Inkling 2 Small on Tinker Today: 594B/17B MoE, AA Index 31, Apache Weights Next Week

Attributed compile + offline HTTP preflight on my box

Primary source: Introducing Inkling 2 Small (Nov 5, 2026) + Inkling 2 Small model card by Thinking Machines Lab.

Access / pricing: Tinker Pricing (page stamp “as of October 19, 2026”); Tinker models & pricing docs (model id thinkingmachines/Inkling-2-Small); Tinker Playground (redirects to auth — no login on this box); tinker-cookbook.

Release policy: A Safe Path to Open Weights (Jul 31, 2026).

Independent index scrape: Artificial Analysis — Inkling 2 Small (intelligenceIndex ≈ 30.63, isOpenWeights: false in our HTML/JSON scrape).

Secondary only: The Decoder (AA 31 vs predecessor Inkling Small 13); MarkTechPost URL intermittently Cloudflare-challenged — unused for numbers. Local copies: /workspace/reputation/runs/36-inkling-2-small/.

Numbers below from the announcement, model card, Tinker pricing/docs, or AA scrape are vendor / dashboard unless marked otherwise. This box did not authenticate to Tinker, call sampling/fine-tune APIs, or download weights. Offline preflight = public HTTP scrapes only.

Thinking Machines Lab’s second generation landed on 2026-11-05 as Inkling 2 Small: a multimodal MoE you can poke on Tinker today, with closed weights at launch and a company line that full Apache 2.0 weights should follow next week after external safety testing and red-teaming. For builders who care about agent loops, fine-tune surfaces, and “when do I self-host?”, that is a sharper decision than another Daybreak-gated cyber demo. The useful checklist is: what actually shipped, how you reach it on Tinker (and what it costs), what the Apache cliff is promising vs guaranteeing, how to read the short vendor/AA score map, and when to wait for downloadable weights instead of burning playground tokens.

What shipped (card + announcement)

Label these as vendor card / announcement:

Training color from the announcement (still vendor narrative, not our run): long pretrain on GB300 NVL72 in native NVFP4, then a single joint RL run (~1,075 steps, 17M+ rollouts, 2,048 GPUs, 9 days) mixing coding, knowledge work, vision, tool use, and safety. Early coding checkpoints were tested on OpenCode under the name Fledge-Alpha — useful signal that the lab optimized for real agent harnesses, not only unit-test rewards.

Access matrix (what this box actually opened)

Practical pin strings from Tinker docs (as scraped):

thinkingmachines/Inkling-2-Small thinkingmachines/Inkling-2-Small:peft:262144 # 256K context row 

Cookbook path named on the card: thinking-machines-lab/tinker-cookbook plus the tml-renderers package for render-related workflows. Checkpoints from Tinker fine-tunes are described as downloadable when the base weights ship.

Tinker economics (hosted now)

Prefer the pricing page + docs over aggregators. Training & sampling table (USD per 1M tokens, page dated October 19, 2026):

Serverless inference beta (same page; Inkling family only): Inkling 2 Small 256K at $0.30 input / $0.03 cached input / $1.00 output per 1M tokens. Storage: $0.10 / GB / month for checkpoints. MoE note on the page: priced by active parameters, not total size — which is why a 594B/17B active model can sit near the Inkling-Small dollar band on sample rates.

For agent loops, cached prefill at $0.03 vs $0.30 is the real budget knob once you keep long tool transcripts warm. We did not measure cache hit rates or tok/s here.

The Apache cliff (intent, not a receipt)

Announcement wording, paraphrased: Inkling 2 Small starts on Tinker with closed weights, following the lab’s safe path to open weights staging story (API / hosted fine-tune before irreversible public weights). They intend to release full weights under Apache 2.0 next week after external safety testing and red-teaming.

Treat that as company intent dated Nov 5, not a calendar we verified. Re-check next week: Hugging Face (or wherever they post), license file literally saying Apache-2.0, whether LoRA/full checkpoints from Tinker become portable, and whether OpenRouter / third-party hosts appear. Until then, “open-weights MoE” headlines are premature — AA’s scrape still had isOpenWeights: false / proprietary categorization on 2026-11-06.

