Prices and claims are what each story reports; a company’s own benchmark stays a company claim. The claim check compares each maker’s main claim with an independent test that our story cites. Released models so far: 6 backed, 9 mixed, 12 not checked yet.

October 2026

  1. GoTo-AI-Gemma-3-27B-ITGoToReleasedOpen weightsCopy the link to this entry

    A 27-billion-parameter model on Google’s Gemma 3, made with AI Singapore, for Indonesian, English, Javanese, Sundanese, Balinese and Batak Toba. GoTo says it scored highest on regional languages in its own tests, with no scores published.

    Claim check: Not checked yet

    Price Free weights under the Gemma licence

    GoTo releases a free AI model for Indonesian and Javanese
  2. DeepSeek-V4.1-Flash-1017DeepSeekReleasedOpen weightsCopy the link to this entry

    A “minor update” to V4.1 Flash with open weights under the MIT licence and up to 1 million tokens of context. DeepSeek says it scores higher on coding and agent tests, works faster and writes shorter answers.

    Claim check: Not checked yet

    Price $0.30 / $1.20 per million input / output tokens (peak, unchanged)

    DeepSeek releases an open update of its V4.1 Flash model Try it yourself: who can use it, the price, an example prompt
  3. Muse Spark OpenMetaReleasedOpen weightsCopy the link to this entry

    Meta’s open-weight model: 816 billion parameters, about 42 billion active per token, and up to 1 million tokens of context. Meta calls it the most capable US open-weight model. Large API sellers need a separate agreement.

    Claim check: MixedArtificial Analysis gives it 39 points; Meta’s own table puts two Chinese open models ahead on coding tests.

    Meta releases Muse Spark Open, an 816B open-weight model Try it yourself: who can use it, the price, an example prompt
  4. Mistral Large 4Mistral AIPreviewOpen weightsCopy the link to this entry

    A model with 1 trillion parameters, 49 billion used per token, reading text and images. Public preview through Mistral’s API; Mistral says the weights follow by the end of October.

    Claim check: MixedArtificial Analysis scores the preview 38 on its Intelligence Index, 64th of 225 models: above the middle score of 26, but far from the leaders. Mistral’s cyber ranking is its own claim.

    Price $1.36 / $4.18 per million input / output tokens (preview)

    Mistral previews Large 4, a 1-trillion-parameter model
  5. BeamReflection AIPreviewOpen weightsCopy the link to this entry

    A text model with 501 billion parameters, 23 billion used per token, and up to 1 million tokens of context. Reflection says it matches GLM-5.2 on hard reasoning with 3–4× less computing; no outside test yet.

    Price Free weights (Apache 2.0) due later in October; early-access list for now

    Reflection unveils Beam, an open model to rival China’s labs
  6. Clef and Clef-flashCloudflareReleasedOpen weightsCopy the link to this entry

    Two decision models for AI agents (27B and 9B) that also read images, offered as an open rival to Jev. Cloudflare says a Clef model tops 7 of 10 decision tests; no outside test yet.

    Claim check: Not checked yet

    Price $0.24 / $0.09 per million input tokens on Workers AI; free weights (Apache 2.0)

    Cloudflare releases open Clef models to take on Jev
  7. Strands Decider 2BAmazon Web ServicesReleasedOpen weightsCopy the link to this entry

    A small decision model that picks one option from a fixed list for AI agents, as an open alternative to Jev. AWS says it takes about 115 ms on one graphics card; no outside test yet.

    Claim check: Not checked yet

    Price Free (Apache 2.0)

    Amazon releases a free, open rival to the Jev decision model

September 2026

  1. Open-1bGensynReleasedOpen weightsCopy the link to this entry

    A small model that publishes checkpoints, data, code and hashes for every training step, so its training can be replayed. About five times slower to run.

    Claim check: Not checked yet

    Gensyn made a small model whose training can be replayed
  2. MiniCPM5-2BOpenBMBReleasedOpen weightsCopy the link to this entry

    A 2.5-billion-parameter long-context model for local and on-device use; much of its training data is shared. OpenBMB says it leads open models of its size.

    Claim check: BackedArtificial Analysis gives it 15 points, the highest among open-weight models under four billion parameters.

    MiniCPM5-2B packs long-context AI into a much smaller model

How this tracker works

An entry appears when one of our stories covers a model launch, a preview, a reported plan, or a model becoming available on a new platform. A claim is Backed when an outside test supports it, Mixed when it holds only in part or only in some settings, and Disputed when an outside test contradicts it. The date is the one the story gives; when a story gives none, it is the story’s own date. We add entries with each edition and correct them under the story when a fact changes.

Reusing this list: you may quote it with a link to this page. Facts belong to the sources each story cites.