DeepSeek-V4.1-Flash-1017 vs Kimi K3
DeepSeek-V4.1-Flash-1017 and Kimi K3 are closely matched at 51.0 and 51.8 on the LLM Stats Score. DeepSeek-V4.1-Flash-1017 is 10.9x cheaper per token.
DeepSeek · Moonshot AI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 and Kimi K3 are closely matched on the overall LLM Stats Score at 51.0 and 51.8.
In the 6 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash-1017 is roughly 10.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4.1-Flash-1017
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- cost matters — it's about 10.9x cheaper per token
- you want the most recent training data — it shipped Oct 2026
Choose Kimi K3
- you want predictable pricing at $2.85/M input and $14.25/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 · 31 for Kimi K3
DeepSeek-V4.1-Flash-1017 outperforms in 4 benchmarks (AutomationBench, BabyVision, DeepSWE 1.1, ZEROBench), while Kimi K3 is better at 2 benchmarks (Humanity's Last Exam, Program Bench).
DeepSeek-V4.1-Flash-1017 shows notably better performance in the majority of 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 9.5x cheaper than Kimi K3 ($2.85/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 11.9x cheaper than Kimi K3 ($14.25/1M tokens).
In conclusion, Kimi K3 is more expensive than DeepSeek-V4.1-Flash-1017.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2036.8B more parameters than DeepSeek-V4.1-Flash-1017, making it 266.9% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Kimi K3 can generate longer responses up to 1,048,576 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 Kimi K3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
Kimi K3
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Kimi K3 was released on 2026-07-16.
DeepSeek-V4.1-Flash-1017 is 3 months newer than Kimi K3.
Oct 17, 2026
0 days ago
3mo newerJul 16, 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. Kimi K3 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
DeepSeek-V4.1-Flash-1017
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs Kimi K3.
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