Kimi K2.6 vs Ling-3.0-flash
Wins 7 of 7 areas
Coding · Agents · Reasoning · Facts · Math · Long documents · Following instructions
Wins 0 of 7 areas
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Kimi K2.6 is the stronger all-rounder.Ling-3.0-flash is cheaper.
Scores updated · 26 tests both models report · How we compare
Where each one wins
Tests won in each of the seven 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 software50Kimi K2.65 of 5 tests
- ReasoningHard problems that need careful thinking30Kimi K2.63 of 3 tests
- MathCompetition and research-level math30Kimi K2.63 of 3 tests
- AgentsCarrying out multi-step tasks on its own31Kimi K2.63 of 5 tests · 1 tie
- FactsGetting facts right instead of making them up20Kimi K2.62 of 2 tests
- Long documentsFinding answers in very long texts10Kimi K2.61 of 1 test
- Following instructionsDoing exactly what it is asked10Kimi K2.61 of 1 test
Long documents and following instructions rest on a single test each.
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.
Ling-3.0-flash costs 94% less for the same work.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where Kimi K2.6 pulls ahead
- Answers hard knowledge questions correctlyAA-Omniscience · Accuracy+14.4points ahead
- Finds hard-to-locate facts by browsing the webBrowseComp+14.1points ahead
- Very hard expert questions across many subjectsHumanity's Last Exam+13.8points ahead
Where Ling-3.0-flash pulls ahead
- Customer-service tasks in a simulated bankτ-Bench V3 · Banking+3.9points ahead
Every test, side by side
All 26 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingKimi K2.6
- Terminal-Bench 2.1Kimi K2.6 by 10.565.955.4+10.5
- SciCodeKimi K2.6 by 9.551.542+9.5
- LiveCodeBench v6Kimi K2.6 by 6.889.682.8+6.8
- SWE-bench MultilingualKimi K2.6 by 4.376.772.4+4.3
- SWE-bench ProKimi K2.6 by 258.656.6+2
AgentsKimi K2.6
- BrowseCompKimi K2.6 by 14.186.372.2+14.1
- GDPValKimi K2.6 by 4.62722.4+4.6
- τ-Bench V3 · BankingLing-3.0-flash by 3.923.327.2+3.9
- MCP AtlasKimi K2.6 by 2.668.165.5+2.6
- Terminal-Bench 4.0tie0.50tie
ReasoningKimi K2.6
- Humanity's Last ExamKimi K2.6 by 13.837.523.7+13.8
- CritPtKimi K2.6 by 6.381.7+6.3
- GPQA DiamondKimi K2.6 by 5.691.185.5+5.6
FactsKimi K2.6
- AA-Omniscience · AccuracyKimi K2.6 by 14.432.618.2+14.4
- AA-Omniscience · Non-hallucinationKimi K2.6 by 3.659.555.9+3.6
MathKimi K2.6
- HMMT Feb. 2026Kimi K2.6 by 5.792.787+5.7
- AIME 2026Kimi K2.6 by 3.296.493.2+3.2
- IMOAnswerBenchKimi K2.6 by 2.38683.7+2.3
Other results6 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.
- AA-OmniscienceKimi K2.6 by 23.25.3-17.9+23.2
- Artificial Analysis Coding IndexKimi K2.6 by 11.261.850.6+11.2
- τ³-Bench BankingLing-3.0-flash by 7.420.628+7.4
- WideSearchKimi K2.6 by 7.280.873.6+7.2
- AA IntelligenceKimi K2.6 by 6.92720.1+6.9
- AA Agentic IndexKimi K2.6 by 1.122.121+1.1
Questions people ask
Which is better, Kimi K2.6 or Ling-3.0-flash?
Kimi K2.6 wins all seven areas where both have results: coding, agents, reasoning, facts, math, long documents and following instructions. Ling-3.0-flash wins none, but costs 94% less.
Which is better for coding?
Kimi K2.6. It wins 5 of the 5 coding tests both models report; Ling-3.0-flash wins none.
Which is cheaper?
Kimi K2.6 costs $0.95 per million input tokens and $4.00 per million output tokens; Ling-3.0-flash costs $0.07 and $0.22. That makes Ling-3.0-flash about 94% cheaper for the same work.
How do you compare the two?
We use the 26 benchmark tests both models have published scores on. The verdict counts the 20 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 6 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.