Short score map (vendor + AA — not our eval)

Announcement prose claims an Artificial Analysis Intelligence Index score of 31 (vs prior Inkling models). The same post’s comparison matrix lists AA Index (v5.0) = 30.6. Our AA.com scrape for inkling-2-small showed intelligenceIndex ≈ 30.63. The Decoder (secondary) frames that as 31 vs Inkling Small 13 — cite only as aggregator color; we did not independently resolve the predecessor’s AA page in this preflight.

Tiny coding slice from the vendor announcement table (effort 0.99 / temperature 1.0 / 1M trajectory limit — their harness, not ours):

Do not treat that matrix as a certificate. Use it to shortlist tasks for your golden eval once playground or API access is real. We invent no independent coding scores and we did not re-run any row.

Limitations they state (read before you demos)

Vendor limitations section, compressed: still not the most succinct communicator; can pick suboptimal tools in skill-heavy repos; no audio; chat UX is weaker (organization/presentation, slash overuse); can overreact on mental-health / safety-adjacent queries. Card also lists ordinary foundation-model risks (hallucination, uneven multilingual/domain coverage, cutoff). If your product is a polished consumer chat, assume extra formatting and refusal tuning work — even when coding-agent demos look strong.

Builder decision: Tinker now vs wait for Apache

Try Tinker now if you need agentic coding / vision-in-the-loop prototypes this week, want LoRA / custom RL on their stack before weights exist elsewhere, or you’re validating whether Fledge-Alpha-class behavior helps your OpenCode / harness loop. Pin thinkingmachines/Inkling-2-Small (or the :peft:262144 256K id), keep effort explicit, and budget cached-prefill math on long rollouts.

Wait for Apache weights if you need air-gap, weight-level inspection, non-Tinker serving, or license certainty before a production bet. “Next week” is the intent; verify the artifact + Apache text before you plan a cluster. Self-host hardware for a 594B MoE (even at 17B active) will still be a data-center story — this preflight did not find a consumer GGUF path because weights are not public yet.

Skip theater if you only wanted OpenRouter one-liner access today: our models API snapshot had prior Inkling ids, not Inkling 2 Small. Prefer Tinker until third-party routes appear.

What this box actually did

preflight 2026-11-06 ~09:22–09:28 America/Toronto NO TINKER KEY / NO CHAT COMPLETION / NO WEIGHT DOWNLOAD HTTP 200: announcement, model card, safe-path blog, tinker home, tinker pricing, tinker docs models markdown, inkling product page, AA models/search scrape + AA /models/inkling-2-small (retry), OpenRouter /api/v1/models, The Decoder article, tinker-cookbook GH HTTP 302→auth: tinker.thinkingmachines.ai/playground HTTP 403 / Cloudflare challenge: MarkTechPost (first); UA path flaky — unused for numbers HTTP 404: thinkingmachines.ai/news/a-safe-path-to-open-weights/ ; thinkingmachines.ai/tinker/playground/ Parsed: 594B/17B; AA vendor 31 / matrix 30.6 / AA.com ~30.63; model id thinkingmachines/Inkling-2-Small; Tinker $0.30/$0.03/$1.00 sample @64K; Apache “next week” intent; OR missing inkling-2 NOT tested: playground chat; fine-tune; serverless inference; weight download; golden eval; latency/tok-s 

Inkling 2 Small is a real Tinker-day release for agent builders: 594B/17B MoE, text+image, variable effort, up to 1M context on the card, hosted fine-tune/sampling priced today, and an Apache 2.0 next week intent that still needs a receipt. For most Toronto product teams on 2026-11-06, the rational move is playground + pin the model id + run your harness, treat AA ~31 as orientation not proof, and put a calendar reminder on the weight drop — not a cluster PO until the Apache file exists.

YongBo Yu — Toronto AI engineer (agent systems / LLM workflows). Site: yongbo-yu.vercel.app · GitHub: YongBoYu1