Model comparison
Kimi K2.5 (Reasoning) vs Laguna M.1
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Kimi K2.5 (Reasoning) #64 (Estimated); Laguna M.1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Kimi K2.5 (Reasoning) and Laguna M.1 share 2 comparable benchmark results. 2 of 8 categories are comparable. 25 results are unique to Kimi K2.5 (Reasoning); 3 to Laguna M.1.
Updated July 27, 2026- Shared results
- 2
- Kimi K2.5 (Reasoning) only
- 25
- Laguna M.1 only
- 3
- Comparable categories
- 2 / 8
Treat this as a split decision. Kimi K2.5 (Reasoning) makes more sense if coding is the priority; Laguna M.1 is the better fit if you need the larger 256K context window.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 2 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) and Laguna M.1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Laguna M.1 gives you the larger context window at 256K, 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 | Kimi K2.5 (Reasoning) | Δ | Laguna M.1 |
|---|---|---|---|
| Coding | Kimi K2.5 (Reasoning)76.8 | Margin← 12.0 | Laguna M.164.8 |
| Agentic | Kimi K2.5 (Reasoning)55.0 | Margin← 9.2 | Laguna M.145.8 |
| Knowledge | Kimi K2.5 (Reasoning)87.2 | MarginNo overlap | Laguna M.1Not measured |
| Multimodal | Kimi K2.5 (Reasoning)78.5 | MarginNo overlap | Laguna M.1Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 50.8%B 45.8%Winner: Kimi K2.5 (Reasoning)Δ 5Terminal-Bench 2.0: Kimi K2.5 (Reasoning) scored 50.8%; Laguna M.1 scored 45.8%. Kimi K2.5 (Reasoning) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 76.8%B 74.6%Winner: Kimi K2.5 (Reasoning)Δ 2.2SWE-bench Verified: Kimi K2.5 (Reasoning) scored 76.8%; Laguna M.1 scored 74.6%. 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 | Kimi K2.5 (Reasoning) | Laguna M.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Kimi K2.5 (Reasoning)$0.6 input / $3 output | Laguna M.1Not available | A complete price comparison is not available. |
| Generation speedtokens per second | Kimi K2.5 (Reasoning)Not available | Laguna M.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Kimi K2.5 (Reasoning)Not available | Laguna M.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Kimi K2.5 (Reasoning)128K | Laguna M.1256K | Laguna M.1 lists the larger context window. |
Benchmark Deep Dive
AgenticKimi K2.5 (Reasoning) wins8 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Laguna M.1 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 50.8% | 45.8% | Kimi K2.5 (Reasoning) leads |
| BrowseCompSource | 60.6% | — | Not comparable |
| APEX-Agents-AASource | 11.5% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | — | Not comparable |
| Gert LabsSource | 32.58% | — | Not comparable |
| AA Agentic IndexSource | 21.7% | — | Not comparable |
| GDPval-AASource | 25.1% | — | Not comparable |
| GDPval-AASource | 1003 | — | Not comparable |
CodingKimi K2.5 (Reasoning) wins7 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Laguna M.1 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 76.8% | 74.6% | Kimi K2.5 (Reasoning) leads |
| Vibe Code BenchSource | 17.54% | — | Not comparable |
| AA-SciCodeSource | 49.0% | — | Not comparable |
| AA Coding IndexSource | 46.8% | — | Not comparable |
| SWE MultilingualSource | — | 63.1% | Not comparable |
| SWE-bench ProSource | — | 49.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 45.8% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Laguna M.1 | Result |
|---|---|---|---|
| GPQASource | 87.6% | — | Not comparable |
| MMLU-ProSource | 87.1% | — | 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 |
Math1 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Laguna M.1 | Result |
|---|---|---|---|
| AIME 2025Source | 96.1% | — | Not comparable |
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Kimi K2.5 (Reasoning) | Laguna M.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 70.2% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, Kimi K2.5 (Reasoning) or Laguna M.1?
Kimi K2.5 (Reasoning) and Laguna M.1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Kimi K2.5 (Reasoning) or Laguna M.1?
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 64.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Kimi K2.5 (Reasoning) or Laguna M.1?
Kimi K2.5 (Reasoning) has the edge for agentic tasks in this comparison, averaging 55 versus 45.8. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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