GPT OSS 120B High vs Inkling 2 Small
Inkling 2 Small leads the LLM Stats Score 47.1 to 24.6. GPT OSS 120B High is 2.4x cheaper per token.
OpenAI · Thinking Machines Lab · Updated for 2026
Which is better?
Inkling 2 Small leads the overall LLM Stats Score 47.1 to 24.6, ranking #41 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, GPT OSS 120B High is roughly 2.4x 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 OSS 120B High
- cost matters — it's about 2.4x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Inkling 2 Small
- overall performance matters — it scores 47.1 and ranks #41 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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
7 reported for GPT OSS 120B High · 11 for Inkling 2 Small
GPT OSS 120B High 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 OSS 120B High ($0.10/1M tokens) is 3.0x cheaper than Inkling 2 Small ($0.30/1M tokens).
For output processing, GPT OSS 120B High ($0.50/1M tokens) is 2.0x cheaper than Inkling 2 Small ($1.00/1M tokens).
In conclusion, Inkling 2 Small is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling 2 Small has 477.2B more parameters than GPT OSS 120B High, making it 408.6% larger.
Context Window
Maximum input and output token capacity
Inkling 2 Small accepts 256,000 input tokens compared to GPT OSS 120B High's 131,072 tokens. Only GPT OSS 120B High specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Inkling 2 Small supports multimodal inputs, whereas GPT OSS 120B High does not.
Inkling 2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT OSS 120B High
Inkling 2 Small
License
Usage and distribution terms
GPT OSS 120B High is licensed under Apache 2.0, while Inkling 2 Small uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GPT OSS 120B High was released on 2025-08-05, while Inkling 2 Small was released on 2026-11-05.
Inkling 2 Small is 15 months newer than GPT OSS 120B High.
Aug 5, 2025
1.3 years ago
Nov 5, 2026
4 days ago
1.3yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT OSS 120B High is available from OpenAI, Fireworks. Inkling 2 Small is available from Thinking Machines Lab.
GPT OSS 120B High
Inkling 2 Small
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B High and Inkling 2 Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B High vs Inkling 2 Small.