Model comparison
GPT-5.2 vs Kimi K2.5 (Reasoning)
Head-to-head evidence from 18 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2 #64 (Estimated); Kimi K2.5 (Reasoning) #57 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2 and Kimi K2.5 (Reasoning) share 18 comparable benchmark results. 4 of 8 categories are comparable. 10 results are unique to GPT-5.2; 9 to Kimi K2.5 (Reasoning).
Updated July 20, 2026- Shared results
- 18
- GPT-5.2 only
- 10
- Kimi K2.5 (Reasoning) only
- 9
- Comparable categories
- 4 / 8
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. GPT-5.2 only becomes the better choice if knowledge is the priority or you need the larger 400K context window.
Confidence note. This is a partial-evidence comparison with 18 shared benchmark results across 6 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 K2.5 (Reasoning) has the cleaner BenchAlign overall profile here, landing at 59.35 versus 58.43. 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 coding, where it averages 76.8 against 70.6. The single biggest benchmark swing on the page is BrowseComp, 65.8% to 60.6%. GPT-5.2 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.60 input / $3.00 output per 1M tokens for Kimi K2.5 (Reasoning). That is roughly 4.7x on output cost alone. GPT-5.2 gives you the larger context window at 400K, 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 | GPT-5.2 | Δ | Kimi K2.5 (Reasoning) |
|---|---|---|---|
| Coding | GPT-5.270.6 | Margin→ 6.2 | Kimi K2.5 (Reasoning)76.8 |
| Knowledge | GPT-5.292.4 | Margin← 5.2 | Kimi K2.5 (Reasoning)87.2 |
| Multimodal | GPT-5.280.4 | Margin← 1.9 | Kimi K2.5 (Reasoning)78.5 |
| Agentic | GPT-5.255.7 | Margin← 0.7 | Kimi K2.5 (Reasoning)55.0 |
| Reasoning | GPT-5.252.9 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
| Math | GPT-5.235.2 | MarginNo overlap | Kimi K2.5 (Reasoning)Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 65.8%B 60.6%Winner: GPT-5.2Δ 5.2BrowseComp: GPT-5.2 scored 65.8%; Kimi K2.5 (Reasoning) scored 60.6%. GPT-5.2 wins this benchmark. - Source ↗
GPQA
KnowledgeA 92.4%B 87.6%Winner: GPT-5.2Δ 4.8GPQA: GPT-5.2 scored 92.4%; Kimi K2.5 (Reasoning) scored 87.6%. GPT-5.2 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 80%B 76.8%Winner: GPT-5.2Δ 3.2SWE-bench Verified: GPT-5.2 scored 80%; Kimi K2.5 (Reasoning) scored 76.8%. GPT-5.2 wins this benchmark. - Source ↗
MMMU-Pro
MultimodalA 79.5%B 78.5%Winner: GPT-5.2Δ 1MMMU-Pro: GPT-5.2 scored 79.5%; Kimi K2.5 (Reasoning) scored 78.5%. GPT-5.2 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2 | Kimi K2.5 (Reasoning) | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Kimi K2.5 (Reasoning) has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.273 tok/s | Kimi K2.5 (Reasoning)Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | Kimi K2.5 (Reasoning)Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | Kimi K2.5 (Reasoning)128K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.2 wins10 benchmarks
| Benchmark | GPT-5.2 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| BrowseCompSource | 65.8% | 60.6% | GPT-5.2 leads |
| OSWorld-VerifiedSource | 47.3% | — | Not comparable |
| τ²-bench resultsSource | 84.8% | 95.9% | Kimi K2.5 (Reasoning) leads |
| Gert LabsSource | 46.54% | 32.58% | GPT-5.2 leads |
| JobBenchSource | 34.3% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 50.8% | Not comparable |
| APEX-Agents-AASource | — | 11.5% | Not comparable |
| AA Agentic IndexSource | — | 21.7% | Not comparable |
| GDPval-AASource | — | 25.4% | Not comparable |
| GDPval-AASource | — | 1009 | Not comparable |
CodingKimi K2.5 (Reasoning) wins5 benchmarks
Reasoning3 benchmarks
KnowledgeGPT-5.2 wins8 benchmarks
| Benchmark | GPT-5.2 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| GPQASource | 92.4% | 87.6% | GPT-5.2 leads |
| Artificial Analysis Intelligence IndexSource | 42.2% | 35.4% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 87.9% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 29.4% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -8.1% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 34.3% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 64.6% | Kimi K2.5 (Reasoning) leads |
| MMLU-ProSource | — | 87.1% | Not comparable |
Math4 benchmarks
MultimodalGPT-5.2 wins6 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | Kimi K2.5 (Reasoning) | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 70.2% | GPT-5.2 leads |
Frequently Asked Questions (5)
Which is better, GPT-5.2 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) is ahead on BenchLM's BenchAlign leaderboard, 59.35 to 58.43. The biggest single separator in this matchup is BrowseComp, where the scores are 65.8% and 60.6%.
Which is better for knowledge tasks, GPT-5.2 or Kimi K2.5 (Reasoning)?
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 87.2. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GPT-5.2 or Kimi K2.5 (Reasoning)?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 70.6. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GPT-5.2 or Kimi K2.5 (Reasoning)?
GPT-5.2 has the edge for agentic tasks in this comparison, averaging 55.7 versus 55. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.
Which is better for multimodal and grounded tasks, GPT-5.2 or Kimi K2.5 (Reasoning)?
GPT-5.2 has the edge for multimodal and grounded tasks in this comparison, averaging 80.4 versus 78.5. Inside this category, Design Arena Website is the benchmark that creates the most daylight between them.
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