DeepSeek-V3.1 vs Kimi K2 Instruct
Wins 4 of 6 areas
Coding · Reasoning · Facts · Long documents
Wins 1 of 6 areas
Following instructions
DeepSeek-V3.1 is the stronger all-rounder.Kimi K2 Instruct is better at following instructions.
Scores updated · 34 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- CodingWriting and fixing software30DeepSeek-V3.13 of 4 tests · 1 tie
- ReasoningHard problems that need careful thinking30DeepSeek-V3.13 of 3 tests
- FactsGetting facts right instead of making them up21DeepSeek-V3.12 of 3 tests
- Long documentsFinding answers in very long texts10DeepSeek-V3.11 of 1 test
- Following instructionsDoing exactly what it is asked01Kimi K2 Instruct1 of 2 tests · 1 tie
- AgentsCarrying out multi-step tasks on its own11Even1 each
Long documents rests on a single test.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
DeepSeek-V3.1 costs 28% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where DeepSeek-V3.1 pulls ahead
- Finds hard-to-locate facts by browsing the webBrowseComp+15.9points ahead
- Code for real scientific research problemsSciCode+8.4points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+7.9points ahead
Where Kimi K2 Instruct pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+12.8points ahead
- Real work tasks from 44 professionsGDPVal+12.6points ahead
- Keeps track of context across a multi-turn chatMulti-Challenge+8points ahead
Every test, side by side
All 34 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-V3.1
- SciCodeDeepSeek-V3.1 by 8.439.130.7+8.4
- SWE-bench MultilingualDeepSeek-V3.1 by 7.254.547.3+7.2
- Terminal-Bench HardDeepSeek-V3.1 by 1.52523.5+1.5
- SWE-bench Verifiedtie6665.8tie
AgentsEven
- BrowseCompDeepSeek-V3.1 by 15.93014.1+15.9
- GDPValKimi K2 Instruct by 12.65.618.2+12.6
ReasoningDeepSeek-V3.1
- Humanity's Last ExamDeepSeek-V3.1 by 7.914.36.4+7.9
- CritPtDeepSeek-V3.1 by 220+2
- GPQA DiamondDeepSeek-V3.1 by 1.277.976.7+1.2
FactsDeepSeek-V3.1
- AA-Omniscience · Non-hallucinationKimi K2 Instruct by 12.817.530.3+12.8
- Vectara HHEM hallucination ratelower is betterDeepSeek-V3.1 by 12.45.517.9+12.4
- AA-Omniscience · AccuracyDeepSeek-V3.1 by 3.62925.4+3.6
Following instructionsKimi K2 Instruct
- Multi-ChallengeKimi K2 Instruct by 846.154.1+8
- IFBenchtie41.541.7tie
Other results19 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- SimpleQADeepSeek-V3.1 by 62.493.431+62.4
- τ²-Bench Telecom (AA run)Kimi K2 Instruct by 3637.473.4+36
- AIME 2024DeepSeek-V3.1 by 23.593.169.6+23.5
- BrowseComp-ZHDeepSeek-V3.1 by 20.449.228.8+20.4
- AA Agentic IndexKimi K2 Instruct by 18.818.937.7+18.8
- vectara_factual_consistencyDeepSeek-V3.1 by 12.494.582.1+12.4
- SWE-Dev (Tools-allowed)Kimi K2 Instruct by 8.653.361.9+8.6
- Aider-PolyglotDeepSeek-V3.1 by 8.468.460+8.4
- HMMT 2025Kimi K2 Instruct by 5.333.538.8+5.3
- vectara_avg_summary_lengthDeepSeek-V3.1 by 4.563.759.2+4.5
- vectara_answer_rateKimi K2 Instruct by 4.194.598.6+4.1
- Artificial Analysis Coding IndexDeepSeek-V3.1 by 3.829.725.9+3.8
- AA-OmniscienceKimi K2 Instruct by 3-29.6-26.6+3
- LiveCodeBenchDeepSeek-V3.1 by 2.756.453.7+2.7
- MMLU-ProDeepSeek-V3.1 by 2.683.781.1+2.6
- AA IntelligenceKimi K2 Instruct by 1.813.515.3+1.8
- Terminal-BenchDeepSeek-V3.1 by 1.331.330+1.3
- MMLU-Reduxtie91.892.7tie
- AIME 2025tie49.849.5tie
Questions people ask
Which is better, DeepSeek-V3.1 or Kimi K2 Instruct?
DeepSeek-V3.1 wins four of the six areas where both have results: coding, reasoning, facts and long documents. Kimi K2 Instruct wins following instructions. They are level on agents.
Which is better for coding?
DeepSeek-V3.1. It wins 3 of the 4 coding tests both models report; Kimi K2 Instruct wins none, and 1 is a tie.
Which is cheaper?
DeepSeek-V3.1 costs $0.56 per million input tokens and $1.68 per million output tokens; Kimi K2 Instruct costs $0.60 and $2.50. That makes DeepSeek-V3.1 about 28% cheaper for the same work.
How do you compare the two?
We use the 34 benchmark tests both models have published scores on. The verdict counts the 15 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 19 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.