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Model Family Directory

KAIL Model Family

A chronological register of five generations in the KAIL model family, developed by Kaniskten Programming. All parameter counts, milestone dates, architectures, and evaluation notes align strictly with verified project records.

Generational Comparison

ModelGenerationStatusArchitectureParameters
KAIL F1FirstHistorical prototypeEarly experimental architecture; formal name not documentedApproximately 1,000
KAIL S1SecondRelease information pendingKailX5 billion (5B)
KAIL S2ThirdRelease information pendingKailX7.6B and 15B
KAIL F2Fourth listed milestoneModel developed; publication status pendingKailAApproximately 1,123,372,800 (1.123B)
KAIL S3Next planned generationComing soonUnder development; not announcedNot announced
1 • Generation First

KAIL F1

The beginning of the KAIL model family, serving as an early foundational experimentation milestone.

Historical prototype
Overview:KAIL F1 represents the beginning of the KAIL model family. Its primary significance is its place in the project's development history, rather than a claim of modern large-language-model capabilities.

Full Specifications

Generation
First
Status
Historical prototype
Release / Milestone date
17 August 2022 — recorded project date
Architecture
Early experimental architecture; formal name not documented
Parameters
Approximately 1,000
Supported languages
Not formally documented
Intended use
Early AI experimentation and foundational model development
Training approach
Historical training details unavailable
Verified evaluation
No standardized evaluation published
Model download
Not publicly confirmed
Repository
Not publicly confirmed
Documentation
Historical documentation not publicly confirmed
2 • Generation Second

KAIL S1

Second generation milestone built on the KailX architecture with a 5B parameter design target.

Release information pending

Full Specifications

Generation
Second
Status
Release information pending
Release / Milestone date
20 May 2024 (Milestone date)
Architecture
KailX
Parameters
5 billion (5B)
Supported languages
All languages — intended coverage
Model variants
One specified 5B size
Intended use
Multilingual text processing and general-purpose AI
Training approach
Not documented
Verified evaluation
Not published
Context length
Not announced
Input/output modalities
Not announced
Quantization formats
Not announced
Model download
Not confirmed
Repository
Not confirmed
Documentation
To be published
KailX ArchitectureKailX is the designated architecture for KAIL S1. Its detailed technical design should be documented separately, including its model layers, attention mechanism, positional encoding, normalization, feed-forward blocks, tokenizer and inference requirements. The 5B parameter count is a model specification, not a measure of benchmark quality or inference speed.
Multilingual Support Scope“All languages” describes the intended goal. To claim verified support for all languages, the model needs multilingual training coverage and evaluations across representative languages and scripts.
3 • Generation Third

KAIL S2

Third generation dual-size system utilizing KailX across 7.6B and 15B parameter configurations.

Release information pending

Full Specifications

Generation
Third
Status
Release information pending
Release / Milestone date
2 April 2025 (Milestone date)
Architecture
KailX
Parameters
7.6B and 15B
Supported languages
Hindi, Tamil, Kannada, Telugu and Malayalam are planned; additional coverage requires confirmation
Model variants
KAIL S2 7.6B; KAIL S2 15B
Intended use
General-purpose AI at two model sizes
Training approach
Not documented
Verified evaluation
Not published
Context length
Not announced
Input/output modalities
Not announced
Quantization formats
Not announced
Model download
Not confirmed
Repository
Not confirmed
Documentation
To be published

Model Variants

KAIL S2 7.6B7.6 billion parameters

Smaller variant · Lower expected resource requirements than the 15B version, all else being equal.

KAIL S2 15B15 billion parameters

Larger variant · Greater potential capacity, with higher memory requirements.

Planned Language Set:HindiTamilKannadaTeluguMalayalam
Architecture & Variant ParityBoth variants use the designated KailX architecture. Whether they share the same tokenizer, training dataset, context length and architectural configuration remains to be documented.
Multilingual Verification CriteriaEnglish and other languages should be listed as supported only after their coverage is established. A multilingual model should be evaluated separately on each language rather than relying on a single overall score.
4 • Generation Fourth listed milestone

KAIL F2

Custom KailA causal LM architecture with 1.123B parameters, fine-tuned via LoRA on curated instruction datasets.

Model developed; publication status pending

Full Specifications

Generation
Fourth listed milestone
Status
Model developed; publication status pending
Release / Milestone date
Not announced
Architecture
KailA
Model class
KailAForCausalLM
Model type
kail
Parameters
Approximately 1,123,372,800 (1.123B)
Training approach
LoRA supervised fine-tuning
Training data
8,000 examples: 7,200 training and 800 validation
Training configuration
Seed 42; effective batch size 16; maximum sequence length 2,048; BF16
Training hardware
NVIDIA RTX 5060 Ti 16GB
Primary evaluation areas
Instruction following, coding, mathematics and identity consistency
Verified evaluation
Internal results available; independent verification not established
Model download
Public availability not confirmed
Repository
kaniskten/kail-f2
Documentation
Model card, architecture information and evaluation report to accompany publication

Planned Benchmark Suite

MMLUARC-EasyARC-ChallengeHellaSwagWinograndeGSM8KTruthfulQAPIQAOpenBookQABoolQ
Architecture & Training WorkflowKAIL F2 uses the custom KailA architecture. The conversion workflow produced a model configuration with approximately 1.123 billion parameters. The documented training process used LoRA-based supervised fine-tuning on a curated instruction dataset. The internal evaluation included coding, mathematical reasoning, general instruction following and adversarial identity tests. These results should be published with the exact test set, scoring procedure and limitations.
5 • Generation Next planned generation

KAIL S3

The next planned model in the KAIL family. Specifications and benchmarks will be published upon finalized verification.

Coming soon
Overview:KAIL S3 is the next planned model in the KAIL family. Its public announcement should specify the finalized architecture, model sizes, supported languages, training methodology, hardware requirements and reproducible evaluation results. Avoid publishing projected specifications as completed capabilities.

Full Specifications

Generation
Next planned generation
Status
Coming soon
Release / Milestone date
Not announced
Architecture
Under development; not announced
Parameters
Not announced
Supported languages
To be announced
Training approach
To be announced
Verified evaluation
Not published
Context length
Not announced
Input/output modalities
Not announced
Model download
Not yet available
Repository
Not announced
Documentation
Planned for release

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