GPT-4 Turbo vs Inkling 2 Small
Inkling 2 Small leads the LLM Stats Score 47.2 to 8.6. Inkling 2 Small is 31.6x cheaper per token.
OpenAI · Thinking Machines Lab · Updated for 2026
Which is better?
Inkling 2 Small leads the overall LLM Stats Score 47.2 to 8.6, ranking #39 overall.
In the 1 individual benchmarks reported for both models, Inkling 2 Small wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Inkling 2 Small is roughly 31.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Inkling 2 Small also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4 Turbo
- you want predictable pricing at $10.00/M input and $30.00/M output
Choose Inkling 2 Small
- overall performance matters — it scores 47.2 and ranks #39 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 31.6x cheaper per token
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Nov 2026
At a glance
The differences that matter most.
Individual benchmarks
6 reported for GPT-4 Turbo · 11 for Inkling 2 Small
GPT-4 Turbo outperforms in 0 benchmarks, while Inkling 2 Small is better at 1 benchmark (GPQA).
Inkling 2 Small significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4 Turbo ($10.00/1M tokens) is 33.3x more expensive than Inkling 2 Small ($0.30/1M tokens).
For output processing, GPT-4 Turbo ($30.00/1M tokens) is 30.0x more expensive than Inkling 2 Small ($1.00/1M tokens).
In conclusion, GPT-4 Turbo is more expensive than Inkling 2 Small.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Inkling 2 Small accepts 256,000 input tokens compared to GPT-4 Turbo's 128,000 tokens. Only GPT-4 Turbo specifies output context (4,096 tokens).
Input capabilities
Documented input modalities across available providers
Inkling 2 Small supports multimodal inputs, whereas GPT-4 Turbo does not.
Inkling 2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4 Turbo
Inkling 2 Small
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-4 Turbo was released on 2024-04-09, while Inkling 2 Small was released on 2026-11-05.
Inkling 2 Small is 31 months newer than GPT-4 Turbo.
Apr 9, 2024
2.6 years ago
Nov 5, 2026
3 days ago
2.6yr newerKnowledge Cutoff
When training data ends
GPT-4 Turbo has a documented knowledge cutoff of 2023-12-31, while Inkling 2 Small's cutoff date is not specified.
We can confirm GPT-4 Turbo's training data extends to 2023-12-31, but cannot make a direct comparison without Inkling 2 Small's cutoff date.
Dec 2023
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Provider Availability
GPT-4 Turbo is available from Azure, OpenAI. Inkling 2 Small is available from Thinking Machines Lab.
GPT-4 Turbo
Inkling 2 Small
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 Turbo and Inkling 2 Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 Turbo vs Inkling 2 Small.