DeepSeek-V4-Pro-0813 vs Inkling-Small
DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.5 to 38.9. Inkling-Small is 1.0x cheaper per token.
DeepSeek · Thinking Machines Lab · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 52.5 to 38.9, ranking #10 overall.
In the 3 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 3; this is a narrower head-to-head signal than the composite indexes.
DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 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-V4-Pro-0813
- overall performance matters — it scores 52.5 and ranks #10 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Inkling-Small
- you want predictable pricing at $0.30/M input and $1.20/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 24 for Inkling-Small
DeepSeek-V4-Pro-0813 outperforms in 3 benchmarks (Humanity's Last Exam, Terminal-Bench 2.1, Toolathlon), while Inkling-Small is better at 0 benchmarks.
DeepSeek-V4-Pro-0813 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-V4-Pro-0813 ($0.43/1M tokens) is 1.4x more expensive than Inkling-Small ($0.30/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 1.4x cheaper than Inkling-Small ($1.20/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Inkling-Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 1324.0B more parameters than Inkling-Small, making it 479.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Inkling-Small's 256,000 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Inkling-Small is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
Inkling-Small supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Inkling-Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Inkling-Small
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Inkling-Small uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Inkling-Small was released on 2026-07-30.
DeepSeek-V4-Pro-0813 is 0 month newer than Inkling-Small.
Aug 13, 2026
3 weeks ago
2w newerJul 30, 2026
1 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Inkling-Small is available from Thinking Machines Lab.
DeepSeek-V4-Pro-0813
Inkling-Small
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Inkling-Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Inkling-Small.