its own tables; we have not independently reproduced them.
- The prose claim of an AA Index score of 31 does not match the 30.6 listed in the lab's AA Index v5.0 table.
- Apache 2.0 weights are an intention timed to "next week" after safety testing, not a release that has already happened.
- CBRN and cyber comparisons are the vendor's; they are not an independent safety board result.
- Pricing, rate limits and Tinker capacity terms are not specified in the announcement we read.