Model Comparison
DeepSeek-V4-Flash-0731 vs Kimi K3Which is better in 2026?
Kimi K3 significantly outperforms across most benchmarks. DeepSeek-V4-Flash-0731 is 53.3x cheaper per token.
Verdict: DeepSeek-V4-Flash-0731 vs Kimi K3 — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Kimi K3 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-V4-Flash-0731 outperforms in 0 benchmarks, while Kimi K3 is better at 4 benchmarks (AutomationBench, DeepSWE, Terminal-Bench 2.1, Toolathlon). Kimi K3 significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-0731 is roughly 53.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose DeepSeek-V4-Flash-0731 if…
- cost matters — it's about 53.3x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Kimi K3 if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 outperforms in 0 benchmarks, while Kimi K3 is better at 4 benchmarks (AutomationBench, DeepSWE, Terminal-Bench 2.1, Toolathlon).
Kimi K3 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 33.3x cheaper than Kimi K3 ($3.00/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 83.3x cheaper than Kimi K3 ($15.00/1M tokens).
In conclusion, Kimi K3 is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 2496.0B more parameters than DeepSeek-V4-Flash-0731, making it 821.1% 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-Flash-0731 is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Kimi K3 supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Kimi K3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Kimi K3
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while Kimi K3 was released on 2026-07-16.
DeepSeek-V4-Flash-0731 is 1 month newer than Kimi K3.
Jul 31, 2026
3 days ago
2w newerJul 16, 2026
2 weeks 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-Flash-0731 is available from DeepInfra, Fireworks, Novita. Kimi K3 is available from Fireworks, Moonshot AI, Novita, Together.
DeepSeek-V4-Flash-0731
Kimi K3
Outputs Comparison
Key Takeaways
Kimi K3
View detailsMoonshot AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Kimi K3 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Kimi K3.