Model comparison
DeepSeek V4 Pro (High) vs Kimi K2.6
Head-to-head evidence from 28 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (High) #81 (Estimated); Kimi K2.6 #74 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and Kimi K2.6 share 28 comparable benchmark results. 4 of 8 categories are comparable. 10 results are unique to DeepSeek V4 Pro (High); 23 to Kimi K2.6.
Updated July 23, 2026- Shared results
- 28
- DeepSeek V4 Pro (High) only
- 10
- Kimi K2.6 only
- 23
- Comparable categories
- 4 / 8
Pick Kimi K2.6 if you want the stronger benchmark profile. DeepSeek V4 Pro (High) only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 28 shared benchmark results across 7 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.6 has the cleaner BenchAlign overall profile here, landing at 56.79 versus 55.47. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Kimi K2.6's sharpest advantage is in agentic, where it averages 73.5 against 70.6. The single biggest benchmark swing on the page is SWE-bench Pro, 54.4% to 58.6%. DeepSeek V4 Pro (High) does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Kimi K2.6 is also the more expensive model on tokens at $0.95 input / $4.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (High). That is roughly 4.6x on output cost alone. DeepSeek V4 Pro (High) gives you the larger context window at 1M, compared with 256K for Kimi K2.6.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V4 Pro (High) | Δ | Kimi K2.6 |
|---|---|---|---|
| Math | DeepSeek V4 Pro (High)94.0 | Margin← 26.9 | Kimi K2.667.1 |
| Knowledge | DeepSeek V4 Pro (High)57.0 | Margin← 14.8 | Kimi K2.642.2 |
| Coding | DeepSeek V4 Pro (High)69.8 | Margin← 5.4 | Kimi K2.664.4 |
| Agentic | DeepSeek V4 Pro (High)70.6 | Margin→ 2.9 | Kimi K2.673.5 |
| Multimodal | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | Kimi K2.679.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Pro
CodingA 54.4%B 58.6%Winner: Kimi K2.6Δ 4.2SWE-bench Pro: DeepSeek V4 Pro (High) scored 54.4%; Kimi K2.6 scored 58.6%. Kimi K2.6 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 63.3%B 66.7%Winner: Kimi K2.6Δ 3.4Terminal-Bench 2.0: DeepSeek V4 Pro (High) scored 63.3%; Kimi K2.6 scored 66.7%. Kimi K2.6 wins this benchmark. - Source ↗
BrowseComp
AgenticA 80.4%B 83.2%Winner: Kimi K2.6Δ 2.8BrowseComp: DeepSeek V4 Pro (High) scored 80.4%; Kimi K2.6 scored 83.2%. Kimi K2.6 wins this benchmark. - Source ↗
GPQA
KnowledgeA 89.1%B 90.5%Winner: Kimi K2.6Δ 1.4GPQA: DeepSeek V4 Pro (High) scored 89.1%; Kimi K2.6 scored 90.5%. Kimi K2.6 wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 94.0%B 92.7%Winner: DeepSeek V4 Pro (High)Δ 1.3HMMT Feb 2026: DeepSeek V4 Pro (High) scored 94.0%; Kimi K2.6 scored 92.7%. DeepSeek V4 Pro (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (High) | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | Kimi K2.6$0.95 input / $4 output | DeepSeek V4 Pro (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | Kimi K2.6256K | DeepSeek V4 Pro (High) lists the larger context window. |
Benchmark Deep Dive
AgenticKimi K2.6 wins18 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | 66.7% | Kimi K2.6 leads |
| BrowseCompSource | 80.4% | 83.2% | Kimi K2.6 leads |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | 55.9% | DeepSeek V4 Pro (High) leads |
| ToolathlonSource | 49% | 50% | Kimi K2.6 leads |
| τ²-bench resultsSource | 94.2% | 95.9% | Kimi K2.6 leads |
| GDPval-AASource | 39.9% | 34.5% | DeepSeek V4 Pro (High) leads |
| GDPval-AASource | 1299 | 1189 | DeepSeek V4 Pro (High) leads |
| AA Agentic IndexSource | 34.4% | 30.3% | DeepSeek V4 Pro (High) leads |
| OSWorld-VerifiedSource | — | 73.1% | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| DeepSearchQASource | — | 92.5% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| APEX-Agents-AASource | — | 28.5% | Not comparable |
| Gert LabsSource | — | 56.82% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| terminalBenchHardSource | — | 43.9% | Not comparable |
CodingDeepSeek V4 Pro (High) wins11 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | 80.2% | Kimi K2.6 leads |
| SWE-bench ProSource | 54.4% | 58.6% | Kimi K2.6 leads |
| SWE MultilingualSource | 74.1% | 76.7% | Kimi K2.6 leads |
| Terminal-Bench 2.0Source | 63.3% | 66.7% | Kimi K2.6 leads |
| AA-SciCodeSource | 46.4% | 53.5% | Kimi K2.6 leads |
| AA Coding IndexSource | 58.7% | 61.8% | Kimi K2.6 leads |
| LiveCodeBench v6Source | — | 89.6% | Not comparable |
| SciCodeSource | — | 52.2% | Not comparable |
| Vibe Code BenchSource | — | 37.89% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
Reasoning4 benchmarks
KnowledgeDeepSeek V4 Pro (High) wins12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | — | Not comparable |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | 90.5% | Kimi K2.6 leads |
| GPQA-DSource | 89.1% | 90.5% | Kimi K2.6 leads |
| HLESource | 34.5% | 34.7% | Kimi K2.6 leads |
| Artificial Analysis Intelligence IndexSource | 43.1% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 90.5% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 33.5% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -9.7% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 41.8% | 32.8% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 39.3% | Kimi K2.6 leads |
MathDeepSeek V4 Pro (High) wins8 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 94.0% | 92.7% | DeepSeek V4 Pro (High) leads |
| IMOAnswerBenchSource | 88.0% | — | Not comparable |
| ApexSource | 27.4% | — | Not comparable |
| Apex ShortlistSource | 85.5% | — | Not comparable |
| AIME26Source | — | 96.4% | Not comparable |
| MMAnswerBenchSource | — | 86.0% | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | — | 38.966% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 14.580% | Not comparable |
Multimodal7 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | 1306 | Kimi K2.6 leads |
| MMMU-ProSource | — | 79.4% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| CharXivSource | — | 80.4% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 79.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.3% | 76.0% | Kimi K2.6 leads |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Pro (High) or Kimi K2.6?
Kimi K2.6 is ahead on BenchLM's BenchAlign leaderboard, 56.79 to 55.47. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 54.4% and 58.6%.
Which is better for knowledge tasks, DeepSeek V4 Pro (High) or Kimi K2.6?
DeepSeek V4 Pro (High) has the edge for knowledge tasks in this comparison, averaging 57 versus 42.2. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro (High) or Kimi K2.6?
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 69.8 versus 64.4. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro (High) or Kimi K2.6?
DeepSeek V4 Pro (High) has the edge for math in this comparison, averaging 94 versus 67.1. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro (High) or Kimi K2.6?
Kimi K2.6 has the edge for agentic tasks in this comparison, averaging 73.5 versus 70.6. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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