DeepSeek-V4.1-Flash-1017 vs Inkling
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 37.1. DeepSeek-V4.1-Flash-1017 is 3.3x cheaper per token.
DeepSeek · Thinking Machines Lab · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 37.1, ranking #15 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash-1017 is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017
- overall performance matters — it scores 51.2 and ranks #15 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 3.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Inkling
- you want predictable pricing at $0.95/M input and $4.05/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 16 for Inkling
DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (Humanity's Last Exam (no tools, text-only)), while Inkling is better at 0 benchmarks.
DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 ($0.30/1M tokens) is 3.2x cheaper than Inkling ($0.95/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 3.4x cheaper than Inkling ($4.05/1M tokens).
In conclusion, Inkling is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling has 211.8B more parameters than DeepSeek-V4.1-Flash-1017, making it 27.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Inkling's 524,288 tokens. Inkling can generate longer responses up to 524,288 tokens, while DeepSeek-V4.1-Flash-1017 is limited to 393,216 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and Inkling support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
Inkling
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Inkling 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-V4.1-Flash-1017 was released on 2026-10-17, while Inkling was released on 2026-07-21.
DeepSeek-V4.1-Flash-1017 is 3 months newer than Inkling.
Oct 17, 2026
2 days ago
2mo newerJul 21, 2026
3 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-V4.1-Flash-1017 is available from DeepSeek. Inkling is available from DeepInfra.
DeepSeek-V4.1-Flash-1017
Inkling
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and Inkling side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs Inkling.