Inkling
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,...
Updated 4 h ago · first seen 11 Sept 2026
model_01M294WVTGRQG13Q8WGWXSATQB
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- 1 quantization0 official · 1 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- inklingthinkingmachines/inklingIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 1Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
Architecture
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
Capabilities
Modalities
- Modalities
- audioimagetext
- Input
- audioimagetext
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Yes
OpenRouter public model & pricing listing · T2
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 4 h agomedium
Benchmarks22
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 22 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing4
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 2 providers
- OpenRouter
- Together AI
- OpenRouter$0 → $4.0512 Sept 2026
- Together AIfirst observed $4.0511 Sept 2026
- OpenRouter$4.05 → $011 Sept 2026
- OpenRouterfirst observed $4.0511 Sept 2026
Input price · USD / 1M tokens 2 providers
- OpenRouter
- Together AI
- OpenRouter$0 → $112 Sept 2026
- Together AIfirst observed $111 Sept 2026
- OpenRouter$1 → $011 Sept 2026
- OpenRouterfirst observed $111 Sept 2026
Lineage
Open in Graph →Versions & Artifacts1
Version history
Context window2 changes
11 Sept 2026→11 Sept 2026→12 Sept 2026current
Max output1 change
11 Sept 2026→12 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 1
quantization 1
- unsloth/inkling-GGUFUnsloth · GGUF—
Timeline10
Full timeline →OpenRouter changed pricing for Inkling: $1 in / $4.05 out per 1M tokens → $1 in / $4.05 out per 1M tokens
$1 in / $4.05 out→$1 in / $4.05 outopenrouterInkling: max output tokens changed from 32768 to 471859
Max output32.8K tokens→471.9K tokensopenrouterInkling scores 55.06% on Terminal-Bench
artificial_analysisInkling scores 1.01% on Terminal-Bench
artificial_analysisInkling scores 31.88% on Humanity's Last Exam
artificial_analysisInkling scores 87.17% on GPQA Diamond
artificial_analysisInkling scores 25.54 on Artificial Analysis Intelligence Index
artificial_analysisInkling: context length changed from 1000000 to 1048576
Context window1M tokens→1.05M tokensopenrouter
Change history23
Viewing AI Atlas as of 1 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Inkling was not yet in AI Atlas on 1 Sept 2026
Release daterelease_date1
Opennessopenness1
Context windowcontext_length3
Max outputmax_output_tokens2
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Hugging Face repohf_repo1
Aa context windowaa_context_window1
Aa opennessaa_openness1
Descriptiondescription1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Openrouter idopenrouter_id1
Openrouter listed atopenrouter_listed_at1
Reasoningreasoning1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Visionvision1
Weights availableweights_available1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
20
Source tiers
T220
Freshest observation
4 h ago
Conflicts
None
Source documents 5
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (60/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →