alt.freeweights.text / Inkling-2-Small

From: thinkingmachines <huggingface.co/thinkingmachines>Newsgroups: alt.freeweights.textSubject:

Inkling-2-Small

Date: 2026-11-15Commit: 8361e7aSigned: 2DC28CC7B26A283B ✓

Image text to text model with 594.1B parameters. Safetensors weights, 394 GB in all. Published by thinkingmachines under Apache-2.0.

594.1B params394GBInkling-2-Smallsafetensorspermissive

FactsParams594.1BSize394 GBFormatssafetensorsTaskimage text to textLicenseApache-2.0From sourcepermissive

$ fw get thinkingmachines/Inkling-2-Small
# manifest sha256 d2ece79eb9c7… · 394 GB · 42 files
$ fw verify ./Inkling-2-Small thinkingmachines/Inkling-2-Small

From sourceHosted (signed)thinkingmachines/Inkling-2-SmallLast check: 2026-11-15 03:21 UTC

Get help

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Works with

Run23 Fine-tune29 Convert15 Evaluate13 Scan13 Apps62

Runs with

Ranked by fit to this model (safetensors), then by GitHub stars.

vLLM exo Text Generation WebUI

SGLang MLC LLM KTransformers LMCache Xinference LMDeploy mistral.rs Mooncake FlashInfer

Show all 23

AIBrix fastllm ExLlamaV3

Transformers LocalAI tinygrad Triton Inference Server BentoML CTranslate2 ExLlamaV2 LitServe

Convert with

mergekit TensorRT Model Optimizer

LLM Compressor Neural Compressor AutoRound AQLM GPTQModel ONNX Core ML Tools ExecuTorch

Show all 15

Evaluate with

Opik DeepEval Ragas lm-evaluation-harness OpenCompass SWE-bench

simple-evals TruLens HELM

LightEval

Evaluate Weave

Show all 13

Autoevals

Scan with

promptfoo garak Guardrails NeMo Guardrails Giskard DeepTeam AI Fairness 360 Fairlearn Detoxify MCP Scanner AgentDojo ModelScan

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picklescan

Overview Model card Files Use it License Provenance Model tree

Overview

Size: 394 GB
Weights: 393 GB (safetensors)
Parameters: 594.1B
Formats: safetensors
Task: image text to text
License: Apache-2.0 (permissive)
Files: 42, each with a sha256
Publisher: thinkingmachines
Added: 2026-11-15
Section: alt.freeweights.text

Lineage

Original release from the publisher.

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Sources

Badge	Host	Last check	Result
From source	huggingface.co	2026-11-15 03:21 UTC	passed

Model card

From the publisher at commit 8361e7a. Shown as plain text with links; images open at the publisher.

Inkling 2 Small#

Image: image

NVFP4 | MXFP8 | Playground | Tinker Cookbook | Acceptable Use

1. General Information#

Inkling 2 Small is a general-purpose multimodal model that accepts text and image inputs and generates text outputs. It is intended for use in English and other languages, and across multiple coding languages. The model is designed to be used by developers building AI-powered applications, including agentic and tool-use systems, coding assistants, chatbots, and retrieval-augmented generation systems, and is suitable for general-purpose conversational use, instruction-following, and other natural language and visual tasks. It is released with open weights to support research, fine-tuning and integration into third-party products by downstream developers.

Languages: English, with general multilingual capabilities across other languages.

2. Getting Started#

Try Inkling 2 Small on the Tinker Playground or access via API using the Tinker Cookbook. To fine-tune Inkling 2 Small with Tinker, also install the tml-renderers package.

Inkling 2 Small supports local inference using:

SGLang (recipe)
vLLM (recipe)
TokenSpeed (recipe)
Unsloth (recipe)

Inkling 2 Small can also be post-trained with:

API access is also available through third party inference providers, including:

Required hardware#

The model is distributed in two checkpoint formats.

The main NVFP4 checkpoint requires a GPU cluster with at least 500GB of aggregated VRAM. This can be met with either of the following example configurations:

2x NVIDIA B300 GPUs
4x NVIDIA H200 GPUs

The alternative MXFP8 checkpoint requires a GPU cluster with at least 800GB of aggregated VRAM. This can be met with either of the following example configurations:

4x NVIDIA B300 GPUs
8x NVIDIA H200 GPUs

The model was pretrained, midtrained and post-trained in NVFP4, so this is the native precision for the model. We recommend the NVFP4 checkpoint for all use-cases, and we're confident that it's the best option. The MXFP8 has a very marginal 1–2 percentage points gain over the NVFP4 checkpoint over evals, but we do not think it is meaningful for any practical use-cases.

Required software#

Running the model directly on GPU hardware requires an inference deployment framework — either SGLang, vLLM, TokenSpeed, Unsloth, or Hugging Face, along with all of their respective dependency libraries.

3. Model Properties#

Model type#

Multimodal autoregressive transformer

Architecture type#

A 48-layer decoder-only transformer with a sparse Mixture-of-Experts (MoE) feed-forward backbone: each token is routed to 8 of 384 experts. Attention is a hybrid of local and global layers. The model is natively multimodal — images are encoded via a vision transformer — with image and text inputs projected into a shared hidden space and processed jointly by the decoder.

Parameters#

594B total, 17B active

Numerics support#

MXFP8 and NVFP4

Input modalities#

Inkling 2 Small accepts text input in UTF-8 encoding and image input in any pixel-based format (with each dimension ideally between 40px and 4096px for optimal performance). It supports a context window of up to 1M tokens.

Output modalities#

Inkling 2 Small generates output as UTF-8 encoded text.

4. Training#

Training data includes a broad variety of content types, including text, images, video. Training data for the model was drawn from publicly available sources, acquired from third-parties, generated internally, or synthetically generated or augmented. Publicly available data includes content from the public internet and publicly accessible repositories.

The training data curation process includes cleaning, processing, and modifying datasets. These processing steps, which vary by data type, may include deduplication and filtering to remove junk or other low-quality data, or to advance safety or other objectives.

5. Evaluations#

| | Open Weights Flash | Open Weights Pro | Closed Weights Flash

| Params (B) activated / total | 17/594 | 18/320 | 15/309 | 23/428 | 16/552 | 42/816 | 40/753 | 42/1020 | 49/1050 | 104/2800 | – | – | –

| AA Index (v5.0) | 30.6 | 27.8 | 26.7 | 29.1 | 32.6 | 24.9 | 31.7 | 29.9 | 26.1 | – | 27.9 | 30.8 | 36.5

| Vals Index (v2.2) | 56.1% | 50.9% | 54.8% | 53.8% | 61.3% | 48.6% | 59.7% | 57.8% | 56.5% | 53.0% | 52.3% | 56.0% | 58.7%

| FrontierCode v2.0 stirrup v0.2.1 | 25.4% | 17.6% | 21.6% | 20.8% | 28.5% | 7.6% | 21.6% | 24.0% | 15.0% | 17.3% | 25.2% | 18.7% | 34.9%

| DeepSWE v1.1 mini-swe-agent v2.4.6 | 72.1% | 63.4% | 67.9% | 73.7% | 77.0% | 60.0% | 69.0% | 71.9% | 61.7% | 68.5% | 66.6% | 73.8% | 59.9%

| Terminal Bench Science v0.1 mini-swe-agent v2.4.6 | 5.7% | 4.8% | 4.3% | 3.3% | 12.9% | 1.9% | 9.5% | 5.7% | 4.3% | 8.1% | 8.6% | 10.0% | 20.0%

| Vibe Code Bench v1.1 openhands (vals) | 81.6% | 30.8% | 79.0% | 73.9% | 87.7% | 76.2% | 78.1% | 85.2% | 81.6% | 85.0% | 81.7% | 78.7% | 90.4%

| SWE-Atlas v1.1 mini-swe-agent v2.4.6 | 61.9% | – | – | – | 62.1% | 42.3% | – | – | – | 61.0% | 50.8% | 57.3% | 59.4%

| SWEBench Pro v2 (Hard) mini-swe-agent v2.4.6 | 86.3% | 82.8% | 89.7% | 84.3% | 89.7% | 82.4% | 84.3% | 89.2% | 83.8% | 88.2% | 88.7% | 58.8% | 52.9%

| Sudo L7 | 14.1% | – | – | – | – | – | 9.4% | – | 13.9% | 12.2% | – | 10.6% | –

| PostTrainBench v1.2 Inkling 2 Small in Claude Code | 31.9% | 36.8% | – | – | 30.5% | – | 34.5% | – | – | 31.5% | – | – | –

| PMPP-Hard (AUC, 0–10h) pi v0.83.0 | 494.27 | – | – | – | 497.36 | – | 430.96 | – | 478.39 | 453.58 | – | – | –

| BioMysteryBench terminus v2 | 70.0% | – | 69.3% | – | – | – | – | – | – | 72.6% | 61.5% | 62.2% | 70.4%

| BrowseComp Inkling 2 Small with compaction | 90.2% | 76.0% | 78.1% | 69.5% | 87.8% | 68.7% | 75.1% | – | 84.5% | 88.4% | 83.6% | 89.4% | 80.2%

| DeepSearchQA Inkling 2 Small with compaction | 90.9% | 84.3% | 86.0% | 82.7% | 84.5% | 80.4% | 84.7% | 90.0% | 84.4% | 95.0% | 83.5% | 90.1% | 83.2%

| MCP Atlas Full / Public | 85.4/85.0% | –/82.0% | –/62.9% | –/80.4% | –/83.2% | 89.2/87.5% | 84.2/83.6% | –/84.4% | –/84.5% | 82.3/84.2% | –/77.8% | –/87.5% | –/81.0%

| AA-Briefcase v1.1 | 1527 | 1451 | 1487 | 1476 | 1570 | 1279 | 1503 | 1512 | 1348 | 1497 | 1337 | 1203 | 1574

| GDPVal-AA v2.1 | 1630 | 1649 | 1614 | 1465 | 1746 | 1401 | 1657 | 1689 | 1384 | 1543 | 1444 | 1445 | 1631

| JobBench | 70.5% | 60.7% | 61.2% | 67.5% | 68.5% | 61.8% | 61.4% | 62.0% | 55.2% | 54.3% | 49.0% | 63.4% | 39.2%

| DAYJOB (Healthcare) | 6.4% | 1.2% | – | – | 6.0% | – | 4.4% | – | 3.6% | 4.0% | 1.2% | 2.0% | –

| EnterpriseOps-Gym | 46.8% | 33.2% | 29.0% | 48.9% | 43.6% | 43.1% | 36.4% | 38.0% | 44.9% | 45.3% | 24.9% | 45.7% | 25.1%

| EnterpriseBench-CoreCraft | 71.8% | 46.7% | – | – | 58.5% | – | 51.8% | – | 47.7% | 43.1% | 43.1% | 58.5% | –

| Finance Agent v2.1 | 67.5% | 60.6% | 63.3% | 58.8% | 62.9% | 60.7% | 65.0% | 64.3% | 61.7% | 60.0% | 56.8% | 65.8% | 65.4%

| Excel Modeling Benchmark v1.1 | 69.5% | 66.3% | 68.9% | 67.8% | 69.2% | 62.0% | 69.1% | 67.4% | 68.7% | 71.3% | 70.0% | 72.9% | 65.5%

| Tax Agent Bench | 65.8% | 62.0% | 59.9% | 62.7% | 74.9% | 52.1% | 73.1% | 64.9% | 67.5% | 68.7% | 58.9% | 66.8% | 62.2%

| Apex-Accounting v1.1 pass@1 | 14.5% | 12.3% | – | 13.5% | 12.5% | 13.8% | 13.9% | – | 12.0% | 9.5% | 10.8% | 15.5% | 15.3%

| DAYJOB (Finance) | 14.3% | 7.3% | – | – | 12.5% | – | 11.0% | – | 4.8% | 5.5% | 6.8% | 4.5% | –

| DeepFinance | 29.8% | – | – | – | – | – | 27.5% | – | 21.5% | – | 26.4% | – | 40.0%

