Model comparison
DeepSeek V4 Flash vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 6 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Flash #61 (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 and Kimi K2.5 (Reasoning) share 6 comparable benchmark results. 3 of 8 categories are comparable. 16 results are unique to DeepSeek V4 Flash; 21 to Kimi K2.5 (Reasoning).
Updated July 23, 2026- Shared results
- 6
- DeepSeek V4 Flash only
- 16
- Kimi K2.5 (Reasoning) only
- 21
- Comparable categories
- 3 / 8
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 4 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) has the cleaner BenchAlign overall profile here, landing at 59.35 versus 58.88. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
Kimi K2.5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 87.2 against 38.8. The single biggest benchmark swing on the page is GPQA, 71.2% to 87.6%.
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. That is roughly 10.7x on output cost alone. Kimi K2.5 (Reasoning) is the reasoning model in the pair, while DeepSeek V4 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. DeepSeek V4 Flash 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 | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Knowledge | DeepSeek V4 Flash38.8 | Margin→ 48.4 | Kimi K2.5 (Reasoning)87.2 |
| Coding | DeepSeek V4 Flash64.2 | Margin→ 12.6 | Kimi K2.5 (Reasoning)76.8 |
| Agentic | DeepSeek V4 Flash49.1 | Margin→ 5.9 | Kimi K2.5 (Reasoning)55.0 |
| Math | DeepSeek V4 Flash40.8 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Multimodal | DeepSeek V4 FlashNot 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 ↗
GPQA
KnowledgeA 71.2%B 87.6%Winner: Kimi K2.5 (Reasoning)Δ 16.4GPQA: DeepSeek V4 Flash scored 71.2%; Kimi K2.5 (Reasoning) scored 87.6%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
MMLU-Pro
KnowledgeA 83%B 87.1%Winner: Kimi K2.5 (Reasoning)Δ 4.1MMLU-Pro: DeepSeek V4 Flash scored 83%; Kimi K2.5 (Reasoning) scored 87.1%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 73.7%B 76.8%Winner: Kimi K2.5 (Reasoning)Δ 3.1SWE-bench Verified: DeepSeek V4 Flash scored 73.7%; Kimi K2.5 (Reasoning) scored 76.8%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 49.1%B 50.8%Winner: Kimi K2.5 (Reasoning)Δ 1.7Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; Kimi K2.5 (Reasoning) scored 50.8%. 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 | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Flash$0.14 input / $0.28 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | DeepSeek V4 Flash has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 FlashNot available | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 FlashNot available | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Flash1M | Kimi K2.5 (Reasoning)128K | DeepSeek V4 Flash lists the larger context window. |
Benchmark Deep Dive
AgenticKimi K2.5 (Reasoning) wins11 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.1% | 50.8% | Kimi K2.5 (Reasoning) leads |
| MCP AtlasSource | 64% | — | Not comparable |
| ToolathlonSource | 40.7% | — | Not comparable |
| Claw-EvalSource | 57.8% | — | Not comparable |
| Gert LabsSource | 54.35% | 32.58% | DeepSeek V4 Flash leads |
| BrowseCompSource | — | 60.6% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| AA Agentic IndexSource | — | 21.7% | Not comparable |
| GDPval-AASource | — | 25.4% | Not comparable |
| GDPval-AASource | — | 1009 | Not comparable |
CodingKimi K2.5 (Reasoning) wins7 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.7% | 76.8% | Kimi K2.5 (Reasoning) leads |
| SWE-bench ProSource | 49.1% | — | Not comparable |
| SWE MultilingualSource | 69.7% | — | Not comparable |
| Terminal-Bench 2.0Source | 49.1% | — | Not comparable |
| Vibe Code BenchSource | — | 17.54% | Not comparable |
| AA-SciCodeSource | — | 49.0% | Not comparable |
| AA Coding IndexSource | — | 46.8% | Not comparable |
Reasoning4 benchmarks
KnowledgeKimi K2.5 (Reasoning) wins12 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| MMLU-ProSource | 83% | 87.1% | Kimi K2.5 (Reasoning) leads |
| SimpleQASource | 23.1% | — | Not comparable |
| Chinese-SimpleQASource | 71.5% | — | Not comparable |
| GPQASource | 71.2% | 87.6% | Kimi K2.5 (Reasoning) leads |
| GPQA-DSource | 71.2% | — | Not comparable |
| HLESource | 8.1% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 35.4% | Not comparable |
| AA-GPQA DiamondSource | — | 87.9% | Not comparable |
| AA-HLESource | — | 29.4% | Not comparable |
| AA-Omniscience IndexSource | — | -8.1% | Not comparable |
| AA-Omniscience AccuracySource | — | 34.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 64.6% | Not comparable |
Math5 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Flash | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 70.2% | Not comparable |
Frequently Asked Questions (4)
Which is better, DeepSeek V4 Flash or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) is ahead on BenchLM's BenchAlign leaderboard, 59.35 to 58.88. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 87.6%.
Which is better for knowledge tasks, DeepSeek V4 Flash or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.2 versus 38.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Flash or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 64.2. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Flash or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 55 versus 49.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.