Model comparison
DeepSeek V3.1 (Reasoning) vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V3.1 (Reasoning) #97 (Supported); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.1 (Reasoning) and Kimi K2.5 (Reasoning) share 12 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeek V3.1 (Reasoning); 15 to Kimi K2.5 (Reasoning).
Updated July 22, 2026- Shared results
- 12
- DeepSeek V3.1 (Reasoning) only
- 0
- Kimi K2.5 (Reasoning) only
- 15
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3.1 (Reasoning) and Kimi K2.5 (Reasoning) is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K2.5 (Reasoning) is priced at $0.60 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeek V3.1 (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 V3.1 (Reasoning) | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Agentic | DeepSeek V3.1 (Reasoning)Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)55.0 |
| Coding | DeepSeek V3.1 (Reasoning)Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)76.8 |
| Knowledge | DeepSeek V3.1 (Reasoning)Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)87.2 |
| Multimodal | DeepSeek V3.1 (Reasoning)Not measured | MarginNo overlap | Kimi K2.5 (Reasoning)78.5 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.1 (Reasoning) | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.1 (Reasoning)$0 input / $0 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | DeepSeek V3.1 (Reasoning) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.1 (Reasoning)Not available | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.1 (Reasoning)Not available | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.1 (Reasoning)128K | Kimi K2.5 (Reasoning)128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | DeepSeek V3.1 (Reasoning) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| τ²-bench resultsSource | 37.4% | 95.9% | Kimi K2.5 (Reasoning) leads |
| Terminal-Bench 2.0Source | — | 50.8% | Not comparable |
| BrowseCompSource | — | 60.6% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| Gert LabsSource | — | 32.58% | Not comparable |
| AA Agentic IndexSource | — | 21.7% | Not comparable |
| GDPval-AASource | — | 25.4% | Not comparable |
| GDPval-AASource | — | 1009 | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | DeepSeek V3.1 (Reasoning) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 20.7% | 35.4% | Kimi K2.5 (Reasoning) leads |
| AA-GPQA DiamondSource | 77.9% | 87.9% | Kimi K2.5 (Reasoning) leads |
| AA-HLESource | 13.0% | 29.4% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience IndexSource | -28.4% | -8.1% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience AccuracySource | 28.8% | 34.3% | Kimi K2.5 (Reasoning) leads |
| AA-Omniscience Hallucination RateSource | 80.3% | 64.6% | Kimi K2.5 (Reasoning) leads |
| GPQASource | — | 87.6% | Not comparable |
| MMLU-ProSource | — | 87.1% | Not comparable |
Math1 benchmarks
| Benchmark | DeepSeek V3.1 (Reasoning) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AIME 2025Source | — | 96.1% | Not comparable |
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.1 (Reasoning) | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 41.5% | 70.2% | Kimi K2.5 (Reasoning) leads |
Frequently Asked Questions (3)
Can I compare DeepSeek V3.1 (Reasoning) and Kimi K2.5 (Reasoning) on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for DeepSeek V3.1 (Reasoning) and Kimi K2.5 (Reasoning) today?
DeepSeek V3.1 (Reasoning): $0.00 input / $0.00 output per 1M tokens Kimi K2.5 (Reasoning): $0.60 input / $3.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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