| Diligence Bench Best harness | 58.1% | 48.3% | – | 51.6% | 50.4% | 59.0% | 49.4% | 51.8% | 51.5% | 50.9% | 42.1% | 51.1% | 40.8%

| AA-AnalystAgent | 51.2% | 25.0% | – | – | – | – | 38.8% | 37.5% | – | 38.8% | 43.8% | 46.3% | 53.8%

| Tau 3 Banking v1.0.1 | 40.4% | 47.2% | – | – | – | – | – | – | – | 33.4% | – | – | –

| ATLAS-Finance v1.1 | 6.0% | – | – | – | – | – | 3.0% | – | – | 3.7% | – | 3.7% | –

| Harvey LAB v1.1 | 21.7% | 10.4% | 13.3% | 7.5% | 14.2% | 25.0% | 14.6% | 13.8% | 15.8% | 12.9% | 4.2% | 12.1% | 4.2%

| Legal Research Bench | 46.6% | 45.2% | 38.0% | 34.1% | 45.2% | 38.5% | 49.0% | 47.1% | 35.6% | 46.2% | 30.3% | 38.9% | 43.8%

The publisher's README is longer; it is cut here. Read the rest at the source.

Files

42 files · 394 GBWeights 393 GB (safetensors). Sizes and sha256 from the signed manifest.

