DeepSeek-V3 vs Inkling 2 Small
Inkling 2 Small leads the LLM Stats Score 47.2 to 14.9. DeepSeek-V3 is 1.1x cheaper per token.
DeepSeek · Thinking Machines Lab · Updated for 2026
Which is better?
Inkling 2 Small leads the overall LLM Stats Score 47.2 to 14.9, ranking #39 overall.
In the 2 individual benchmarks reported for both models, Inkling 2 Small wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V3 is roughly 1.1x 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 DeepSeek-V3
- cost matters — it's about 1.1x cheaper per token
- you need open weights you can self-host or fine-tune
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 2 of 2 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
20 reported for DeepSeek-V3 · 11 for Inkling 2 Small
DeepSeek-V3 outperforms in 0 benchmarks, while Inkling 2 Small is better at 2 benchmarks (GPQA, SWE-Bench Verified).
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, DeepSeek-V3 ($0.27/1M tokens) is 1.1x cheaper than Inkling 2 Small ($0.30/1M tokens).
For output processing, DeepSeek-V3 ($0.89/1M tokens) is 1.1x cheaper than Inkling 2 Small ($1.00/1M tokens).
In conclusion, Inkling 2 Small is more expensive than DeepSeek-V3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 has 77.0B more parameters than Inkling 2 Small, making it 13.0% larger.
Context Window
Maximum input and output token capacity
Inkling 2 Small accepts 256,000 input tokens compared to DeepSeek-V3's 131,072 tokens. Only DeepSeek-V3 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Inkling 2 Small supports multimodal inputs, whereas DeepSeek-V3 does not.
Inkling 2 Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3
Inkling 2 Small
License
Usage and distribution terms
DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Inkling 2 Small uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V3 was released on 2024-12-25, while Inkling 2 Small was released on 2026-11-05.
Inkling 2 Small is 23 months newer than DeepSeek-V3.
Dec 25, 2024
1.9 years ago
Nov 5, 2026
3 days ago
1.9yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 is available from DeepSeek, DeepInfra. Inkling 2 Small is available from Thinking Machines Lab.
DeepSeek-V3
Inkling 2 Small
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 and Inkling 2 Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 vs Inkling 2 Small.