Model comparison
DeepSeek V4 Flash (High) vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 21 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash (High) #92 (Estimated); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Flash (High) and Kimi K2.5 (Reasoning) share 21 comparable benchmark results. 3 of 8 categories are comparable. 17 results are unique to DeepSeek V4 Flash (High); 6 to Kimi K2.5 (Reasoning).
Updated July 23, 2026- Shared results
- 21
- DeepSeek V4 Flash (High) only
- 17
- Kimi K2.5 (Reasoning) only
- 6
- Comparable categories
- 3 / 8
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. DeepSeek V4 Flash (High) only becomes the better choice if agentic is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Kimi K2.5 (Reasoning) is clearly ahead on the BenchAlign aggregate, 59.35 to 53.95. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 87.2 against 52.1. The single biggest benchmark swing on the page is BrowseComp, 53.5% to 60.6%. DeepSeek V4 Flash (High) does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Kimi K2.5 (Reasoning) is also the more expensive model on tokens at $0.60 input / $3.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (High). That is roughly 10.7x on output cost alone. DeepSeek V4 Flash (High) gives you the larger context window at 1M, compared with 128K for Kimi K2.5 (Reasoning).
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 Flash (High) | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash (High)52.1 | Margin→ 35.1 | Kimi K2.5 (Reasoning)87.2 |
| Coding | DeepSeek V4 Flash (High)68.5 | Margin→ 8.3 | Kimi K2.5 (Reasoning)76.8 |
| Agentic | DeepSeek V4 Flash (High)55.3 | Margin← 0.3 | Kimi K2.5 (Reasoning)55.0 |
| Math | DeepSeek V4 Flash (High)91.9 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Multimodal | DeepSeek V4 Flash (High)Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)78.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 53.5%B 60.6%Winner: Kimi K2.5 (Reasoning)Δ 7.1BrowseComp: DeepSeek V4 Flash (High) scored 53.5%; Kimi K2.5 (Reasoning) scored 60.6%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 56.6%B 50.8%Winner: DeepSeek V4 Flash (High)Δ 5.8Terminal-Bench 2.0: DeepSeek V4 Flash (High) scored 56.6%; Kimi K2.5 (Reasoning) scored 50.8%. DeepSeek V4 Flash (High) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 78.6%B 76.8%Winner: DeepSeek V4 Flash (High)Δ 1.8SWE-bench Verified: DeepSeek V4 Flash (High) scored 78.6%; Kimi K2.5 (Reasoning) scored 76.8%. DeepSeek V4 Flash (High) wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 86.4%B 87.1%Winner: Kimi K2.5 (Reasoning)Δ 0.7MMLU-Pro: DeepSeek V4 Flash (High) scored 86.4%; Kimi K2.5 (Reasoning) scored 87.1%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
GPQA
KnowledgeA 87.4%B 87.6%Winner: Kimi K2.5 (Reasoning)Δ 0.2GPQA: DeepSeek V4 Flash (High) scored 87.4%; Kimi K2.5 (Reasoning) scored 87.6%. Kimi K2.5 (Reasoning) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Flash (High) | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash (High)$0.14 input / $0.28 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | DeepSeek V4 Flash (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Flash (High)Not available | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Flash (High)Not available | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash (High)1M | Kimi K2.5 (Reasoning)128K | DeepSeek V4 Flash (High) lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Flash (High) wins11 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.6% | 50.8% | DeepSeek V4 Flash (High) leads |
| BrowseCompSource | 53.5% | 60.6% | Kimi K2.5 (Reasoning) leads |
| HLE w/ toolsSource | 40.3% | — | Not comparable |
| MCP AtlasSource | 67.4% | — | Not comparable |
| ToolathlonSource | 43.5% | — | Not comparable |
| τ²-bench resultsSource | 95.6% | 95.9% | Kimi K2.5 (Reasoning) leads |
| AA Agentic IndexSource | 28.2% | 21.7% | DeepSeek V4 Flash (High) leads |
| GDPval-AASource | 32.4% | 25.4% | DeepSeek V4 Flash (High) leads |
| GDPval-AASource | 1147 | 1009 | DeepSeek V4 Flash (High) leads |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| Gert LabsSource | — | 32.58% | Not comparable |
CodingKimi K2.5 (Reasoning) wins8 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| CodeforcesSource | 2816.0 | — | Not comparable |
| SWE-bench VerifiedSource | 78.6% | 76.8% | DeepSeek V4 Flash (High) leads |
| SWE-bench ProSource | 52.3% | — | Not comparable |
| SWE MultilingualSource | 70.2% | — | Not comparable |
| Terminal-Bench 2.0Source | 56.6% | — | Not comparable |
| AA-SciCodeSource | 42.0% | 49.0% | Kimi K2.5 (Reasoning) leads |
| AA Coding IndexSource | 52.0% | 46.8% | DeepSeek V4 Flash (High) leads |
| Vibe Code BenchSource | — | 17.54% | Not comparable |
Reasoning4 benchmarks
KnowledgeKimi K2.5 (Reasoning) wins12 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| MMLU-ProSource | 86.4% | 87.1% | Kimi K2.5 (Reasoning) leads |
| SimpleQASource | 28.9% | — | Not comparable |
| Chinese-SimpleQASource | 73.2% | — | Not comparable |
| GPQASource | 87.4% | 87.6% | Kimi K2.5 (Reasoning) leads |
| GPQA-DSource | 87.4% | — | Not comparable |
| HLESource | 29.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 37.5% | 35.4% | DeepSeek V4 Flash (High) leads |
| AA-GPQA DiamondSource | 86.7% | 87.9% | Kimi K2.5 (Reasoning) leads |
| AA-HLESource | 27.8% | 29.4% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience IndexSource | -22.3% | -8.1% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience AccuracySource | 35.5% | 34.3% | DeepSeek V4 Flash (High) leads |
| AA-Omniscience Hallucination RateSource | 89.7% | 64.6% | Kimi K2.5 (Reasoning) leads |
Math5 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash (High) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.5% | 70.2% | DeepSeek V4 Flash (High) leads |
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Flash (High) or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) is ahead on BenchLM's BenchAlign leaderboard, 59.35 to 53.95. The biggest single separator in this matchup is BrowseComp, where the scores are 53.5% and 60.6%.
Which is better for knowledge tasks, DeepSeek V4 Flash (High) or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.2 versus 52.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash (High) or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 68.5. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash (High) or Kimi K2.5 (Reasoning)?
DeepSeek V4 Flash (High) has the edge for agentic tasks in this comparison, averaging 55.3 versus 55. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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