Show all 42 files with their sha256

File	Size	sha256
.eval_results/Inkling-2-Small.yaml	2.86 KB	ef281c166580b0b6ae95da0a239a1dab26caf57bad75aba848a5370c53e178bc
.eval_results/gpqa.yaml	182 B	485c0d5c6b985d9ea2e0abae428992d40de7a84a8fa0644d6cceb7f89a2adb48
.eval_results/hmmt_feb_2026.yaml	206 B	f2f89a5ca4098af118f4bb15bf64a5f1b0aa81b0f7cf7481363681265d5e042a
.eval_results/swe-bench_multilingual.yaml	225 B	2fa5bd16b8ae4159192e686831743e74f6e1428c80a3043171dfccb39614ffec
.eval_results/terminal-bench-2.1.yaml	241 B	f8bdcd24e98f582a5dcfc539f35da5bde3e5442fb1623bb365fe6fcf9d359fab
.eval_results/terminal-bench.yaml	267 B	b0ea3a5ab844b8c7bd5c21f1aaeecec766d0ba472af22a9fd153808458721d6a
.gitattributes	1.57 KB	34448b82c17d60fec9b65b1f093c115ddbaadc04beb1b0140b6bfed2e012a930
README.md	129 KB	1b58f92b862cbcf67b4ddbcc56c270fe72d491bd6a2a3e73f7541690fcbdb315
chat_template.jinja	6.66 KB	e9cfd8e75d1272633c2e72b3cc76e99567e2bc8912b960483aed483ad35d54c7
config.json	2.77 KB	18512277b0c6916a54de7ce77b6518b0519b91e45c56df1f41c3fa3f09b9b465
hf_quant_config.json	88.9 KB	2d2079af0ae7cb990b5467ab3383a6ee01c738e1bfd712de4fe109d63dd03802
model-00001-of-00024.safetensors	16.2 GB	d5e2ab13b8f433da7b2221191c6e254836bd93d9fd3f1ea2cadec1d4a002b69b
model-00002-of-00024.safetensors	18.7 GB	4c0dc50628685b3a06ae6eb14ece99e566604c7246dacd69a888e09f859ec0a2
model-00003-of-00024.safetensors	16.7 GB	421810dbc6ecc342c903260c32b72adb6f770f91a9cadf7105f36527ab140b9d
model-00004-of-00024.safetensors	18.7 GB	8ccab80fac89922589bb6a36748503cb0939670880d8340b49821b885f67befa
model-00005-of-00024.safetensors	16.7 GB	9fc06229959a9ef8cd089b5e54502c2c58511f14b8b40869e8513917d08c2d3c
model-00006-of-00024.safetensors	18.7 GB	5ef349a9c63fb41cdab91da11ae093c3ca9020e3c3c3f3e8a4e985b9c3eea199
model-00007-of-00024.safetensors	16.7 GB	57e6f2ce0848ce421458d44415d1e6c804f081f131d749c8cee29c7dbe06ed89
model-00008-of-00024.safetensors	18.7 GB	9c5426ed76df2b17c810eb46afb7107af1e325eaa3bc5dd5f4749f90cb5d3f43
model-00009-of-00024.safetensors	16.7 GB	409be1eef555bdbfa0c54eba2c83096fce03bef42825fc46ba8ae75c9b203578
model-00010-of-00024.safetensors	18.7 GB	0cbd6f5fccfb21cd92d8acd8df1047591267a126b143a06893c3def70e1dd729
model-00011-of-00024.safetensors	16.7 GB	5e32b1cb814decd3bd976c912304556eae78f051bfee32b46b80f42c23516469
model-00012-of-00024.safetensors	18.7 GB	e83d3b4c0695e3fd98336240eb22d8846282c132a197c3d48c498b03515f7c58
model-00013-of-00024.safetensors	16.7 GB	4fa4f049c92c0ee80c8d0548858a0597e22c94a848c55cd0c1a5f4fdb5a95d25
model-00014-of-00024.safetensors	18.7 GB	e31830dac4ab557a80d848ebdcc741214ac41c80118e0c57b86d5cb443b3b2c1
model-00015-of-00024.safetensors	15.3 GB	d3726dda84e3e6f9a51144b927548538350fe19306531ad7c469d096f217dc04
model-00016-of-00024.safetensors	12.8 GB	dd52ccc4699846d9b676028ecb5215f231caf6e43716396d29a74f6b84b7bf98
model-00017-of-00024.safetensors	12.8 GB	314e216a559fcc20f4afadb150d0fbffad2bcef06706b5da5cd88b6ca34de160
model-00018-of-00024.safetensors	12.8 GB	a169b5dc19632a96847e88008ed8cbb81bad48f9ecb529734be6a5f190c3953c
model-00019-of-00024.safetensors	12.8 GB	778358d2978c3a1d27cb6649799e309c46c98bfa508b6140ee34d678c62d2290
model-00020-of-00024.safetensors	12.8 GB	cc1c409dab27a3cc2dc67b64d6ebc409ac074d500235991b5bf363c74daea17a
model-00021-of-00024.safetensors	12.8 GB	d82eabc9d7d944b3a215a925f9f27539a2baf97608d987c3fbaf753688a3e7bc
model-00022-of-00024.safetensors	19.9 GB	88f9e567ea721cba6de8bd922d8ae0af9323a926d973d37077dd8ce88ee9fff4
model-00023-of-00024.safetensors	18.7 GB	4ad641cf6b8ebb3dae2cc7f896a6a1c1a96cb1f36f6dd70d0eb3ae24374a0681
model-00024-of-00024.safetensors	11.9 GB	ed5f05298ba5605db2cb957866d08024fa708de8c0d45e7268e4f7da9b58dfed
model.safetensors.index.json	153 KB	380049228e9932948bcb1e45b99834d2153fce4dc85df6d5eeeb74a92cbc0bb4
mtp.safetensors	3.42 GB	3b265640ec84ba66e928a2844c4c022c94be731336b0f63755a20a247bfd2a36
processor_config.json	394 B	b326f9a5d49c037c463045bec4d80229f5463048df7d6de95b597667888228ae
special_tokens_map.json	448 B	26152a6988fb88d00ee1bead146bd19589337eefaa5222dbdb7677ffd2403b95
tiktoken/tokenizer.model	3.39 MB	f170372dd655728909228220d77cf6b8104a59f38a91262a7d2c4027906ec0d8
tokenizer.json	26.2 MB	7f332727f9a3f093dd452a39cc978e6757627e5dad1b0673aa4e75174f236dd6
tokenizer_config.json	13.2 KB	6addc2bf8dc756dea8edd083a4ea3b67a66b8f513e9745a36e4a7cc0cc9f55ed

VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.

