Kimi K2.6 vs DeepSeek V4

The two open-weight coding models that reset the price-performance curve in April 2026 — compared head to head.

Short answer: Choose DeepSeek V4 for the largest context window (1M tokens), a pure MIT licence and the cheapest tier (V4-Flash at $0.14/$0.28). Choose Kimi K2.6 for native multimodal input and a strong, well-priced top tier. Both are open-weight and frontier-class at coding.

Kimi K2.6 vs DeepSeek V4: side-by-side

 Kimi K2.6DeepSeek V4-Pro
MakerMoonshot AIDeepSeek
Released20 April 202624 April 2026
ArchitectureMoE · 1T params · 32B activeMoE · 1.6T params · 49B active
Context window262,144 tokens1,000,000 tokens
ModalitiesText, images, videoText
API price (per 1M)$0.60 in / $2.50 out$1.74 in / $3.48 out
LicenceModified MIT — open weightsMIT — open weights
Cheapest tierV4-Flash · $0.14 / $0.28

Benchmark comparison

Both models are elite at coding, but they publish results on different test variants — so read the numbers as parallel strengths, not a direct race.

BenchmarkKimi K2.6DeepSeek V4-Pro
SWE-bench Pro58.6%
SWE-bench Verified80.6%
Codeforces rating3,206
Humanity's Last Exam (tools)54.0%

Key takeaway

DeepSeek V4-Pro's 3,206 Codeforces rating is the highest competitive-programming score of any model at release. Kimi K2.6 ties GPT-5.5 on SWE-bench Pro and leads on Humanity's Last Exam with tools. Both punch at the frontier from the open-weight side.

Price comparison

This is close, with a twist. On the top tier, Kimi K2.6 ($0.60/$2.50) undercuts DeepSeek V4-Pro ($1.74/$3.48) on input and is comparable on output. But DeepSeek also offers V4-Flash at $0.14/$0.28 — the cheapest capable model in this comparison by a wide margin. If absolute lowest cost is the goal and you can use a smaller model, V4-Flash wins; if you want the strongest single model cheaply, Kimi K2.6 is the value pick.

Licensing

Both ship open weights, with one difference. DeepSeek V4 uses a standard, unconditional MIT licence. Kimi K2.6 uses a modified MIT licence that behaves identically for almost everyone — the only added clause requires displaying "Kimi K2" branding if your product exceeds 100 million monthly active users or $20 million in monthly revenue. For the vast majority of teams, both are effectively unrestricted.

Which should you use?

Full Kimi K2.6 overview   Full DeepSeek V4 overview

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Frequently asked questions

Is Kimi K2.6 better than DeepSeek V4?

Both are frontier-class open-weight coding models. Kimi K2.6 scores 58.6% on SWE-bench Pro and is cheaper on its top tier. DeepSeek V4-Pro scores 80.6% on SWE-bench Verified and has the highest Codeforces rating of any model at release (3,206), plus a larger 1M-token context window. They are measured on different test variants, so neither is a clean winner.

Which is cheaper?

DeepSeek V4-Flash is the cheapest at $0.14 / $0.28 per million input/output tokens. Kimi K2.6 costs $0.60 / $2.50 on Moonshot's official API. DeepSeek V4-Pro costs $1.74 / $3.48 — so for the top tier, Kimi K2.6 is cheaper on input but comparable on output.

Which has a bigger context window?

DeepSeek V4 has the bigger context window: 1 million tokens versus Kimi K2.6's 262,144 tokens.

Are both open source?

Both have open weights. DeepSeek V4 uses a standard MIT licence. Kimi K2.6 uses a modified MIT licence that adds a branding requirement only for products above 100 million monthly active users or $20 million in monthly revenue.