Upstream commit	Date	Contents
8361e7a31a pinned now	2026-11-15 03:21 UTC	42 files · 394 GB

Use it

$ fw get thinkingmachines/Inkling-2-Small
# manifest sha256 d2ece79eb9c7… · 394 GB · 42 files
$ fw verify ./Inkling-2-Small thinkingmachines/Inkling-2-Small

fw.pyChecks the signature and every sha256, tries each source in order, resumes.

$ python3 fw.py get https://freeweights.allternit.com/manifests/thinkingmachines/Inkling-2-Small.json --dir ./Inkling-2-Small
$ python3 fw.py verify ./Inkling-2-Small ./thinkingmachines__Inkling-2-Small.json

hfThe Hugging Face CLI with one setting. Same repo id.

$ HF_ENDPOINT=https://freeweights.allternit.com hf download thinkingmachines/Inkling-2-Small --revision 8361e7a31ae7e9966a49a91d3994fde618936c2b --local-dir ./Inkling-2-Small

transformersLoad the weights in Python.

import os
os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com"
from transformers import AutoModelForImageTextToText, AutoProcessor
processor = AutoProcessor.from_pretrained("thinkingmachines/Inkling-2-Small", revision="8361e7a31ae7e9966a49a91d3994fde618936c2b")
model = AutoModelForImageTextToText.from_pretrained("thinkingmachines/Inkling-2-Small", revision="8361e7a31ae7e9966a49a91d3994fde618936c2b", device_map="auto")

vLLMServe an OpenAI-compatible API.

$ HF_ENDPOINT=https://freeweights.allternit.com vllm serve thinkingmachines/Inkling-2-Small --revision 8361e7a31ae7e9966a49a91d3994fde618936c2b

License

Name: Apache License 2.0
Id: Apache-2.0
Class: Permissive
Redistribution: yes
Listing: Hosted (signed)
Decided: License as declared by the publisher. No person read it. 2026-11-15
Text in: README.md
Text sha256: 1b58f92b862cbcf67b4ddbcc56c270fe72d491bd6a2a3e73f7541690fcbdb315
Terms gate: No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: thinkingmachines <huggingface.co/thinkingmachines>Newsgroups: alt.freeweights.textSubject: Inkling-2-SmallDate: 2026-11-15Commit: 8361e7aSigned: 2DC28CC7B26A283B ✓

Upstream: thinkingmachines/Inkling-2-Small
Pinned commit: 8361e7a31ae7e9966a49a91d3994fde618936c2b
Manifest: Inkling-2-Small.json · .minisig
Manifest sha256: d2ece79eb9c7dfdbe6df83fb92dabaafca3791a803683e712376fa033b31105f
Signature: minisign, Ed25519, key 2DC28CC7B26A283B
Created: 2026-11-15 03:21 UTC
Generator: freeweights-manifest/0.1.0
Takedowns: None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/thinkingmachines/Inkling-2-Small.json
$ curl -O https://freeweights.allternit.com/manifests/thinkingmachines/Inkling-2-Small.json.minisig
$ minisign -Vm Inkling-2-Small.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq
$ shasum -a 256 <file>   # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

1 model in the catalog name this one as their parent.

Quantizations: 1

Quantizations 1

unsloth/Inkling-2-Small-GGUF4.97 TB

Get it

Download

$ HF_ENDPOINT=https://freeweights.allternit.com hf download thinkingmachines/Inkling-2-Small

Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest

minisign, key 2DC28CC7B26A283B. Inkling-2-Small.json. Provenance. Takedown history: none.

Source

huggingface.co/thinkingmachines/Inkling-2-Small

Variants

1 quantized or adapter build of Inkling-2-Small. Each has its own license check and page.

SubjectSizeParamsLicenseDate

Inkling-2-Small-GGUFHosted (signed) From: unsloth in alt.freeweights.text4.97 TB—Permissive2026-11-15

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From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_e2egit-v2-10-8B

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From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_unitsyn-python-large-10-8B

From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_mix_h2_language_proportional-65-8B

Inkling-2-Small

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Inkling 2 Small#

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2. Getting Started#

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